function_minimizer Class Reference

Description not yet available. More...

#include <admodel.h>

Public Member Functions
	function_minimizer (long int sz=0L)
virtual	~function_minimizer ()
	Destructor. More...
virtual void	AD_uf_inner ()
virtual void	AD_uf_outer ()
void	adamoeba (const dmatrix &p, const dvector &y, int ndim, double ftol, int maxfn)
	Nelder-Mead simplex alogrithm. More...
double	adapt_eps (int ii, int iseps, double eps, double alpha, double &adapt_delta, double &mu, dvector &epsvec, dvector &epsbar, dvector &Hbar)
void	add_sample_dense (const int nvar, int &is2, dvector &m, dmatrix &m2, const independent_variables &q)
	Calculate running covariance using Welford's "online" algorithm. More...
void	add_sample_diag (const int nvar, int &n, dvector &m, dvector &m2, const independent_variables &q)
	Calculate running covariance using Welford's "online" algorithm. More...
dvariable	adromb (_func func, double a, double b, int ns=9)
	Romberg integration. More...
dvariable	adromb (_func func, const dvariable &a, double b, int ns=9)
	Romberg integration. More...
dvariable	adromb (_func func, const dvariable &a, const dvariable &b, int ns=9)
	Romberg integration. More...
dvariable	adromb (_func func, double a, const dvariable &b, int ns=9)
	Romberg integration. More...
dvariable	adrombo (_func func, double a, double b, int ns=9)
dvariable	adrombo (_func func, const dvariable &a, double b, int ns=9)
dvariable	adrombo (_func func, const dvariable &a, const dvariable &b, int ns=9)
dvariable	adrombo (_func func, double a, const dvariable &b, int ns=9)
virtual void	allocate ()
double	amxxx (const dmatrix &p, const dvector &y, const dvector &psum, int ndim, int ihi, double fac)
	Description not yet available. More...
void	begin_df1b2_funnel (void)
void	begin_funnel_stuff (void)
void	begin_gauss_hermite_stuff (void)
virtual void	between_phases_calculations (void)
void	build_tree (int nvar, dvector &gr, dmatrix &chd, double eps, dvector &p, dvector &y, dvector &gr2, double logu, int v, int j, double H0, dvector &_thetaprime, dvector &_thetaplus, dvector &_thetaminus, dvector &_rplus, dvector &_rminus, double &_alphaprime, int &_nalphaprime, bool &_sprime, int &_nprime, int &_nfevals, bool &_divergent, const random_number_generator &rng, dvector &gr2_end, dvector &_grprime, dvector &_gr2prime, double &_nllprime, double &_Hprime, independent_variables &_parsaveprime)
bool	calculate_chd_and_inverse (int nvar, const dmatrix &metric, dmatrix &chd, dmatrix &chdinv)
	Calculate the Cholesky decomposition and its inverse given a mass matrix. More...
bool	choleski_decomp_hmc (const dmatrix &metric, dmatrix &L)
void	computations (int argc, char *argv[])
void	computations (void)
void	computations1 (int argc, char *argv[])
void	computations_np (int argc, char *argv[])
int	compute_next_window (int i, int warmup, int w1, int aws, int w3)
int	constrained_minimization2 (int _n, int _nh, int _ng, dvector &__x)
void	constraint_report (void)
virtual void	constraints_minimize (void)
virtual void	deallocate ()
dmatrix	dep_hess_routine (const dvariable &dep)
	Description not yet available. More...
void	depvars_routine (void)
	Calculate the derivatives of dependent variables with respect to the independent variables. More...
dmatrix	diag_hess_routine (void)
double	diag_projected_hess_determinant (const dvector &g, const int underflow_flag, dmatrix &dh)
dvariable	do_gauss_hermite_integration (void)
int	ef_ (double *f, double *x)
void	end_df1b2_funnel (void)
void	end_df1b2_funnel_stuff (void)
void	end_gauss_hermite_stuff (void)
void	end_get_importance_sampling_comnponent (void)
double	exprnd (double p)
virtual void	final_calcs (void)
double	find_reasonable_stepsize (int nvar, dvector y, dvector p, dmatrix &chd, bool verbose_adapt_mass, bool verbose_find_epsilon, int chain)
void	function_evaluation_block_pvm_slave (void)
void	function_evaluation_block_pvm_slave_random_effects (int nvar, int _crit, independent_variables &x, const dvector &g, const double &f)
void	function_evaluation_block_pvm_slave_random_effects (void)
void	get_bigS (int ndvar, int nvar1, int nvar, dmatrix &S, dmatrix &BS, dvector &scale)
	Description not yet available. More...
std::string	get_filename (const char *f)
void	get_function_difference (void)
dmatrix &	get_hessian ()
dmatrix &	get_hessian_inverse ()
double	get_hybrid_monte_carlo_value (int nvar, const independent_variables &y, dvector &g)
	Written by Dave, commented by Cole starting 8/31/2016 Description not yet available. More...
double	get_ln_det_value () const
double	get_monte_carlo_value (int nvar, const independent_variables &x)
double	get_monte_carlo_value (int nvar, const independent_variables &x, dvector &g)
double	get_monte_carlo_value (int nvar, const dvector &x)
void	get_particular_grad (int iprof, int nvar, const dvector &fg, const dvector &g)
double	hess_determinant (int underflow_flag)
bool	hess_inv ()
	Symmetrize and invert the hessian. More...
void	hess_routine (void)
void	hess_routine_and_constraint (int iprof, const dvector &g, dvector &fg)
void	hess_routine_master (void)
void	hess_routine_noparallel (void)
void	hess_routine_noparallel_random_effects (void)
	Description not yet available. More...
void	hess_routine_noparallel_randomeffects (void)
void	hess_routine_random_effects (void)
	Description not yet available. More...
void	hess_routine_slave (void)
void	hess_routine_slave_random_effects (void)
	Description not yet available. More...
void	hess_step ()
	hess_step is used for HMC. See details in function_minimizer::hess_step. More...
void	hybrid_mcmc_routine (int, int, double, int)
	Description not yet available. More...
double	leapfrog (int nvar, dvector &gr, dmatrix &chd, double eps, dvector &p, dvector &x, dvector &gr2)
	Function to take a single HMC leapfrog step, given current position and momentum variables. More...
void	likeprof_routine (double global_min)
void	limited_memory_quasi_newton (const independent_variables &, int)
void	limited_memory_quasi_newton (const independent_variables &, int, int)
void	limited_memory_quasi_newton (double &f, const independent_variables &, int, int, int, double)
void	limited_memory_quasi_newton_block (int nvar, int _crit, independent_variables &x, const dvector &_g, const double &_f, int nsteps)
	Description not yet available. More...
void	mcmc_computations (void)
void	mcmc_eval (void)
	Description not yet available. More...
void	mcmc_routine (int, int, double, int)
	Monte Carlo Markov Chain minimization routine Approximate the target distribution by performing a random walk across parameter space, integrating at each step. More...
virtual void	minimize (void)
void	monte_carlo_routine (void)
void	multint (int n, const dvar_vector &a, const dvar_vector &b, const dvar_vector &h, double al, int m, const dvariable &e, const dvariable &aint, const int &key, PMFVI f)
void	multint4 (int n, const dvar_vector &a, const dvar_vector &b, const dvar_vector &h, double al, int m, const dvariable &e, const dvariable &aint1, const dvariable &aint2, dvariable &aint3, const dvariable &aint4, const int &key, PMFVIV4 f)
void	neldmead (int n, dvector &_start, dvector &_xmin, double *ynewlo, double reqmin, double delta, int *icount, int *numres, int *ifault)
	Nelder-Mead simplex alogrithm. More...
void	normalize_posterior_distribution (double udet, const dvector &siglevel, const ofstream &ofs2, int num_pp, const dvector &all_values, const dmatrix &actual_value, double global_min, int offset, const dmatrix &lprof, const dmatrix &ldet, const dmatrix &xdist, const dmatrix &penalties)
void	nuts_mcmc_routine (int, int, double, int)
	The function implements the MCMC algorithm NUTS, which is a self-tuning variant of Hamiltonian Monte Carlo. More...
virtual void	other_calculations (void)
void	other_separable_stuff_begin (void)
void	other_separable_stuff_end (void)
void	pre_user_function (void)
	Description not yet available. More...
void	pre_userfunction (void)
void	print_mcmc_progress (int is, int nmcmc, int nwarmup, int chain, int refresh)
void	print_mcmc_timing (double time_warmup, double time_total, int chain)
void	prof_hess_routine (int ip, double new_value, double final_weight)
void	prof_minimize (int iprof, double sigma, double new_value, const double &fprof, const int underflow_flag, double global_min, const double &penalties, const double &final_weight)
void	prof_minimize_re (int iprof, double sigma, double new_value, const double &fprof, const int underflow_flag, double global_min, const double &penalties, const double &final_weight)
double	projected_hess_determinant (const dvector &g, const int underflow_flag, const dvector &xscale, const double &ln_det_proj_jac)
double	projected_hess_determinant (const dvector &g, const int underflow_flag)
double	projected_hess_determinant (const dmatrix &hh, const dvector &g, const int underflow_flag)
double	projected_hess_determinant (const dvector &fg, const dvector &g, const int underflow_flag, const dvector &curvscale, const dvector &xscale, double &ln_det_proj_jac, const double &tmp, const dmatrix &hesses)
double	projected_jacobian (const dvector &g, const dvector &xscale)
void	pvm_master_function_evaluation (double &f, independent_variables &x, const dvector &g, int nvar)
void	pvm_master_function_evaluation_no_derivatives (double &f, independent_variables &x, int nvar)
void	pvm_master_function_evaluation_profile (double &f, independent_variables &x, const dvector &g, int nvar, int iprof, double weight, double new_value)
double	pvm_master_get_monte_carlo_value (int nvar, const dvector &x)
void	pvm_master_mcmc_computations (void)
void	pvm_master_mcmc_routine (int nmcmc, int iseed0, double dscale, int restart_flag)
void	pvm_master_prof_minimize (int iprof, double sigma, double new_value, const double &_fprof, const int underflow_flag, double global_min, const double &_penalties, const double &_final_weight)
void	pvm_slave_function_evaluation (void)
void	pvm_slave_function_evaluation_no_derivatives (void)
void	pvm_slave_function_evaluation_noder (void)
void	pvm_slave_get_monte_carlo_value (int nvar)
void	pvm_slave_likeprof_routine (void)
void	pvm_slave_mcmc_computations (void)
void	pvm_slave_mcmc_routine (void)
void	pvm_slave_prof_minimize (int underflow_flag)
void	quasi_newton_block (int nvar, int crit, independent_variables &x, const dvector &g, const double &f)
	Description not yet available. More...
void	quasi_newton_block_pvm_master (int nvar, int _crit, independent_variables &x, const dvector &g, const double &f)
void	quasi_newton_block_pvm_master_random_effects (int nvar, int _crit, independent_variables &x, const dvector &g, const double &f)
void	quasi_newton_minimizer1 (int nvar, double _crit, double &f, const independent_variables &x, const dvector &g)
dvariable	random_effects_maximization (const dvar_vector &v)
void	read_mle_hmc (int nvar, dvector &mle)
dvector	rotate_gradient (const dvector &x, const dmatrix &m)
dvector	rotate_pars (const dvector &m, const dvector &x)
dvector	rotate_pars (const dmatrix &m, const dvector &x)
void	rwm_mcmc_routine (int, int, double, int)
void	sd_routine (void)
void	set_initial_simplex (const dmatrix &p, const dvector &y, int nvar, const dvector &x, double delta)
void	set_multinomial_weights (dvector &d)
virtual void	set_runtime (void)
virtual void	set_runtime_crit (const char *)
virtual void	set_runtime_maxfn (const char *)
void	setup_quadprior_calcs (void)
void	sgibbs_mcmc_routine (int, int, double, int)
void	shmc_mcmc_routine (int, int, double, int)
bool	slow_phase (int is, int warmup, int w1, int w3)
void	sob_routine (int nmcmc, double dscale, int restart_flag)
void	sobol_importance_routine (int nmcmc, int iseed0, double dscale, int restart_flag)
void	start_get_importance_sampling_comnponent (void)
bool	stop_criterion (int nvar, dvector &thetaminus, dvector &thetaplus, dvector &rminus, dvector &rplus)
void	top_mcmc_routine (int, int, double, int)
dvariable	trapzd (void *, double a, double b, int n)
dvariable	trapzd (_func func, double a, double b, int n)
	Extended trapezoid rule. More...
dvariable	trapzd (_func func, double a, const dvariable &b, int n)
	Extended trapezoid rule. More...
dvariable	trapzd (_func func, const dvariable &a, double b, int n)
	Extended trapezoid rule. More...
dvariable	trapzd (_func func, const dvariable &a, const dvariable &b, int n)
	Extended trapezoid rule. More...
void	trust_region_update (int nvar, int _crit, independent_variables &x, const dvector &_g, const double &_f)
	Description not yet available. More...
double	unrestricted_hess_determinant (void)
virtual dvar_matrix	user_d2frandeff (const dvar_vector &x)
virtual dvar_vector	user_dfrandeff (const dvar_vector &x)
virtual void	user_function ()
virtual dvariable	user_randeff (const dvar_vector &x)
virtual void	userfunction (void)=0

