Reverse mode Automatic Differentiation

Classes
class	double_and_int
	Holds the data for the prevariable class. More...
class	dvariable
	Fundamental data type for reverse mode automatic differentiation. More...
class	prevariable
	Base class for dvariable. More...

Functions
static void	gradient_structure::set_NO_DERIVATIVES (void)
	Disable accumulation of derivative information. More...
static void	gradient_structure::set_YES_DERIVATIVES (void)
	Enable accumulation of derivative information. More...

Detailed Description

Function Documentation

void gradient_structure::set_NO_DERIVATIVES ( void  )

static

Disable accumulation of derivative information.

Used internally by ADMB to avoid computation of derivatives. Also useful for running simulations using variable objects when function minimization is not required.

Definition at line 641 of file gradstrc.cpp.

Referenced by laplace_approximation_calculator::banded_calculations(), laplace_approximation_calculator::banded_calculations_lme(), 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(), laplace_approximation_calculator::default_calculations(), laplace_approximation_calculator::default_calculations_check_derivatives(), function_minimizer::depvars_routine(), do_gauss_hermite_block_diagonal(), do_gauss_hermite_block_diagonal_multi(), laplace_approximation_calculator::do_one_feval(), evaluate_function_no_derivatives(), function_minimizer::get_particular_grad(), laplace_approximation_calculator::get_uhat_lm_newton2(), laplace_approximation_calculator::get_uhat_quasi_newton(), laplace_approximation_calculator::get_uhat_quasi_newton_block_diagonal(), function_minimizer::hess_routine_and_constraint(), function_minimizer::hybrid_mcmc_routine(), function_minimizer::limited_memory_quasi_newton(), function_minimizer::limited_memory_quasi_newton_block(), function_minimizer::mcmc_eval(), function_minimizer::mcmc_routine(), function_minimizer::minimize(), function_minimizer::monte_carlo_routine(), function_minimizer::prof_minimize(), function_minimizer::prof_minimize_re(), function_minimizer::quasi_newton_block(), function_minimizer::rwm_mcmc_routine(), function_minimizer::shmc_mcmc_routine(), and laplace_approximation_calculator::test_trust_region_method().

void gradient_structure::set_YES_DERIVATIVES ( void  )

static

Enable accumulation of derivative information.

Used internally by ADMB to restart computation of derivatives.

Definition at line 650 of file gradstrc.cpp.

Referenced by laplace_approximation_calculator::banded_calculations(), laplace_approximation_calculator::banded_calculations_lme(), 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::default_calculations(), laplace_approximation_calculator::default_calculations_check_derivatives(), function_minimizer::dep_hess_routine(), function_minimizer::depvars_routine(), do_gauss_hermite_block_diagonal(), do_gauss_hermite_block_diagonal_multi(), evaluate_function_no_derivatives(), function_minimizer::get_particular_grad(), laplace_approximation_calculator::get_uhat_lm_newton2(), laplace_approximation_calculator::get_uhat_quasi_newton(), laplace_approximation_calculator::get_uhat_quasi_newton_block_diagonal(), function_minimizer::hess_routine_and_constraint(), function_minimizer::hess_routine_noparallel(), function_minimizer::hess_routine_noparallel_random_effects(), function_minimizer::hess_routine_slave_random_effects(), function_minimizer::hess_step(), function_minimizer::hybrid_mcmc_routine(), function_minimizer::limited_memory_quasi_newton(), function_minimizer::limited_memory_quasi_newton_block(), function_minimizer::nuts_mcmc_routine(), function_minimizer::prof_minimize(), function_minimizer::prof_minimize_re(), function_minimizer::quasi_newton_block(), function_minimizer::random_effects_maximization(), function_minimizer::shmc_mcmc_routine(), and laplace_approximation_calculator::test_trust_region_method().