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o2scl::prob_dens_mdim_gproc< vec_t, mat_t, mat_col_t > Class Template Reference

A multidimensional normal distribution from a Gaussian process. More...

#include <prob_dens_func.h>

Inheritance diagram for o2scl::prob_dens_mdim_gproc< vec_t, mat_t, mat_col_t >:
o2scl::prob_dens_mdim_gaussian< vec_t > o2scl::prob_dens_mdim< vec_t >

Detailed Description

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

Idea for Future:
The linear algebra only works with ublas and is not optimized.

Definition at line 1247 of file prob_dens_func.h.

Additional Inherited Members

- Public Member Functions inherited from o2scl::prob_dens_mdim_gaussian< vec_t >
virtual size_t dim () const
 The dimensionality.
 
 prob_dens_mdim_gaussian ()
 Create an empty distribution.
 
 prob_dens_mdim_gaussian (size_t p_ndim, vec_t &p_peak, boost::numeric::ublas::matrix< double > &covar)
 Create a distribution from the covariance matrix.
 
void set (size_t p_ndim, vec_t &p_peak, boost::numeric::ublas::matrix< double > &covar)
 Set the peak and covariance matrix for the distribution.
 
void set_alt (size_t p_ndim, vec_t &p_peak, boost::numeric::ublas::matrix< double > &p_chol, boost::numeric::ublas::matrix< double > &p_covar_inv, double p_norm)
 Alternate set function for use when covariance matrix has already been decomposed and inverted.
 
void set_gproc (size_t n_dim, size_t n_init, vec_vec_t &x, vec_t &y, func_t &fcovar)
 Given a data set and a covariance function, construct probability distribution based on a Gaussian process which includes noise.
 
virtual double pdf (const vec_t &x) const
 The normalized density.
 
virtual double log_pdf (const vec_t &x) const
 The log of the normalized density.
 
virtual void operator() (vec_t &x) const
 Sample the distribution.
 
- Protected Attributes inherited from o2scl::prob_dens_mdim_gaussian< vec_t >
boost::numeric::ublas::matrix< double > chol
 Cholesky decomposition.
 
boost::numeric::ublas::matrix< double > covar_inv
 Inverse of the covariance matrix.
 
vec_t peak
 Location of the peak.
 
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.
 

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

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