parEsts: Essential Parameter Estimation Results

In gppm: Gaussian Process Panel Modeling

Essential Parameter Estimation Results

Description

Extracts the essential parameter estimation results for a GPPM.

Usage

parEsts(object, level = 0.95)

Arguments

object	object of class GPPM. Must be fitted, that is, a result from fit.GPPM.
level	scalar from 0 to 1. The confidence level required.

Value

A data.frame containing the estimated parameters, standard errors, and the lower and upper bounds of the confidence intervals.

See Also

Other functions to extract from a GPPM: SE(), coef.GPPM(), confint.GPPM(), covFun(), fitted.GPPM(), getData(), getIntern(), logLik.GPPM(), maxNObs(), meanFun(), nObs(), nPars(), nPers(), nPreds(), 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)
paramEssentials <- parEsts(lgcmFit)

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