bdm::BM Class Reference

Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities. More...

#include <bdmbase.h>

Detailed Description

Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.

This object represents exact or approximate evaluation of the Bayes rule:

$f(\theta_t | y_1,\ldots,y_t, u_1,\ldots,u_t) = \frac{f(y_t|\theta_t,\cdot) f(\theta_t|d_1,\ldots,d_{t-1})}{f(y_t|d_1,\ldots,d_{t-1})}$

where: $ y_t $ is the variable Access to the resulting posterior density is via function posterior().

As a "side-effect" it also evaluates log-likelihood of the data, which can be accessed via function _ll(). It can also evaluate predictors of future values of $y_t$ , see functions epredictor() and predictor().

Alternatively, it can evaluate posterior density with rvc replaced by the given values, $ c_t $ :

$f(\theta_t | c_t, d_1,\ldots,d_t) \propto f(y_t,\theta_t|c_t,\cdot, d_1,\ldots,d_{t-1})$

Member Enumeration Documentation

Member Function Documentation

void bdm::BM::from_setting ( const Setting & set ) [inline, virtual]

Create object from the following structure check if not remove... rv...

    class = 'BM';
    --- optional fields ---
    log_level = "...";                                 % identifiers of levels of detail to store to loggers
    yrv = RV({'names',...},[sizes,...],[times,...]);   % names of modelled data
    rvc = RV({'names',...},[sizes,...],[times,...]);   % names of data in condition
    rv = RV({'names',...},[sizes,...],[times,...]);    % names of parameters
    --- inherited fields ---
    bdm::root::from_setting

Reimplemented from bdm::root.

References bdm::UI::get(), rvc, set_rv(), and yrv.

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

bdmbase.h
bdmbase.cpp

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bdm::BM Class Reference

Detailed Description

Member Enumeration Documentation

Member Function Documentation