Static Public Member Functions
static int	inner_opt (void)

Public Attributes
double	crit
double	dfn
int	diagonal_metric_flag
long	iexit
long	ifn
long	ihang
long	ihflag
int	imax
int	iprint
laplace_approximation_calculator *	lapprox
int	maxfn
int	maxfn_flag
int	mcmc2_flag
double	min_improve
dvector *	multinomial_weights
dmatrix *	negdirections
int	quit_flag
int	repeatminflag
int	robust_hybrid_flag
int	scroll_flag
int	spminflag

Static Public Attributes
static int	bad_step_flag =0
static int	constraint_exit_number
static int	first_hessian_flag =0
static int	inner_opt_flag =0
static int	likeprof_flag
static int	negative_eigenvalue_flag =0
static int	output_flag = defaults::output
static named_dvar_vector *	pg
static named_dvar_vector *	ph
static int	random_effects_flag =0
static int	test_trust_flag =0

Protected Member Functions
virtual void	report (const dvector &gradients)
void	report_function_minimizer_stats (void)

Protected Attributes
double	ffbest

Static Protected Attributes
static dvector	convergence_criteria
static int	have_constraints =0
static dvector	maximum_function_evaluations
static int	sd_flag
static adstring	user_data_file
static adstring	user_par_file

Private Member Functions
dvariable	do_gauss_hermite_integration_multi (void)

Private Attributes
dmatrix	_hessian
dmatrix	_hessian_inverse
double	_ln_det_value
adstring_array	param_labels
ivector	param_size
gradient_structure *	pgs

Friends
class	equality_constraint_vector
class	inequality_constraint_vector

Detailed Description

Description not yet available.

Parameters

Definition at line 1850 of file admodel.h.

Constructor & Destructor Documentation

function_minimizer::function_minimizer

(

long int

sz = 0L

)

Definition at line 553 of file xmodelm3.cpp.

function_minimizer::~function_minimizer ( )

virtual

Destructor.

Definition at line 633 of file xmodelm3.cpp.

Member Function Documentation

void function_minimizer::AD_uf_inner ( )

virtual

Definition at line 40 of file xmodelm4.cpp.

Referenced by laplace_approximation_calculator::check_hessian_type(), laplace_approximation_calculator::default_calculations_check_derivatives(), laplace_approximation_calculator::do_one_feval(), evaluate_function(), evaluate_function_gradient(), evaluate_function_no_derivatives(), evaluate_function_quiet(), evaluate_function_with_quadprior(), laplace_approximation_calculator::get_fx_fu(), laplace_approximation_calculator::get_gradient_lme(), laplace_approximation_calculator::get_gradient_lme_hp(), laplace_approximation_calculator::get_uhat_lm_newton2(), laplace_approximation_calculator::get_uhat_quasi_newton(), and laplace_approximation_calculator::get_uhat_quasi_newton_block_diagonal().

void function_minimizer::AD_uf_outer ( )

virtual

Definition at line 39 of file xmodelm4.cpp.

Referenced by calculate_importance_sample(), calculate_importance_sample_block_diagonal(), calculate_importance_sample_block_diagonal_funnel(), calculate_importance_sample_block_diagonal_option2(), calculate_importance_sample_block_diagonal_option_antithetical(), calculate_importance_sample_funnel(), calculate_importance_sample_shess(), calculate_laplace_approximation(), do_gauss_hermite_block_diagonal(), and do_gauss_hermite_block_diagonal_multi().

void function_minimizer::adamoeba	(	const dmatrix &	_p,
		const dvector &	_y,
		int	ndim,
		double	ftol,
		int	nfunk
	)

Nelder-Mead simplex alogrithm.

Parameters

_p	Matrix
_y	Vector
ndim	Integer
ftol	Double
nfunk	Integer

The implementation of this algorithm was inspired by "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 10

Deprecated:

User should use the neldmead function

Definition at line 38 of file amoeba.cpp.

