parEsts: Essential Parameter Estimation Results

In karchjd/gppm: Gaussian Process Panel Modeling

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, covf, datas, fitted.GPPM, getIntern, logLik.GPPM, maxnObs, meanf, 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)

karchjd/gppm documentation built on May 27, 2019, 11:49 p.m.