Hi all, I understand that gls() uses generalized least squares, but I thought that maybe optimum weights from gls might be used as weights in lm (as shown below), but apparently this is not the case. See:
library(nlme) f1 <- gls(Petal.Width ~ Species / Petal.Length, data = iris, weights = varIdent(form = ~ 1 | Species)) aa <- attributes(summary(f1)$modelStruct$varStruct)$weights f2 <- lm(Petal.Width ~ Species / Petal.Length, data = iris, weights = aa) summary(f1)$tTable; summary(f2) So, the two models with the very same weights do differ (in terms of standard errors). Could you please explain why? Are these different types of weights? Many thanks in advance, Stats Wolf ______________________________________________ R-help@r-project.org mailing list 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.