Referenced by minimize().

double function_minimizer::adapt_eps	(	int	ii,
		int	iseps,
		double	eps,
		double	alpha,
		double &	adapt_delta,
		double &	mu,
		dvector &	epsvec,
		dvector &	epsbar,
		dvector &	Hbar
	)

Definition at line 234 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine(), and shmc_mcmc_routine().

void function_minimizer::add_sample_dense	(	const int	nvar,
		int &	n,
		dvector &	m,
		dmatrix &	m2,
		const independent_variables &	q
	)

Calculate running covariance using Welford's "online" algorithm.

Parameters

n

is a count of samples m is a running vector of means (initialized at 0) m2 is a running vector of unscaled variances (initalized at 0) q is a vector of the new parameters used to update returns updated n, m, and m2 via reference m2/(n-1) is the covariance through n samples this is loosely based off of Stan's algorithm: welford_covar_estimator.hpp

Definition at line 621 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

void function_minimizer::add_sample_diag	(	const int	nvar,
		int &	n,
		dvector &	m,
		dvector &	m2,
		const independent_variables &	q
	)

Calculate running covariance using Welford's "online" algorithm.

Parameters

n

is a count of samples m is a running vector of means (initialized at 0) m2 is a running matrix of unscaled covariance (initalized at 0) q is a vector of the new parameters used to update returns updated n, m, and m2 via reference m2/(n-1) is the covariance through n samples this is loosely based off of Stan's algorithm: welford_covar_estimator.hpp

Definition at line 598 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

dvariable function_minimizer::adromb	(	_func	func,
		double	a,
		double	b,
		int	ns = 9
	)

Romberg integration.

Parameters

func	Pointer to a member function of class model_parameters.
a	Lower limit of integration.
b	Upper limit of inegration.
ns

Returns

The integral of the function from a to b using Romberg's method

Definition at line 40 of file dfqromb.cpp.

dvariable function_minimizer::adromb	(	_func	func,
		const dvariable &	a,
		double	b,
		int	ns = 9
	)

Romberg integration.

Parameters

func	Pointer to a member function of class model_parameters.
a	Lower limit of integration.
b	Upper limit of inegration.
ns

Returns

The integral of the function from a to b using Romberg's method

Definition at line 69 of file dfqromb.cpp.

dvariable function_minimizer::adromb	(	_func	func,
		const dvariable &	a,
		const dvariable &	b,
		int	ns = 9
	)

Romberg integration.

Parameters

func	Pointer to a member function of class model_parameters.
a	Lower limit of integration.
b	Upper limit of inegration.
ns

Returns

The integral of the function from a to b using Romberg's method

Definition at line 127 of file dfqromb.cpp.

dvariable function_minimizer::adromb	(	_func	func,
		double	a,
		const dvariable &	b,
		int	ns = 9
	)

Romberg integration.

Parameters

func	Pointer to a member function of class model_parameters.
a	Lower limit of integration.
b	Upper limit of inegration.
ns

Returns

The integral of the function from a to b using Romberg's method

Definition at line 98 of file dfqromb.cpp.

dvariable function_minimizer::adrombo	(	_func	func,
		double	a,
		double	b,
		int	ns = 9
	)

dvariable function_minimizer::adrombo	(	_func	func,
		const dvariable &	a,
		double	b,
		int	ns = 9
	)

dvariable function_minimizer::adrombo	(	_func	func,
		const dvariable &	a,
		const dvariable &	b,
		int	ns = 9
	)

dvariable function_minimizer::adrombo	(	_func	func,
		double	a,
		const dvariable &	b,
		int	ns = 9
	)

virtual void function_minimizer::allocate ( void  )

inlinevirtual

Definition at line 1903 of file admodel.h.

Referenced by limited_memory_quasi_newton_block(), prof_minimize_re(), quasi_newton_block(), and trust_region_update().

double function_minimizer::amxxx	(	const dmatrix &	_p,
		const dvector &	_y,
		const dvector &	_psum,
		int	ndim,
		int	ihi,
		double	fac
	)

Description not yet available.

Parameters

Definition at line 107 of file amoeba.cpp.

Referenced by adamoeba().

void function_minimizer::begin_df1b2_funnel ( void  )

inline

Definition at line 1877 of file admodel.h.

void function_minimizer::begin_funnel_stuff

(

void

)

Definition at line 803 of file xmodelm3.cpp.

void function_minimizer::begin_gauss_hermite_stuff

(

void

)

Definition at line 761 of file xmodelm3.cpp.

Referenced by begin_funnel_stuff().

virtual void function_minimizer::between_phases_calculations ( void  )

inlinevirtual

Definition at line 1937 of file admodel.h.

Referenced by minimize().

void function_minimizer::build_tree	(	int	nvar,
		dvector &	gr,
		dmatrix &	chd,
		double	eps,
		dvector &	p,
		dvector &	y,
		dvector &	gr2,
		double	logu,
		int	v,
		int	j,
		double	H0,
		dvector &	_thetaprime,
		dvector &	_thetaplus,
		dvector &	_thetaminus,
		dvector &	_rplus,
		dvector &	_rminus,
		double &	_alphaprime,
		int &	_nalphaprime,
		bool &	_sprime,
		int &	_nprime,
		int &	_nfevals,
		bool &	_divergent,
		const random_number_generator &	rng,
		dvector &	gr2_end,
		dvector &	_grprime,
		dvector &	_gr2prime,
		double &	_nllprime,
		double &	_Hprime,
		independent_variables &	_parsaveprime
	)

Definition at line 75 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

bool function_minimizer::calculate_chd_and_inverse	(	int	nvar,
		const dmatrix &	metric,
		dmatrix &	chd,
		dmatrix &	chdinv
	)

Calculate the Cholesky decomposition and its inverse given a mass matrix.

Parameters

nvar	Number of active parameters metric Mass matrix chd Choleksy decomposition, updated via reference chdinv Inverse of chd, updated via reference returns nothing except updated matrices by reference

Definition at line 641 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

bool function_minimizer::choleski_decomp_hmc	(	const dmatrix &	metric,
		dmatrix &	L
	)

what is this?

Definition at line 686 of file hmc_functions.cpp.

Referenced by calculate_chd_and_inverse().

void function_minimizer::computations	(	int	argc,
		char *	argv[]
	)

Definition at line 39 of file modspmin.cpp.

void function_minimizer::computations

(

void

)

Definition at line 397 of file modspmin.cpp.

void function_minimizer::computations1	(	int	argc,
		char *	argv[]
	)

Definition at line 138 of file modspmin.cpp.

Referenced by computations(), and hess_step().

void function_minimizer::computations_np	(	int	argc,
		char *	argv[]
	)

int function_minimizer::compute_next_window	(	int	i,
		int	warmup,
		int	w1,
		int	aws,
		int	w3
	)

Definition at line 34 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

int function_minimizer::constrained_minimization2	(	int	_n,
		int	_nh,
		int	_ng,
		dvector &	__x
	)

void function_minimizer::constraint_report

(

void

)

virtual void function_minimizer::constraints_minimize ( void  )

virtual

Referenced by computations1().

virtual void function_minimizer::deallocate ( void  )

inlinevirtual

Definition at line 1904 of file admodel.h.

Referenced by quasi_newton_block().

dmatrix function_minimizer::dep_hess_routine

(

const dvariable &

dep

)

Description not yet available.

Parameters

Definition at line 16 of file dep_hess.cpp.

void function_minimizer::depvars_routine

(

void

)

Calculate the derivatives of dependent variables with respect to the independent variables.

Definition at line 488 of file mod_hess.cpp.

Referenced by computations1(), and hess_step().

dmatrix function_minimizer::diag_hess_routine

(

void

)

double function_minimizer::diag_projected_hess_determinant	(	const dvector &	g,
		const int	underflow_flag,
		dmatrix &	dh
	)

dvariable function_minimizer::do_gauss_hermite_integration

(

void

)

Definition at line 12 of file xmodelm5.cpp.

Referenced by do_gauss_hermite_block_diagonal(), and do_gauss_hermite_block_diagonal_multi().

dvariable function_minimizer::do_gauss_hermite_integration_multi ( void  )

private

Definition at line 31 of file xmodelm5.cpp.

Referenced by do_gauss_hermite_integration().

int function_minimizer::ef_	(	double *	f,
		double *	x
	)

void function_minimizer::end_df1b2_funnel ( void  )

inline

Definition at line 1879 of file admodel.h.

void function_minimizer::end_df1b2_funnel_stuff

(

void

)

Definition at line 830 of file xmodelm3.cpp.

void function_minimizer::end_gauss_hermite_stuff

(

void

)

Definition at line 863 of file xmodelm3.cpp.

