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dfun
2009 Sep 06
2
question about ... passed to two different functions
...- as.numeric(runif(n) < p)
out <- glm(y ~ x1 + x2 + x3, family = binomial())
summary(out)
### now we want to do a Bayesian analysis of the model, so we write
### a function that evaluates the log unnormalized density of the
### Markov chain we want to run (log likelihood + log prior)
ludfun <- function(beta) {
stopifnot(is.numeric(beta))
stopifnot(length(beta) == ncol(modmat))
eta <- as.numeric(modmat %*% beta)
logp <- ifelse(eta < 0, eta - log1p(exp(eta)), - log1p(exp(- eta)))
logq <- ifelse(eta < 0, - log1p(exp(eta)), - eta - log1p(exp(- et...