bdm::elognorm Class Reference

#include <libEF.h>

List of all members.

Public Member Functions

vec sample () const
 Returns a sample, $ x $ from density $ f_x()$.
vec mean () const
 return expected value
virtual void dupdate (mat &v)
 TODO decide if it is really needed.
virtual double evallog (const vec &val) const
 Evaluate normalized log-probability.
virtual vec evallog (const mat &Val) const
 Evaluate normalized log-probability for many samples.
virtual void pow (double p)
 Power of the density, used e.g. to flatten the density.
Constructors
void set_parameters (const vec &mu, const ldmat &R)
Constructors
Construction of each epdf should support two types of constructors:
  • empty constructor,
  • copy constructor,
The following constructors should be supported for convenience:
  • constructor followed by calling set_parameters()
  • constructor accepting random variables calling set_rv()
All internal data structures are constructed as empty. Their values (including sizes) will be set by method set_parameters(). This way references can be initialized in constructors.

void set_parameters (int dim0)
Mathematical operations
void dupdate (mat &v, double nu=1.0)
 dupdate in exponential form (not really handy)
mat sample (int N) const
double evallog_nn (const vec &val) const
 Evaluate normalized log-probability.
double lognc () const
 logarithm of the normalizing constant, $\mathcal{I}$
vec variance () const
 return expected variance (not covariance!)
mpdfcondition (const RV &rvn) const
 Return conditional density on the given RV, the remaining rvs will be in conditioning.
enorm< ldmat > * marginal (const RV &rv) const
 Return marginal density on the given RV, the remainig rvs are intergrated out.
Access to attributes
vec & _mu ()
void set_mu (const vec mu0)
ldmat_R ()
const ldmat_R () const
Matematical Operations
virtual mat sample_m (int N) const
 Returns N samples, $ [x_1 , x_2 , \ldots \ $ from density $ f_x(rv)$.
virtual vec evallog_m (const mat &Val) const
 Compute log-probability of multiple values argument val.
virtual void qbounds (vec &lb, vec &ub, double percentage=0.95) const
 Lower and upper bounds of percentage % quantile, returns mean-2*sigma as default.
Connection to other classes
Description of the random quantity via attribute rv is optional. For operations such as sampling rv does not need to be set. However, for marginalization and conditioning rv has to be set. NB:

void set_rv (const RV &rv0)
 Name its rv.
bool isnamed () const
 True if rv is assigned.
const RV_rv () const
 Return name (fails when isnamed is false).
Access to attributes
int dimension () const
 Size of the random variable.

Protected Attributes

vec mu
 mean value
ldmat R
 Covariance matrix in decomposed form.
int dim
 dimension of the random variable
RV rv
 Description of the random variable.


Detailed Description

Log-Normal probability density only allow diagonal covariances!

Density of the form


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

Generated on Thu Apr 23 21:06:46 2009 for mixpp by  doxygen 1.5.8