Referenced by end_df1b2_funnel_stuff().

void function_minimizer::end_get_importance_sampling_comnponent

(

void

)

Definition at line 785 of file xmodelm3.cpp.

Referenced by end_df1b2_funnel_stuff().

double function_minimizer::exprnd

(

double

p

)

virtual void function_minimizer::final_calcs ( void  )

inlinevirtual

Definition at line 1934 of file admodel.h.

Referenced by computations().

double function_minimizer::find_reasonable_stepsize	(	int	nvar,
		dvector	y,
		dvector	p,
		dmatrix &	chd,
		bool	verbose_adapt_mass,
		bool	verbose_find_epsilon,
		int	chain
	)

Definition at line 331 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

void function_minimizer::function_evaluation_block_pvm_slave

(

void

)

Referenced by minimize().

void function_minimizer::function_evaluation_block_pvm_slave_random_effects	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	g,
		const double &	f
	)

void function_minimizer::function_evaluation_block_pvm_slave_random_effects

(

void

)

Referenced by minimize().

void function_minimizer::get_bigS	(	int	ndvar,
		int	nvar1,
		int	nvar,
		dmatrix &	S,
		dmatrix &	BS,
		dvector &	scale
	)

Description not yet available.

Parameters

Definition at line 15 of file getbigs.cpp.

Referenced by sd_routine().

std::string function_minimizer::get_filename

(

const char *

f

)

Definition at line 63 of file hmc_functions.cpp.

Referenced by hess_step(), nuts_mcmc_routine(), and rwm_mcmc_routine().

void function_minimizer::get_function_difference

(

void

)

Definition at line 823 of file xmodelm3.cpp.

Referenced by end_df1b2_funnel_stuff().

dmatrix& function_minimizer::get_hessian ( )

inline

Definition at line 2192 of file admodel.h.

dmatrix& function_minimizer::get_hessian_inverse ( )

inline

Definition at line 2193 of file admodel.h.

double function_minimizer::get_hybrid_monte_carlo_value	(	int	nvar,
		const independent_variables &	y,
		dvector &	g
	)

Written by Dave, commented by Cole starting 8/31/2016 Description not yet available.

Parameters

y	is vector of Choleski rotated parameters (i.e., unbounded space; y=chd*x where x is algorithm space). g is a vector of empty gradients returns the negative log likelihood (density), but also stores gradients at y in g

Definition at line 258 of file hmc_functions.cpp.

Referenced by find_reasonable_stepsize(), hybrid_mcmc_routine(), leapfrog(), nuts_mcmc_routine(), and shmc_mcmc_routine().

double function_minimizer::get_ln_det_value ( ) const

inline

Definition at line 2190 of file admodel.h.

double function_minimizer::get_monte_carlo_value	(	int	nvar,
		const independent_variables &	x
	)

Definition at line 11 of file mod_mc2.cpp.

Referenced by mcmc_eval(), mcmc_routine(), monte_carlo_routine(), and rwm_mcmc_routine().

double function_minimizer::get_monte_carlo_value	(	int	nvar,
		const independent_variables &	x,
		dvector &	g
	)

Definition at line 75 of file mod_mc2.cpp.

double function_minimizer::get_monte_carlo_value	(	int	nvar,
		const dvector &	x
	)

Definition at line 10 of file mod_mc4.cpp.

void function_minimizer::get_particular_grad	(	int	iprof,
		int	nvar,
		const dvector &	fg,
		const dvector &	g
	)

Definition at line 175 of file newmodm2.cpp.

Referenced by likeprof_routine().

double function_minimizer::hess_determinant

(

int

underflow_flag

)

Definition at line 10 of file modhdet.cpp.

bool function_minimizer::hess_inv

(

void

)

Symmetrize and invert the hessian.

Definition at line 574 of file mod_hess.cpp.

Referenced by computations1(), and hess_step().

void function_minimizer::hess_routine

(

void

)

Definition at line 21 of file mod_hess.cpp.

Referenced by computations1(), and hess_step().

void function_minimizer::hess_routine_and_constraint	(	int	iprof,
		const dvector &	g,
		dvector &	fg
	)

Definition at line 215 of file mod_hess.cpp.

void function_minimizer::hess_routine_master

(

void

)

Referenced by hess_routine().

void function_minimizer::hess_routine_noparallel

(

void

)

Definition at line 61 of file mod_hess.cpp.

Referenced by hess_routine().

void function_minimizer::hess_routine_noparallel_random_effects

(

void

)

Description not yet available.

Parameters

Definition at line 129 of file mod_rhes.cpp.

Referenced by hess_routine_random_effects().

void function_minimizer::hess_routine_noparallel_randomeffects

(

void

)

void function_minimizer::hess_routine_random_effects

(

void

)

Description not yet available.

Parameters

Definition at line 99 of file mod_rhes.cpp.

Referenced by hess_routine().

void function_minimizer::hess_routine_slave

(

void

)

Referenced by hess_routine().

void function_minimizer::hess_routine_slave_random_effects

(

void

)

Description not yet available.

Parameters

Definition at line 556 of file mod_rhes.cpp.

Referenced by hess_routine_random_effects().

void function_minimizer::hess_step

(

)

hess_step is used for HMC. See details in function_minimizer::hess_step.

Feature to try and get closer to the optimal point (minimum) using Newton steps with the inverse Hessian.

If successful it gives evidence that the mode has been reached and the nearby curvature is well approximated by a quadratic form.

Let x be the current MLE parameter vector. Then a single step consists of calculating x'=x-inv(Hessian)*gradient. This calculation is done in the unbounded parameter space.

This feature is initiated by calling "-hess_step N -hess_step_tol eps" to specify the maximum number of steps (N) and a minimum threshold (eps) for the maximum absolute gradient ('maxgrad'), below which is deemed sufficient and causes the function to exit early with success. The defaults are N=5 and eps=1e-12. The function will continue even if the maxgrad gets bigger because often sucessive steps improve the Hessian and can finish successfully. If successful, the new MLE is deemed improved and is propagated through the model to update all output files.

The upside of this feature is it confirms that the geometry near the mode is quadratic and well represented by the Hessian. It may also slightly improve the MLE and uncertainty estimates. The downside is that the Hessian needs to be recalculated and inverted at each step so it is costly computationally.

One technical issue is that because this is run after optimization, the model initialization needs to be considered. If there are inactive parameters in some cases they may not be intialized to what is in the template. A workaround is to specify initial values via the -ainp or -binp arguments, as is standard. Future versions should explore how to automate this, or only warn the user when there are inactive parameters.

Typical usage is to optimize model, then use this feature if convergence is suspect. If it reduces the maxgrad to zero this gives strong evidence for convergence.

Author

Cole Monnahan

Definition at line 49 of file output_checks.cpp.

Referenced by computations().

void function_minimizer::hybrid_mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

Description not yet available.

Parameters

Definition at line 83 of file hybmcmc.cpp.

Referenced by mcmc_computations().

int function_minimizer::inner_opt ( void  )

static

Definition at line 39 of file xmodelm3.cpp.

Referenced by end_df1b2_funnel_stuff(), and pre_userfunction().

double function_minimizer::leapfrog	(	int	nvar,
		dvector &	gr,
		dmatrix &	chd,
		double	eps,
		dvector &	p,
		dvector &	x,
		dvector &	gr2
	)

Function to take a single HMC leapfrog step, given current position and momentum variables.

Returns nll value but also updates position and momentum variables by reference.

Definition at line 408 of file hmc_functions.cpp.

Referenced by build_tree(), find_reasonable_stepsize(), and shmc_mcmc_routine().

void function_minimizer::likeprof_routine

(

double

global_min

)

Definition at line 67 of file mod_pmin.cpp.

Referenced by computations1().

void function_minimizer::limited_memory_quasi_newton	(	const independent_variables &	_x,
		int	m
	)

Definition at line 32 of file lmnewton.cpp.

Referenced by laplace_approximation_calculator::get_uhat_lm_newton(), and minimize().

void function_minimizer::limited_memory_quasi_newton	(	const independent_variables &	,
		int	,
		int
	)

void function_minimizer::limited_memory_quasi_newton	(	double &	f,
		const independent_variables &	_x,
		int	m,
		int	noprintx,
		int	maxfn,
		double	crit
	)

Definition at line 231 of file lmnewton.cpp.

void function_minimizer::limited_memory_quasi_newton_block	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	_g,
		const double &	_f,
		int	nsteps
	)

Description not yet available.

