Parameter Handlers

Functions for parameter management. More...

Collaboration diagram for Parameter Handlers:

Functions
vector	get_param (int id, array[] int params_fixed_lookup, array[] int params_variable_lookup, vector params_value, matrix params)
real	get_param (int id, array[] int params_fixed_lookup, array[] int params_variable_lookup, vector params_value, vector params)
void	params_lp (vector params, array[] int prior_dist, vector prior_dist_params, vector params_lower, vector params_upper)

Description

Functions for parameter management.

Functions from params.stan for accessing, manipulating, and applying priors to model parameters.

Function Documentation

get_param() [1/2]

vector get_param	(	int	id,
		array[]int	params_fixed_lookup,
		array[]int	params_variable_lookup,
		vector	params_value,
		matrix	params )

#include </github/workspace/inst/stan/functions/params.stan>

Get a parameter value from either fixed or variable parameters (matrix version)

This function is an overloaded version of get_param that works with a matrix of parameter values, returning a vector of parameter values for multiple samples.

Parameters

id	Parameter ID
params_fixed_lookup	Array of fixed parameter lookup indices
params_variable_lookup	Array of variable parameter lookup indices
params_value	Vector of fixed parameter values
params	Matrix of variable parameter values (rows are samples)

Returns

A vector of parameter values across samples

Definition at line 52 of file params.stan.

                                                     {
  int n_samples = rows(params);
  if (id == 0) {
    return rep_vector(0, n_samples) ; // parameter not used
  } else if (params_fixed_lookup[id]) {
    return rep_vector(params_value[params_fixed_lookup[id]], n_samples);
  } else {
    return params[, params_variable_lookup[id]];
  }
}

get_param() [2/2]

real get_param	(	int	id,
		array[]int	params_fixed_lookup,
		array[]int	params_variable_lookup,
		vector	params_value,
		vector	params )

#include </github/workspace/inst/stan/functions/params.stan>

Parameter Handlers

This group of functions handles parameter access, retrieval, and prior specification in the model. Parameters can be either fixed (specified in advance) or variable (estimated during inference). Get a parameter value from either fixed or variable parameters

This function retrieves a parameter value based on its ID, checking first if it's a fixed parameter and then if it's a variable parameter.

Parameters

id	Parameter ID
params_fixed_lookup	Array of fixed parameter lookup indices
params_variable_lookup	Array of variable parameter lookup indices
params_value	Vector of fixed parameter values
params	Vector of variable parameter values

Returns

The parameter value (scalar)

Definition at line 24 of file params.stan.

                                                   {
  if (id == 0) {
    return 0; // parameter not used
  } else if (params_fixed_lookup[id]) {
    return params_value[params_fixed_lookup[id]];
  } else {
    return params[params_variable_lookup[id]];
  }
}

params_lp()

void params_lp	(	vector	params,
		array[]int	prior_dist,
		vector	prior_dist_params,
		vector	params_lower,
		vector	params_upper )

#include </github/workspace/inst/stan/functions/params.stan>

Update log density for parameter priors

This function adds the log density contributions from parameter priors to the target, supporting multiple prior distribution types.

Parameters

params	Vector of parameter values
prior_dist	Array of prior distribution types (0: lognormal, 1: gamma, 2: normal)
prior_dist_params	Vector of prior distribution parameters
params_lower	Vector of lower bounds for parameters
params_upper	Vector of upper bounds for parameters

Definition at line 80 of file params.stan.

                                   {
  int params_id = 1;
  int num_params = num_elements(params);
  for (id in 1:num_params) {
    if (prior_dist[id] == 0) { // lognormal
      params[id] ~
        lognormal(
          prior_dist_params[params_id], prior_dist_params[params_id + 1]
        )
        T[params_lower[id], params_upper[id]];
      params_id += 2;
    } else if (prior_dist[id] == 1) {
      params[id] ~
        gamma(prior_dist_params[params_id], prior_dist_params[params_id + 1])
        T[params_lower[id], params_upper[id]];
      params_id += 2;
    } else if (prior_dist[id] == 2) {
      params[id] ~
        normal(prior_dist_params[params_id], prior_dist_params[params_id + 1])
        T[params_lower[id], params_upper[id]];
      params_id += 2;
    } else {
      reject("dist must be <= 2");
    }
  }
}