work/git/mixpp/bdm/stat/libBM.h File Reference

Bayesian Models (bm) that use Bayes rule to learn from observations. More...

#include <itpp/itbase.h>
#include "../itpp_ext.h"

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Namespaces
namespace	bdm
Classes
class	bdm::base
	Root class of BDM objects. More...
class	bdm::str
	Structure of RV (used internally), i.e. expanded RVs. More...
class	bdm::RV
	Class representing variables, most often random variables. More...
class	bdm::fnc
	Class representing function of variable represented by rv. More...
class	bdm::epdf
	Probability density function with numerical statistics, e.g. posterior density. More...
class	bdm::mpdf
	Conditional probability density, e.g. modeling some dependencies. More...
class	bdm::datalink_e2e
class	bdm::datalink_m2e
	data link between More...
class	bdm::datalink_m2m
class	bdm::mepdf
	Unconditional mpdf, allows using epdf in the role of mpdf. More...
class	bdm::compositepdf
	Abstract composition of pdfs, a base for specific classes this abstract class is common to epdf and mpdf. More...
class	bdm::DS
	Abstract class for discrete-time sources of data. More...
class	bdm::BM
	Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. More...
class	bdm::BMcond
	Conditional Bayesian Filter. More...
Functions
RV	bdm::concat (const RV &rv1, const RV &rv2)
	Concat two random variables.

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Detailed Description

Bayesian Models (bm) that use Bayes rule to learn from observations.

Author:

Vaclav Smidl.

----------------------------------- BDM++ - C++ library for Bayesian Decision Making under Uncertainty

Using IT++ for numerical operations -----------------------------------