weights and lmer2

Hi, all,

Is the weights argument supposed to work with lmer2? I'm trying to
replicate some analysis from nlme::lme but am having difficulty with the
weights argument. Here's some funny data to work with:

set.seed(42)
z <- expand.grid(A = 1:5, B = 1:4, r = 1:2)
n <- nrow(z)
z$w <- rpois(n, 100)
z$y <- rnorm(n, ifelse(z$A%%2, 1, 2) + ifelse(z$A%%2 & z$B%%2, -1, 1))
z[1:2] <- lapply(z[1:2], factor)

## Session 1 with lmer2
library(lme4)
fit <- lmer2(y ~ (1 | A) + (1 | A:B), z)
wfit <- lmer2(y ~ (1 | A) + (1 | A:B), z, weights = w)

## Session 2 with lme
library(nlme)
fit <- lme(y ~ 1, z, ~1 | A/B)
wfit <- lme(y ~ 1, z, ~1 | A/B, weights = ~w)
vfit <- lme(y ~ 1, z, ~1 | A/B, correlation = varFixed(~w))

## Standard deviations from Session 1 (lmer2)
                fit      wfit
A:B      0.9371798 0.9371798
A        0.8673610 0.8673610
Residual 0.7908478 0.7908478

## Standard deviations from Session 2 (lme)
                              fit       wfit       vfit
(Intercept) | B %in% A 0.9371788 0.90186678 0.90186678
(Intercept) | A        0.8673608 0.87420501 0.87420501
Residual               0.7908482 0.07878061 0.07878061

It appears that the weights argument has no effect for lmer2 (or for
lmer, which I also tried).

Thanks,

--sundar