Hello, All:
I want to simulate future observations from fits to heteroscedastic data. A simple example is as follows:
(DF3_2 <- data.frame(y=c(1:3, 10*(1:3)), gp=factor(rep(1:2, e=3)))) # I want to fit 4 models # and simulate future observations from all 4: fit11 <- lm(y~1, DF3_2) fit21 <- lm(y~gp, DF3_2) library(nlme) (fit12 <- lme(y~1, data=DF3_2, random=~1|gp)) (fit22 <- lme(y~gp, data=DF3_2, random=~1|gp)) library(lme4) (fit12r <- lmer(y~1+(1|gp), data=DF3_2, REML=FALSE)) (fit22r <- lmer(y~gp+(1|gp), data=DF3_2, REML=FALSE)) # I can simulate what I want for fit11 and fit21 # as follows: simPred <- function(object, nSims=2){ pred <- predict(object, DF3_2[6,], se.fit=TRUE, interval='prediction') with(pred, fit[1, 'fit'] + se.fit*rt(nSims, df)) } simPred(fit11) simPred(fit21) # How can I do the same with either fit12 and fit22 # or fit12r and fit22r? Thanks, Spencer Graves ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.