library(epigrowthfit)
options(warn = 2L, error = if (interactive()) recover)
## excess ##############################################################
r <- log(2) / 20
tinfl <- 100
K <- 25000
b <- 10
disp <- 50
zz <- simulate(egf_model(curve = "logistic", family = "nbinom",
excess = TRUE),
nsim = 1L,
seed = 366465L,
mu = log(c(r, tinfl, K, b, disp)),
cstart = 10)
mm <- egf(zz, formula_priors = list(log(b) ~ Normal(mu = 2.5, sigma = 1)))
stopifnot(all.equal(coef(zz), coef(mm), tolerance = 5e-02))
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