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

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

Compute log-likelihoods from UPG.Logit objects

Description

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

Usage

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

Arguments

object	an object of class UPG.Logit.
...	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.Logit to summarize a UPG.Logit object and create tables. plot.UPG.Logit to plot a UPG.Logit object. coef.UPG.Logit to extract coefficients from a UPG.Logit object.

Examples

# estimate a logit model using example data
library(UPG)
data(lfp)
y = lfp[,1]
X = lfp[,-1]
results.logit = UPG(y = y, X = X, model = "logit")

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

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