density.hpp File Reference

Classes to construct multivariate negative log Gaussian density objects. More...

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Classes
class	density::AR1_t< distribution >
	Stationary AR1 process. More...
class	density::ARk_t< scalartype_ >
	Stationary AR(k) process. More...
class	density::contAR2_t< scalartype_ >
	Continuous AR(2) process. More...
class	density::GMRF_t< scalartype_ >
	Gaussian Markov Random Field. More...
class	density::MVNORM_t< scalartype_ >
	Multivariate normal distribution with user supplied covariance matrix. More...
class	density::N01< scalartype_ >
	Standardized normal distribution. More...
class	density::PROJ_t< distribution >
	Projection of multivariate gaussian variable. More...
class	density::SCALE_t< distribution >
	Apply scale transformation on a density. More...
class	density::SEPARABLE_t< distribution1, distribution2 >
	Separable extension of two densitites. More...
class	density::UNSTRUCTURED_CORR_t< scalartype_ >
	Multivariate normal distribution with unstructered correlation matrix. More...
class	density::VECSCALE_t< distribution >
	Apply a vector scale transformation on a density. More...

Namespaces
	density
	Collection of multivariate Gaussian distributions (members listed in density.hpp)

Macros
#define	SIMULATE_NOT_YET_IMPLEMENTED

Functions
template<class scalartype >
GMRF_t< scalartype >	density::GMRF (Eigen::SparseMatrix< scalartype > Q, int order, bool normalize=true)
	Construct object to evaluate density of Gaussian Markov Random Field (GMRF) for sparse Q. More...
template<class scalartype >
MVNORM_t< scalartype >	density::MVNORM (matrix< scalartype > Sigma, bool use_atomic=true)
	Construct object to evaluate multivariate zero-mean normal density with user supplied covariance matrix. More...
template<class distribution1 , class distribution2 >
SEPARABLE_t< distribution1, distribution2 >	density::SEPARABLE (distribution1 f_, distribution2 g_)
	Construct object to evaluate the separable extension of two multivariate zero-mean normal densities. See SEPARABLE_t for details. More...
template<class scalartype >
UNSTRUCTURED_CORR_t< scalartype >	density::UNSTRUCTURED_CORR (vector< scalartype > x)
	Construct object to evaluate the density with unstructured correlation matrix. See UNSTRUCTURED_CORR_t for details.
template<class vectortype , class distribution >
VECSCALE_t< distribution >	density::VECSCALE (distribution f_, vectortype scale_)
	Construct object to evaluate a scaled density. See VECSCALE_t for details.

Detailed Description

Classes to construct multivariate negative log Gaussian density objects.

Note

These density classes return the negative log likelihood.

Definition in file density.hpp.

Macro Definition Documentation

SIMULATE_NOT_YET_IMPLEMENTED

#define SIMULATE_NOT_YET_IMPLEMENTED

Value:

private:                                        \
vectortype sqrt_cov_scale(vectortype x){}       \
void simulate(vectortype &u){}                  \
vectortype simulate(){}                         \
public:

Conventions for simulation:

Definition at line 54 of file density.hpp.