predict.lda breaks when priors are specified

Dear R help,

What am I doing wrong here? when I don't specify the priors it works
just fine but when I specify the priors it breaks.? Does anyone know
why and how I can fix it?
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N=20000
ncontrol=ncases=50
X <- as.matrix(rnorm(N,0,1))
eta <- -5.3 + X * 1.7
p <- exp(eta)/(1+exp(eta))
Y <- rbinom(N,1,p)
controls <- sample(seq_len(N), ncontrol, prob=!Y)
cases <- sample(seq_len(N), ncases, prob=Y)
data<-rbind(

+ data.frame(Y = 0, X = cbind(1,X[controls,])),
+ data.frame(Y = 1, X = cbind(1,X[cases,])))

head(data)

? Y X.1??????? X.2
1 0?? 1? 0.6965323
2 0?? 1 -0.0817520
3 0?? 1? 2.8673412
4 0?? 1 -0.2351386
5 0?? 1? 0.2653452
6 0?? 1 -1.2437612

m <- lda(Y~X,subset=c(controls,cases),priors=c(.95,.05))
predict(m)

Error in model.frame.default(formula = Y ~ X, priors = c(0.95, 0.05),? :
? variable lengths differ (found for '(priors)')

predict(m,prior=c(.95,0.05))

Error in model.frame.default(formula = Y ~ X, priors = c(0.95, 0.05),? :
? variable lengths differ (found for '(priors)')
---
Thanks,
Andrew