logLik.GPPM: Log-Likelihood

In gppm: Gaussian Process Panel Modeling

Log-Likelihood

Description

Compute the log-likelihood for a GPPM at the maximum likelihood parameter values.

Usage

## S3 method for class 'GPPM'
logLik(object, ...)

Arguments

object	object of class GPPM. Must be fitted, that is, a result from fit.GPPM.
...	additional arguments (currently not used).

Value

Returns an object of class logLik. Attributes are: "df" (degrees of freedom; number of estimated parameters in the model) and nobs (number of persons in the model)

See Also

Other functions to extract from a GPPM: SE(), coef.GPPM(), confint.GPPM(), covFun(), fitted.GPPM(), getData(), getIntern(), maxNObs(), meanFun(), nObs(), nPars(), nPers(), nPreds(), parEsts(), pars(), preds(), vcov.GPPM()

Examples

data("demoLGCM")
lgcm <- gppm(
  "muI+muS*t", "varI+covIS*(t+t#)+varS*t*t#+(t==t#)*sigma",
  demoLGCM, "ID", "y"
)
lgcmFit <- fit(lgcm)
ll <- logLik(lgcmFit)

gppm documentation built on Aug. 25, 2025, 9:50 a.m.