if (FALSE) { # require("pscl")
# Generate some zero-inflated data
set.seed(123)
N <- 100 # Samples
x <- runif(N, 0, 10) # Predictor
off <- rgamma(N, 3, 2) # Offset variable
yhat <- -1 + x * 0.5 + log(off) # Prediction on log scale
dat <- data.frame(y = NA, x, logOff = log(off))
dat$y <- rpois(N, exp(yhat)) # Poisson process
dat$y <- ifelse(rbinom(N, 1, 0.3), 0, dat$y) # Zero-inflation process
m1 <- zeroinfl(y ~ offset(logOff) + x | 1, data = dat, dist = "poisson")
find_offset(m1)
m2 <- zeroinfl(y ~ x | 1, data = dat, offset = logOff, dist = "poisson")
find_offset(m2)
}
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