logLik.UPG.Binomial: Compute log-likelihoods from UPG.Binomial objects

In UPG: Efficient Bayesian Algorithms for Binary and Categorical Data Regression Models

Compute log-likelihoods from UPG.Binomial objects

Description

logLik can be used to compute log-likelihoods from UPG.Binomial objects. The log-likelihood is based on the posterior mean of the coefficients.

Usage

## S3 method for class 'UPG.Binomial'
logLik(object = NULL, ...)

Arguments

object	an object of class UPG.Binomial.
...	other logLik parameters.

Value

Returns a numeric of class logLik with attributes containing the number of estimated parameters and the number of observations.

Author(s)

Gregor Zens

See Also

summary.UPG.Binomial to summarize a UPG.Binomial object and create tables. plot.UPG.Binomial to plot a UPG.Binomial object. coef.UPG.Binomial to extract coefficients from a UPG.Binomial object.

Examples

# estimate a binomial logit model using example data
library(UPG)
data(titanic)
y  = titanic[,1]
Ni = titanic[,2]
X  = titanic[,-c(1,2)]
results.binomial = UPG(y = y, X = X, Ni = Ni, model = "binomial")

# extract log-likelihood
ll.binomial = logLik(results.binomial)

UPG documentation built on Nov. 4, 2023, 5:06 p.m.