Parameters

Definition at line 23 of file df1b2lmn2.cpp.

Referenced by minimize().

void function_minimizer::mcmc_computations

(

void

)

Definition at line 472 of file modspmin.cpp.

Referenced by computations1().

void function_minimizer::mcmc_eval

(

void

)

Description not yet available.

Parameters

Definition at line 14 of file mceval.cpp.

Referenced by computations().

void function_minimizer::mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

Monte Carlo Markov Chain minimization routine Approximate the target distribution by performing a random walk across parameter space, integrating at each step.

This routine also parses the command line arguments and performs actions for the following ones: -mcdiag Use diagonal covariance matrix with covariance = dscale. -mcrb N Modify covariance matrix to reduce high correlations. 1<=N<=9 where 1=10% and 9=90%. -mcec Read in empirical covariance matrix. This is a file with the program name prepended to extension '.ecm'. -mcpin NAME Read in starting values for MCMC from file NAME. NAME must be a valid ADMB '.par' file. -mcscale Dynamically scales covariance matrix until a reasonable acceptance rate is observed. -nosdmcmc Turn off calculation os sdreport variables during mcsave phase (saves a lot of CPU time). -mcu Use uniform multivariate distributions as bounds, if this is not specified then random normal multivariate distributions will be used. -mcnoscale Don't rescale step size based on acceptance rate. -mcr Continue MCMC from a previous -mcmc call. Uses '.mcm' file to accomplish this. -mcsave N Save parameter values from every Nth simulation instead of every single one. -mcprobe N Use probing strategy, 0.00001<N<=0.499. See the function new_probing_bounded_multivariate_normal() in prmonte.cpp for more detail. -mcgrope Deprecated, equivalent to -mcprobe

Parameters

int	nmcmc The number of MCMC simulations to run.
int	iseed0 Initial seed value for simulations.
double	dscale Scale value used only if -mcdiag is specified.
int	restart_flag Restart the MCMC, even if -mcr is specified.

Returns

Nothing.

Definition at line 126 of file xxmcmc.cpp.

Referenced by mcmc_computations().

void function_minimizer::minimize ( void  )

virtual

Todo:

What does the -uhess option do?

Definition at line 49 of file xmodelm3.cpp.

Referenced by computations(), and computations1().

void function_minimizer::monte_carlo_routine

(

void

)

Definition at line 35 of file mod_mc.cpp.

void function_minimizer::multint	(	int	n,
		const dvar_vector &	a,
		const dvar_vector &	b,
		const dvar_vector &	h,
		double	al,
		int	m,
		const dvariable &	e,
		const dvariable &	aint,
		const int &	key,
		PMFVI	f
	)

void function_minimizer::multint4	(	int	n,
		const dvar_vector &	a,
		const dvar_vector &	b,
		const dvar_vector &	h,
		double	al,
		int	m,
		const dvariable &	e,
		const dvariable &	aint1,
		const dvariable &	aint2,
		dvariable &	aint3,
		const dvariable &	aint4,
		const int &	key,
		PMFVIV4	f
	)

void function_minimizer::neldmead	(	int	n,
		dvector &	_start,
		dvector &	_xmin,
		double *	ynewlo,
		double	reqmin,
		double	delta,
		int *	icount,
		int *	numres,
		int *	ifault
	)

Nelder-Mead simplex alogrithm.

Parameters

n	Integer
_start	Vector
_xmin	Vector
ynewlo	Double
reqmin	Double
delta	Double
icount	Integer pointer
numres	Integer pointer
ifault	Integer pointer

Definition at line 150 of file amoeba.cpp.

Referenced by minimize().

void function_minimizer::normalize_posterior_distribution	(	double	udet,
		const dvector &	siglevel,
		const ofstream &	ofs2,
		int	num_pp,
		const dvector &	all_values,
		const dmatrix &	actual_value,
		double	global_min,
		int	offset,
		const dmatrix &	lprof,
		const dmatrix &	ldet,
		const dmatrix &	xdist,
		const dmatrix &	penalties
	)

Definition at line 63 of file newmodmn.cpp.

Referenced by likeprof_routine().

void function_minimizer::nuts_mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

The function implements the MCMC algorithm NUTS, which is a self-tuning variant of Hamiltonian Monte Carlo.

This function implements the original algorithm of Hoffman and Gelman (2014), namely dynamic trajectory lengths and step size adaptation via the dual averaging algorithm. In addition, it uses a diagonal mass matrix adaptation scheme based on Stan's. Thus, a covariance matrix is not necessary (so it works on models without an invertible Hessian).

This routine also parses the command line arguments and performs actions for the following ones: -adapt_delta Target acceptance rate [0,1]. Defaults to 0.8. -max_treedepth Maximum treedepth. Defaults to 12. Caps trajectory lengths at 2^12 -hyeps The step size to use. If not specified it will be adapted (recommended). -duration The maximum runtime in minutes. -mcdiag Initial mass matrix is unit diagonal -mcpin NAME Read in MCMC starting values for active parameters only from file NAME. -warmup The number of warmup iterations during which adaptation occurs. -refresh How often to refresh the console output (defaults to 10%) -adapt_mass Do diagonal mass matrix adaptation -adapt_mass_dense Do dense mass matrix adaptation -verbose_adapt_mass Flag whether to print mass adaptation updates to console -adapt_window Mass matrix adaptation initial window size

• adapt_init_buffer Mass matrix adaptation initial buffer size
• adapt_term_buffer Mass matrix adaptation terminal buffer size

  Parameters

  int	nmcmc The number of MCMC simulations to run.
  int	iseed0 Initial seed value for simulations.
  double	dscale Scale value used only if -mcdiag is specified. Disabled for NUTS.
  int	restart_flag Restart the MCMC, even if -mcr is specified. Disalbed for NUTS.

  Returns

  Nothing. Creates file <model>.psv with bounded parameters, and various files used by R package adnuts for diagnostics.

Mass matrix and inverse are now ready to be used.

Prepare initial value. Need to both back-transform, and then rotate this to be in the "x" space.

Now z0 is either the MLE or the user specified value

Start initializing the algorithm at the initial point. z0

Definition at line 51 of file nuts.cpp.

Referenced by mcmc_computations().

virtual void function_minimizer::other_calculations ( void  )

inlinevirtual

Definition at line 1933 of file admodel.h.

Referenced by computations().

void function_minimizer::other_separable_stuff_begin

(

void

)

Definition at line 732 of file xmodelm3.cpp.

void function_minimizer::other_separable_stuff_end

(

void

)

Definition at line 748 of file xmodelm3.cpp.

void function_minimizer::pre_user_function

(

void

)

Description not yet available.

Parameters

Definition at line 370 of file df1b2lp8.cpp.

Referenced by laplace_approximation_calculator::block_diagonal_calculations(), laplace_approximation_calculator::check_hessian_type(), laplace_approximation_calculator::check_hessian_type2(), and laplace_approximation_calculator::get_newton_raphson_info_block_diagonal().

void function_minimizer::pre_userfunction

(

void

)

Definition at line 586 of file model7.cpp.

Referenced by depvars_routine(), hess_routine_and_constraint(), hess_routine_noparallel(), limited_memory_quasi_newton_block(), and quasi_newton_block().

void function_minimizer::print_mcmc_progress	(	int	is,
		int	nmcmc,
		int	nwarmup,
		int	chain,
		int	refresh
	)

Definition at line 284 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine(), rwm_mcmc_routine(), and shmc_mcmc_routine().

void function_minimizer::print_mcmc_timing	(	double	time_warmup,
		double	time_total,
		int	chain
	)

Definition at line 298 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine(), rwm_mcmc_routine(), and shmc_mcmc_routine().

void function_minimizer::prof_hess_routine	(	int	ip,
		double	new_value,
		double	final_weight
	)

void function_minimizer::prof_minimize	(	int	iprof,
		double	sigma,
		double	new_value,
		const double &	fprof,
		const int	underflow_flag,
		double	global_min,
		const double &	penalties,
		const double &	final_weight
	)

Definition at line 221 of file newmodm2.cpp.

Referenced by likeprof_routine().

void function_minimizer::prof_minimize_re	(	int	iprof,
		double	sigma,
		double	new_value,
		const double &	fprof,
		const int	underflow_flag,
		double	global_min,
		const double &	penalties,
		const double &	final_weight
	)

Definition at line 17 of file newmodm5.cpp.

