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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Classes
class	str
	Structure of RV (used internally), i.e. expanded RVs. More...
class	RV
	Class representing variables, most often random variables. More...
class	fnc
	Class representing function of variable represented by rv. More...
class	epdf
	Probability density function with numerical statistics, e.g. posterior density. More...
class	mpdf
	Conditional probability density, e.g. modeling some dependencies. More...
class	datalink_e2e
class	datalink_m2e
	data link between More...
class	datalink_m2m
class	mepdf
	Unconditional mpdf, allows using epdf in the role of mpdf. More...
class	compositepdf
	Abstract composition of pdfs, a base for specific classes this abstract class is common to epdf and mpdf. More...
class	DS
	Abstract class for discrete-time sources of data. More...
class	BM
	Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. More...
class	BMcond
	Conditional Bayesian Filter. More...
Functions
RV	concat (const RV &rv1, const RV &rv2)
	Concat two random variables.
Variables
RV	RV0
	Default empty RV that can be used as default argument.

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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 -----------------------------------