bdm::euni Class Reference

Uniform distributed density on a rectangular support. More...

#include <libEF.h>

List of all members.

Public Member Functions

double eval (const vec &val) const
double evallog (const vec &val) const
 Compute log-probability of argument val.
vec sample () const
 Returns a sample, $ x $ from density $ f_x()$.
vec mean () const
 set values of low and high
vec variance () const
 return expected variance (not covariance!)
Constructors
 euni ()
 euni (const vec &low0, const vec &high0)
void set_parameters (const vec &low0, const vec &high0)
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)
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 mpdfcondition (const RV &rv) const
 Return conditional density on the given RV, the remaining rvs will be in conditioning.
virtual epdfmarginal (const RV &rv) const
 Return marginal density on the given RV, the remainig rvs are intergrated out.
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 low
 lower bound on support
vec high
 upper bound on support
vec distance
 internal
double nk
 normalizing coefficients
double lnk
 cache of log( nk )
int dim
 dimension of the random variable
RV rv
 Description of the random variable.


Detailed Description

Uniform distributed density on a rectangular support.
The documentation for this class was generated from the following file:

Generated on Thu Mar 19 16:25:44 2009 for mixpp by  doxygen 1.5.8