Referenced by likeprof_routine().

double function_minimizer::projected_hess_determinant	(	const dvector &	g,
		const int	underflow_flag,
		const dvector &	xscale,
		const double &	ln_det_proj_jac
	)

Definition at line 9 of file nnewmod2.cpp.

double function_minimizer::projected_hess_determinant	(	const dvector &	g,
		const int	underflow_flag
	)

Definition at line 17 of file newmodm2.cpp.

double function_minimizer::projected_hess_determinant	(	const dmatrix &	hh,
		const dvector &	g,
		const int	underflow_flag
	)

double function_minimizer::projected_hess_determinant	(	const dvector &	fg,
		const dvector &	g,
		const int	underflow_flag,
		const dvector &	curvscale,
		const dvector &	xscale,
		double &	ln_det_proj_jac,
		const double &	tmp,
		const dmatrix &	hesses
	)

double function_minimizer::projected_jacobian	(	const dvector &	g,
		const dvector &	xscale
	)

void function_minimizer::pvm_master_function_evaluation	(	double &	f,
		independent_variables &	x,
		const dvector &	g,
		int	nvar
	)

void function_minimizer::pvm_master_function_evaluation_no_derivatives	(	double &	f,
		independent_variables &	x,
		int	nvar
	)

Referenced by minimize().

void function_minimizer::pvm_master_function_evaluation_profile	(	double &	f,
		independent_variables &	x,
		const dvector &	g,
		int	nvar,
		int	iprof,
		double	weight,
		double	new_value
	)

double function_minimizer::pvm_master_get_monte_carlo_value	(	int	nvar,
		const dvector &	x
	)

Definition at line 36 of file mod_mc2.cpp.

Referenced by monte_carlo_routine().

void function_minimizer::pvm_master_mcmc_computations

(

void

)

Definition at line 598 of file modspmin.cpp.

Referenced by computations1().

void function_minimizer::pvm_master_mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

Referenced by pvm_master_mcmc_computations().

void function_minimizer::pvm_master_prof_minimize	(	int	iprof,
		double	sigma,
		double	new_value,
		const double &	_fprof,
		const int	underflow_flag,
		double	global_min,
		const double &	_penalties,
		const double &	_final_weight
	)

Referenced by likeprof_routine().

void function_minimizer::pvm_slave_function_evaluation

(

void

)

void function_minimizer::pvm_slave_function_evaluation_no_derivatives

(

void

)

Referenced by minimize().

void function_minimizer::pvm_slave_function_evaluation_noder

(

void

)

void function_minimizer::pvm_slave_get_monte_carlo_value

(

int

nvar

)

Definition at line 59 of file mod_mc2.cpp.

Referenced by monte_carlo_routine().

void function_minimizer::pvm_slave_likeprof_routine

(

void

)

Definition at line 50 of file mod_pmin.cpp.

Referenced by computations1().

void function_minimizer::pvm_slave_mcmc_computations

(

void

)

Definition at line 661 of file modspmin.cpp.

void function_minimizer::pvm_slave_mcmc_routine

(

void

)

Referenced by computations1(), and pvm_slave_mcmc_computations().

void function_minimizer::pvm_slave_prof_minimize

(

int

underflow_flag

)

Referenced by pvm_slave_likeprof_routine().

void function_minimizer::quasi_newton_block	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	_g,
		const double &	_f
	)

Description not yet available.

Parameters

Definition at line 23 of file df1b2qnm.cpp.

Referenced by minimize().

void function_minimizer::quasi_newton_block_pvm_master	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	g,
		const double &	f
	)

Referenced by minimize().

void function_minimizer::quasi_newton_block_pvm_master_random_effects	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	g,
		const double &	f
	)

Referenced by minimize().

void function_minimizer::quasi_newton_minimizer1	(	int	nvar,
		double	_crit,
		double &	f,
		const independent_variables &	x,
		const dvector &	g
	)

dvariable function_minimizer::random_effects_maximization

(

const dvar_vector &

v

)

Definition at line 33 of file randeff.cpp.

void function_minimizer::read_mle_hmc	(	int	nvar,
		dvector &	mle
	)

Definition at line 432 of file hmc_functions.cpp.

Referenced by hess_step(), nuts_mcmc_routine(), and rwm_mcmc_routine().

virtual void function_minimizer::report ( const dvector &  gradients )

inlineprotectedvirtual

Definition at line 1915 of file admodel.h.

Referenced by minimize().

void function_minimizer::report_function_minimizer_stats ( void  )

inlineprotected

Definition at line 1914 of file admodel.h.

Referenced by minimize().

dvector function_minimizer::rotate_gradient	(	const dvector &	x,
		const dmatrix &	m
	)

Definition at line 547 of file hmc_functions.cpp.

Referenced by find_reasonable_stepsize(), leapfrog(), and nuts_mcmc_routine().

dvector function_minimizer::rotate_pars	(	const dvector &	m,
		const dvector &	x
	)

Referenced by find_reasonable_stepsize(), leapfrog(), and nuts_mcmc_routine().

dvector function_minimizer::rotate_pars	(	const dmatrix &	m,
		const dvector &	x
	)

Definition at line 498 of file hmc_functions.cpp.

void function_minimizer::rwm_mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

Definition at line 92 of file rwm.cpp.

Referenced by mcmc_computations().

void function_minimizer::sd_routine

(

void

)

Definition at line 101 of file mod_sd.cpp.

Referenced by computations1().

void function_minimizer::set_initial_simplex	(	const dmatrix &	p,
		const dvector &	y,
		int	nvar,
		const dvector &	x,
		double	delta
	)

Definition at line 656 of file xmodelm3.cpp.

Referenced by minimize().

void function_minimizer::set_multinomial_weights

(

dvector &

d

)

Definition at line 548 of file xmodelm3.cpp.

void function_minimizer::set_runtime ( void  )

virtual

Definition at line 451 of file modspmin.cpp.

Referenced by computations1().

void function_minimizer::set_runtime_crit ( const char *  s )

virtual

Definition at line 463 of file modspmin.cpp.

Referenced by computations1().

void function_minimizer::set_runtime_maxfn ( const char *  s )

virtual

Definition at line 453 of file modspmin.cpp.

Referenced by computations1().

void function_minimizer::setup_quadprior_calcs ( void  )

inline

Definition at line 1878 of file admodel.h.

void function_minimizer::sgibbs_mcmc_routine	(	int	,
		int	,
		double	,
		int
	)

void function_minimizer::shmc_mcmc_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

Definition at line 19 of file hmc.cpp.

Referenced by mcmc_computations().

bool function_minimizer::slow_phase	(	int	is,
		int	warmup,
		int	w1,
		int	w3
	)

Definition at line 53 of file hmc_functions.cpp.

Referenced by nuts_mcmc_routine().

void function_minimizer::sob_routine	(	int	nmcmc,
		double	dscale,
		int	restart_flag
	)

void function_minimizer::sobol_importance_routine	(	int	nmcmc,
		int	iseed0,
		double	dscale,
		int	restart_flag
	)

void function_minimizer::start_get_importance_sampling_comnponent

(

void

)

Definition at line 777 of file xmodelm3.cpp.

Referenced by begin_funnel_stuff().

bool function_minimizer::stop_criterion	(	int	nvar,
		dvector &	thetaminus,
		dvector &	thetaplus,
		dvector &	rminus,
		dvector &	rplus
	)

Definition at line 214 of file hmc_functions.cpp.

Referenced by build_tree(), and nuts_mcmc_routine().

void function_minimizer::top_mcmc_routine	(	int	,
		int	,
		double	,
		int
	)

dvariable function_minimizer::trapzd	(	void *	,
		double	a,
		double	b,
		int	n
	)

Referenced by adromb().

dvariable function_minimizer::trapzd	(	_func	func,
		double	a,
		double	b,
		int	n
	)

Extended trapezoid rule.

This algorithm was adapted from function trapzd in "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 4.2

Definition at line 156 of file dfqromb.cpp.

dvariable function_minimizer::trapzd	(	_func	func,
		double	a,
		const dvariable &	b,
		int	n
	)

Extended trapezoid rule.

This algorithm was adapted from function trapzd in "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 4.2

Definition at line 211 of file dfqromb.cpp.

dvariable function_minimizer::trapzd	(	_func	func,
		const dvariable &	a,
		double	b,
		int	n
	)

Extended trapezoid rule.

This algorithm was adapted from function trapzd in "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 4.2

Definition at line 184 of file dfqromb.cpp.

dvariable function_minimizer::trapzd	(	_func	func,
		const dvariable &	a,
		const dvariable &	b,
		int	n
	)

Extended trapezoid rule.

