MoTBFs (version 1.2)

BICMoTBF: Computing the BIC Score of an MoTBF Function

Description

Computes the Bayesian information criterion value (BIC) of a mixture of truncated basis function. The BIC score is the log likelihood penalizes by the number of parameters of the function and the number of records of the evaluated data.

Usage

BICMoTBF(Px, X)

Arguments

Px

A function of class "motbf".

X

A "numeric" vector with the data to evaluate.

Value

A "numeric" value containing the BIC score.

See Also

univMoTBF

Examples

# NOT RUN {
## Data
X <- rexp(10000)

## Data test
Xtest <- rexp(1000)
Xtest <- Xtest[Xtest>=min(X) && Xtest<=max(X)]

## Learning
f1 <- univMoTBF(X, POTENTIAL_TYPE = "MOP", nparam = 10); f1
f2 <- univMoTBF(X, POTENTIAL_TYPE = "MTE", maxParam = 11); f2

## BIC values
BICMoTBF(Px = f1, X = Xtest)
BICMoTBF(Px = f2, X = Xtest)


# }