IC.SVC_mle: Conditional Akaike's and Bayesian Information Criteria

In varycoef: Modeling Spatially Varying Coefficients

Conditional Akaike's and Bayesian Information Criteria

Description

Methods to calculate information criteria for SVC_mle objects. Currently, two are supported: the conditional Akaike's Information Criteria cAIC = -2*log-likelihood + 2*(edof + df) and the Bayesian Information Criteria BIC = -2*log-likelihood + log(n) * npar. Note that the Akaike's Information Criteria is of the corrected form, that is: edof is the effective degrees of freedom which is derived as the trace of the hat matrices and df is the degree of freedoms with respect to mean parameters.

Usage

## S3 method for class 'SVC_mle'
BIC(object, ...)

## S3 method for class 'SVC_mle'
AIC(object, conditional = "BW", ...)

Arguments

object	SVC_mle object
...	further arguments
conditional	string. If conditional = "BW", the conditional AIC is calculated.

Value

numeric, value of information criteria

Author(s)

Jakob Dambon

varycoef documentation built on Sept. 18, 2022, 1:07 a.m.