Public Member Functions | Protected Attributes | List of all members
o2scl::prob_cond_mdim_gaussian< vec_t, mat_t > Class Template Reference

A multi-dimensional Gaussian conditional probability density function. More...

#include <prob_dens_func.h>

Inheritance diagram for o2scl::prob_cond_mdim_gaussian< vec_t, mat_t >:
o2scl::prob_cond_mdim< vec_t >

Public Member Functions

 prob_cond_mdim_gaussian ()
 Create an empty distribution.
 prob_cond_mdim_gaussian (size_t p_ndim, mat_t &covar)
 Create a distribution from the covariance matrix.
virtual size_t dim () const
 The dimensionality.
void set (size_t p_ndim, mat_t &covar)
 Set the covariance matrix for the distribution.
virtual double pdf (const vec_t &x, const vec_t &x2) const
 The normalized density.
virtual double log_pdf (const vec_t &x, const vec_t &x2) const
 The log of the normalized density.
virtual void operator() (const vec_t &x, vec_t &x2) const
 Sample the distribution.
- Public Member Functions inherited from o2scl::prob_cond_mdim< vec_t >
virtual double metrop_hast (const vec_t &x, vec_t &x2) const
 Sample the distribution and return the log of the Metropolis-Hastings ratio.

Protected Attributes

mat_t chol
 Cholesky decomposition.
mat_t covar_inv
 Inverse of the covariance matrix.
double norm
 Normalization factor.
size_t ndim
 Number of dimensions.
vec_t q
 Temporary storage 1.
vec_t vtmp
 Temporary storage 2.
o2scl::prob_dens_gaussian pdg
 Standard normal.

Detailed Description

template<class vec_t = boost::numeric::ublas::vector<double>, class mat_t = boost::numeric::ublas::matrix<double>>
class o2scl::prob_cond_mdim_gaussian< vec_t, mat_t >

This class is experimental.

Definition at line 1026 of file prob_dens_func.h.

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

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