A multi-dimensional Gaussian conditional probability density function. More...
#include <prob_dens_func.h>
This class is experimental.
Definition at line 1825 of file prob_dens_func.h.
Public Member Functions | |
prob_cond_mdim_gaussian () | |
Create an empty distribution. | |
prob_cond_mdim_gaussian (const prob_cond_mdim_gaussian &pcmg) | |
Copy constructor. | |
prob_cond_mdim_gaussian & | operator= (const prob_cond_mdim_gaussian &pcmg) |
Copy constructor with operator=. | |
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_seed (unsigned long int s) |
Set the seed. | |
void | set (size_t p_ndim, mat_t &covar) |
Set the covariance matrix for the distribution. | |
virtual double | pdf (const vec_t &x_B, const vec_t &x_A) const |
The conditional probability of x_A given x_B, i.e. ![]() | |
virtual double | log_pdf (const vec_t &x_B, const vec_t &x_A) const |
The log of the conditional probability of x_A given x_B i.e. ![]() | |
virtual void | operator() (const vec_t &x_B, vec_t &x_A) const |
Sample the distribution. | |
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virtual double | log_metrop_hast (const vec_t &x, vec_t &x_prime) const |
Sample the distribution and return the log of the Metropolis-Hastings ratio. More... | |
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. | |
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