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bnclassify (version 0.4.8)

loglik: Compute (penalized) log-likelihood.

Description

Compute (penalized) log-likelihood and conditional log-likelihood score of a bnc_bn object on a data set. Requires a data frame argument in addition to object.

Usage

# S3 method for bnc_bn
AIC(object, ...)

# S3 method for bnc_bn BIC(object, ...)

# S3 method for bnc_bn logLik(object, ...)

cLogLik(object, ...)

Arguments

object

A bnc_bn object.

...

A data frame (D).

Details

log-likelihood = logP(Dθ),

Akaike's information criterion (AIC) = logP(Dθ)12|θ|,

The Bayesian information criterion (BIC) score: = logP(Dθ)logN2|θ|,

where |θ| is the number of free parameters in object, D is the data set and N is the number of instances in D.

cLogLik computes the conditional log-likelihood of the model.

Examples

Run this code
data(car)
nb <- bnc('nb', 'class', car, smooth = 1)
logLik(nb, car)   
AIC(nb, car)
BIC(nb, car)
cLogLik(nb, car)   

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