This algorithm was adapted from function trapzd in "Numerical Recipes in C", 2nd edition, Press, Teukolsky, Vetterling, Flannery, chapter 4.2

Definition at line 240 of file dfqromb.cpp.

void function_minimizer::trust_region_update	(	int	nvar,
		int	_crit,
		independent_variables &	x,
		const dvector &	_g,
		const double &	_f
	)

Description not yet available.

Parameters

Definition at line 20 of file f1b2trst.cpp.

Referenced by minimize().

double function_minimizer::unrestricted_hess_determinant

(

void

)

Definition at line 10 of file newmodm4.cpp.

Referenced by likeprof_routine().

dvar_matrix function_minimizer::user_d2frandeff ( const dvar_vector &  x )

virtual

Definition at line 26 of file model37.cpp.

Referenced by random_effects_maximization().

dvar_vector function_minimizer::user_dfrandeff ( const dvar_vector &  x )

virtual

Definition at line 18 of file model37.cpp.

Referenced by random_effects_maximization().

void function_minimizer::user_function ( )

virtual

Definition at line 43 of file xmodelm4.cpp.

Referenced by laplace_approximation_calculator::banded_calculations(), laplace_approximation_calculator::block_diagonal_calculations(), laplace_approximation_calculator::default_calculations(), laplace_approximation_calculator::default_calculations_check_derivatives(), laplace_approximation_calculator::get_complete_hessian(), get_newton_raphson_info(), laplace_approximation_calculator::get_newton_raphson_info(), laplace_approximation_calculator::get_newton_raphson_info_banded(), get_second_ders(), and pre_user_function().

dvariable function_minimizer::user_randeff ( const dvar_vector &  x )

virtual

Definition at line 9 of file model37.cpp.

Referenced by random_effects_maximization().

virtual void function_minimizer::userfunction ( void  )

pure virtual

Referenced by adamoeba(), amxxx(), dep_hess_routine(), do_evaluation(), get_hybrid_monte_carlo_value(), get_monte_carlo_value(), get_particular_grad(), hess_step(), limited_memory_quasi_newton(), minimize(), neldmead(), nuts_mcmc_routine(), pre_userfunction(), prof_minimize(), prof_minimize_re(), pvm_master_get_monte_carlo_value(), pvm_slave_get_monte_carlo_value(), and set_initial_simplex().

Friends And Related Function Documentation

friend class equality_constraint_vector

friend

Definition at line 2166 of file admodel.h.

friend class inequality_constraint_vector

friend

Definition at line 2167 of file admodel.h.

Member Data Documentation

dmatrix function_minimizer::_hessian

private

Definition at line 2198 of file admodel.h.

Referenced by get_hessian(), get_ln_det_value(), and hess_inv().

dmatrix function_minimizer::_hessian_inverse

private

Definition at line 2199 of file admodel.h.

Referenced by get_hessian_inverse(), and hess_inv().

double function_minimizer::_ln_det_value

private

Definition at line 2197 of file admodel.h.

Referenced by get_ln_det_value(), and sd_routine().

int function_minimizer::bad_step_flag =0

static

Definition at line 1853 of file admodel.h.

Referenced by laplace_approximation_calculator::banded_calculations(), laplace_approximation_calculator::do_newton_raphson_banded(), and quasi_newton_block().

int function_minimizer::constraint_exit_number

static

Definition at line 2031 of file admodel.h.

dvector function_minimizer::convergence_criteria

staticprotected

Definition at line 1915 of file admodel.h.

Referenced by limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), quasi_newton_block(), random_effects_maximization(), set_runtime_crit(), and ~function_minimizer().

double function_minimizer::crit

Definition at line 1891 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), quasi_newton_block(), and random_effects_maximization().

double function_minimizer::dfn

Definition at line 1893 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

int function_minimizer::diagonal_metric_flag

Definition at line 1887 of file admodel.h.

Referenced by calculate_chd_and_inverse(), nuts_mcmc_routine(), rotate_gradient(), rotate_pars(), and shmc_mcmc_routine().

double function_minimizer::ffbest

protected

Definition at line 1908 of file admodel.h.

Referenced by computations1(), limited_memory_quasi_newton_block(), and quasi_newton_block().

int function_minimizer::first_hessian_flag =0

static

Definition at line 1855 of file admodel.h.

Referenced by laplace_approximation_calculator::block_diagonal_calculations(), laplace_approximation_calculator::default_calculations(), laplace_approximation_calculator::default_calculations_check_derivatives(), and hess_routine_noparallel_random_effects().

int function_minimizer::have_constraints =0

staticprotected

Definition at line 1921 of file admodel.h.

Referenced by computations1().

long function_minimizer::iexit

Definition at line 1894 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

long function_minimizer::ifn

Definition at line 1888 of file admodel.h.

Referenced by limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), quasi_newton_block(), and random_effects_maximization().

long function_minimizer::ihang

Definition at line 1896 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

long function_minimizer::ihflag

Definition at line 1895 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

int function_minimizer::imax

Definition at line 1892 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

int function_minimizer::inner_opt_flag =0

static

Definition at line 1860 of file admodel.h.

Referenced by laplace_approximation_calculator::get_fx_fu(), laplace_approximation_calculator::get_uhat_lm_newton2(), laplace_approximation_calculator::get_uhat_quasi_newton(), and inner_opt().

int function_minimizer::iprint

Definition at line 1890 of file admodel.h.

Referenced by function_minimizer(), laplace_approximation_calculator::get_uhat_lm_newton(), likeprof_routine(), limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), quasi_newton_block(), and random_effects_maximization().

laplace_approximation_calculator* function_minimizer::lapprox

Definition at line 1862 of file admodel.h.

Referenced by laplace_approximation_calculator::banded_calculations_trust_region_approach(), begin_funnel_stuff(), begin_gauss_hermite_stuff(), laplace_approximation_calculator::block_diagonal_calculations(), calculate_importance_sample(), calculate_importance_sample_block_diagonal(), calculate_importance_sample_block_diagonal_funnel(), calculate_importance_sample_block_diagonal_option2(), calculate_importance_sample_block_diagonal_option_antithetical(), calculate_importance_sample_funnel(), calculate_importance_sample_shess(), calculate_laplace_approximation(), laplace_approximation_calculator::check_hessian_type(), laplace_approximation_calculator::check_hessian_type2(), computations1(), depvars_routine(), do_gauss_hermite_block_diagonal(), do_gauss_hermite_block_diagonal_multi(), do_gauss_hermite_integration(), do_gauss_hermite_integration_multi(), end_df1b2_funnel_stuff(), end_gauss_hermite_stuff(), end_get_importance_sampling_comnponent(), evaluate_function_with_quadprior(), function_minimizer(), get_bigS(), get_function_difference(), get_hybrid_monte_carlo_value(), get_monte_carlo_value(), get_particular_grad(), hess_routine(), hess_routine_noparallel_random_effects(), hess_routine_slave_random_effects(), limited_memory_quasi_newton_block(), minimize(), other_separable_stuff_begin(), pre_user_function(), pre_userfunction(), prof_minimize_re(), quasi_newton_block(), start_get_importance_sampling_comnponent(), trust_region_update(), and ~function_minimizer().

int function_minimizer::likeprof_flag

static

Definition at line 1854 of file admodel.h.

int function_minimizer::maxfn

Definition at line 1889 of file admodel.h.

Referenced by function_minimizer(), hess_step(), limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), minimize(), prof_minimize(), prof_minimize_re(), quasi_newton_block(), and random_effects_maximization().

int function_minimizer::maxfn_flag

Definition at line 1898 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

dvector function_minimizer::maximum_function_evaluations

staticprotected

Definition at line 1917 of file admodel.h.

Referenced by limited_memory_quasi_newton(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), quasi_newton_block(), random_effects_maximization(), set_runtime_maxfn(), and ~function_minimizer().

int function_minimizer::mcmc2_flag

Definition at line 1885 of file admodel.h.

Referenced by computations1(), get_hybrid_monte_carlo_value(), get_monte_carlo_value(), hybrid_mcmc_routine(), mcmc_routine(), nuts_mcmc_routine(), rwm_mcmc_routine(), and shmc_mcmc_routine().

double function_minimizer::min_improve

Definition at line 1900 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

dvector* function_minimizer::multinomial_weights

Definition at line 1863 of file admodel.h.

Referenced by function_minimizer(), set_multinomial_weights(), and ~function_minimizer().

int function_minimizer::negative_eigenvalue_flag =0

static

Definition at line 1859 of file admodel.h.

Referenced by hess_inv(), and minimize().

dmatrix* function_minimizer::negdirections

Definition at line 1858 of file admodel.h.

