# 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 dependency graph for libBM.h:

This graph shows which files directly or indirectly include this file:

Go to the source code of this file.

## Classes
class | str
| Structure of RV (used internally). 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 | mepdf
| Unconditional mpdf, allows using epdf in the role of mpdf. More...
class | compositepdf
| Abstract composition of pdfs, a base for specific classes. 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.

## 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 -----------------------------------