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STK++ 1.0
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The project StatModel proposes classes for modeling Statistical Models. More...
Classes | |
| class | STK::AICCriterion |
| Derived class of Criterion for computing the AIC Criterion The AIC criteria is a penalization of the likelihood given by the formula
where | |
| class | STK::BICCriterion |
| Derived class of Criterion for computing the BIC Criterion The Bic criteria is a penalization of the likelihood given by the formula
where | |
| class | STK::Gaussian2BlocksStatModel |
| Compute the the maximum likelihood estimates of a Gaussian tow blocks statistical model. More... | |
| class | STK::GaussianStatModel |
| Compute the the maximum likelihood estimates of a Gaussian statistical model. More... | |
| class | STK::ICriterion |
| Interface base class for the selection model criterions. More... | |
| class | STK::IStatModelBase |
| Interface base class for all statistical models. More... | |
| class | STK::ITStatModel< TYPE, TContainerHo, TContainerVe, TContainer2D > |
| Interface base class for all statistical models. More... | |
Enumerations | |
| enum | STK::StatModel::TypeCriterion { STK::StatModel::unknown_, STK::StatModel::aic_, STK::StatModel::bic_, STK::StatModel::icl_ } |
Model selection criteria. More... | |
Functions | |
| TypeCriterion | STK::StatModel::StringToTypeCriterion (String const &type) |
| convert a String to a TypeReduction. | |
| String | STK::StatModel::TypeCriterionToString (TypeCriterion const &type) |
| convert a TypeCriterion to a String. | |
The project StatModel proposes classes for modeling Statistical Models.
The aim of this project is to define Interface and specialized classes in order to manipulate and estimate the parameters of any kind of statistical model.
A "statistical model" is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more random variables. The model is statistical as the variables are not deterministically but stochastically related. In mathematical terms, a statistical model is frequently thought of as a pair
where
is the set of possible observations and
the set of possible probability distributions on
. It is assumed that there is a distinct element of
which generates the observed data. Statistical inference enables us to make statements about which element(s) of this set are likely to be the true one.
| TypeCriterion STK::StatModel::StringToTypeCriterion | ( | String const & | type | ) |
convert a String to a TypeReduction.
| type | the String we want to convert |
type. if the string does not match any known name, the unknown_ type is returned. Definition at line 48 of file STK_StatModel_Util.cpp.
References _T, STK::StatModel::aic_, STK::StatModel::bic_, STK::StatModel::icl_, STK::toUpperString(), and STK::StatModel::unknown_.
{
if (toUpperString(type) == toUpperString(_T("AIC")))
return aic_;
if (toUpperString(type) == toUpperString(_T("BIC")))
return bic_;
if (toUpperString(type) == toUpperString(_T("ICL")))
return icl_;
return unknown_;
}
| String STK::StatModel::TypeCriterionToString | ( | TypeCriterion const & | type | ) |
convert a TypeCriterion to a String.
| type | the type of criterion we want to convert |
Definition at line 60 of file STK_StatModel_Util.cpp.
References _T, STK::StatModel::aic_, STK::StatModel::bic_, STK::StatModel::icl_, and STK::StatModel::unknown_.