Referenced by function_minimizer(), hess_inv(), limited_memory_quasi_newton_block(), prof_minimize_re(), quasi_newton_block(), and ~function_minimizer().

int function_minimizer::output_flag = defaults::output

static

Definition at line 1972 of file admodel.h.

Referenced by computations(), depvars_routine(), fmm::fmin(), get_output_stream(), hess_inv(), hess_routine_noparallel(), hess_routine_noparallel_random_effects(), hess_step(), minimize(), and sd_routine().

adstring_array function_minimizer::param_labels

private

Definition at line 1911 of file admodel.h.

Referenced by sd_routine().

ivector function_minimizer::param_size

private

Definition at line 1912 of file admodel.h.

Referenced by sd_routine().

named_dvar_vector* function_minimizer::pg

static

Definition at line 1906 of file admodel.h.

gradient_structure* function_minimizer::pgs

private

Definition at line 1910 of file admodel.h.

Referenced by function_minimizer(), and ~function_minimizer().

named_dvar_vector* function_minimizer::ph

static

Definition at line 1905 of file admodel.h.

int function_minimizer::quit_flag

Definition at line 1899 of file admodel.h.

Referenced by computations1(), function_minimizer(), limited_memory_quasi_newton_block(), minimize(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

int function_minimizer::random_effects_flag =0

static

Definition at line 1857 of file admodel.h.

Referenced by fmm::fmin(), hess_routine(), likeprof_routine(), limited_memory_quasi_newton_block(), mcmc_routine(), minimize(), quasi_newton_block(), rwm_mcmc_routine(), and trust_region_update().

int function_minimizer::repeatminflag

Definition at line 1884 of file admodel.h.

Referenced by computations1(), function_minimizer(), and minimize().

int function_minimizer::robust_hybrid_flag

Definition at line 1886 of file admodel.h.

Referenced by hybrid_mcmc_routine().

int function_minimizer::scroll_flag

Definition at line 1897 of file admodel.h.

Referenced by function_minimizer(), limited_memory_quasi_newton_block(), prof_minimize(), prof_minimize_re(), and quasi_newton_block().

int function_minimizer::sd_flag

staticprotected

Definition at line 1918 of file admodel.h.

int function_minimizer::spminflag

Definition at line 1883 of file admodel.h.

Referenced by computations1(), function_minimizer(), hess_inv(), and minimize().

int function_minimizer::test_trust_flag =0

static

Definition at line 1856 of file admodel.h.

Referenced by computations1(), and laplace_approximation_calculator::operator()().

adstring function_minimizer::user_data_file

staticprotected

Definition at line 1919 of file admodel.h.

adstring function_minimizer::user_par_file

staticprotected

Definition at line 1920 of file admodel.h.

---

The documentation for this class was generated from the following files:

• admodel.h (Last Changed on May 13, 2022 for git-revision 4aafc7ceeb108263fdf90577fb213d3829bc3084.)
• adglobl.cpp (Last Changed on August 03, 2022 for git-revision f8640678bd7af83c55e23f39d73768d9c698f51a.)
• amoeba.cpp (Last Changed on April 05, 2018 for git-revision 113ade054696f6bbf3085c103c16348f3c8a9e78.)
• dep_hess.cpp (Last Changed on July 07, 2022 for git-revision f6721274be90e25ac0685c62af2c1cba28791ea5.)
• dfqromb.cpp (Last Changed on January 24, 2022 for git-revision 74757431d83636e29cb5726a0bcd75902dacd0d9.)
• getbigs.cpp (Last Changed on April 04, 2020 for git-revision 30ac290f82b9a604a2f2a4022e2b20bf6a012fcd.)
• hmc.cpp (Last Changed on June 29, 2022 for git-revision be1526a357a87937cf302cae3cdbcf78712362c7.)
• hmc_functions.cpp (Last Changed on January 19, 2022 for git-revision ff878dbfa8fee2a88cec20cc5c8e10c8f3d35627.)
• hybmcmc.cpp (Last Changed on April 04, 2020 for git-revision 30ac290f82b9a604a2f2a4022e2b20bf6a012fcd.)
• lmnewton.cpp (Last Changed on February 17, 2022 for git-revision e9b921f3a6f970f4a53398d141831583cf8746df.)
• mceval.cpp (Last Changed on April 04, 2020 for git-revision 30ac290f82b9a604a2f2a4022e2b20bf6a012fcd.)
• mod_hess.cpp (Last Changed on August 06, 2022 for git-revision 808780089317c67198079de06b64df009a4a6543.)
• mod_mc.cpp (Last Changed on January 24, 2022 for git-revision 74757431d83636e29cb5726a0bcd75902dacd0d9.)
• mod_mc2.cpp (Last Changed on April 05, 2018 for git-revision 76b0a7eecd306e4d86ef00a07536f9dd1ed1bf4d.)
• mod_mc4.cpp (Last Changed on April 04, 2020 for git-revision 30ac290f82b9a604a2f2a4022e2b20bf6a012fcd.)
• mod_pmin.cpp (Last Changed on March 01, 2022 for git-revision 581d46c0ba066e1ee2548048bc1683888f18b76d.)
• mod_sd.cpp (Last Changed on August 02, 2022 for git-revision a381f2677c52c9ad6665c46ad3274808fdd78006.)
• model.cpp (Last Changed on June 29, 2022 for git-revision be1526a357a87937cf302cae3cdbcf78712362c7.)
• model37.cpp (Last Changed on April 22, 2014 for git-revision 219a09ff06fd9cee4c006dd85abbefca00beea03.)
• model7.cpp (Last Changed on May 09, 2022 for git-revision 5513524e7e10a5a41f689a73f266698e82684a49.)
• modhdet.cpp (Last Changed on October 31, 2014 for git-revision be2eaa920c37aa24993755082e3b70ac50761b46.)
• modspmin.cpp (Last Changed on July 07, 2022 for git-revision f6721274be90e25ac0685c62af2c1cba28791ea5.)
• newmodm2.cpp (Last Changed on June 29, 2022 for git-revision 90ff3225c384e19fdeaf789b3d0cd5d2ced40eb0.)
• newmodm4.cpp (Last Changed on April 06, 2020 for git-revision 372226c80b997196493ae7570cc76be8fe43268c.)
• newmodm5.cpp (Last Changed on April 06, 2020 for git-revision 372226c80b997196493ae7570cc76be8fe43268c.)
• newmodmn.cpp (Last Changed on November 07, 2014 for git-revision e5e02137d6a646033717d56b1947a188ce8b8b5a.)
• nnewmod2.cpp (Last Changed on October 31, 2014 for git-revision be2eaa920c37aa24993755082e3b70ac50761b46.)
• nuts.cpp (Last Changed on June 28, 2022 for git-revision b75f20beaa52fbb8e39f2e547aa45593b40c8951.)
• output_checks.cpp (Last Changed on June 29, 2022 for git-revision be1526a357a87937cf302cae3cdbcf78712362c7.)
• randeff.cpp (Last Changed on March 01, 2022 for git-revision 581d46c0ba066e1ee2548048bc1683888f18b76d.)
• rwm.cpp (Last Changed on June 28, 2022 for git-revision b75f20beaa52fbb8e39f2e547aa45593b40c8951.)
• xmodelm3.cpp (Last Changed on August 04, 2022 for git-revision 9cd228d57ddaaa05092ccd86a12934d02a275b0a.)
• xmodelm4.cpp (Last Changed on April 26, 2014 for git-revision 6bada5f61f8fc694fa1269191c5bf39de32070f9.)
• xmodelm5.cpp (Last Changed on April 26, 2014 for git-revision 6bada5f61f8fc694fa1269191c5bf39de32070f9.)
• xxmcmc.cpp (Last Changed on July 17, 2022 for git-revision 95a666f32bc604f959e3d263c19e518d2292eeaf.)
• df1b2lmn2.cpp (Last Changed on February 23, 2022 for git-revision 03a707fac9e6a921b7ed27fe45f58a62bf94c90f.)
• df1b2lp8.cpp (Last Changed on March 01, 2022 for git-revision 581d46c0ba066e1ee2548048bc1683888f18b76d.)
• df1b2qnm.cpp (Last Changed on February 23, 2022 for git-revision 03a707fac9e6a921b7ed27fe45f58a62bf94c90f.)
• f1b2trst.cpp (Last Changed on November 24, 2014 for git-revision e89781374c17d436cb28f4bbfb4ed2a86f8b8202.)
• mod_rhes.cpp (Last Changed on March 07, 2022 for git-revision 572dcb45e56ad50c708cff6ccbd1978cb520520b.)