inst/doc/hacking.R

In glmmTMB: Generalized Linear Mixed Models using Template Model Builder

params <-
list(EVAL = FALSE)

## ----glmmTMB, load_lib,echo=FALSE---------------------------------------------
library(glmmTMB)
knitr::opts_chunk$set(eval = if (isTRUE(exists("params"))) params$EVAL else FALSE)

## ----eval = FALSE-------------------------------------------------------------
# #' @rdname nbinom2
# #' @export
# zo_truncated_poisson <- function(link="log") {
#     r <- list(family="zo_truncated_poisson",
#               variance=function(lambda) {
#                   stop("haven't implemented variance function")
#                   ## should figure this out ...
#                   ## (lambda+lambda^2)/(1-exp(-lambda)) - lambda^2/((1-exp(-lambda))^2)
#               })
#     return(make_family(r,link))
# }

## ----eval = FALSE-------------------------------------------------------------
# .noDispersionFamilies <- c("binomial", "poisson", "truncated_poisson",
#                            "zo_truncated_poisson")

## ----testzo, eval = FALSE-----------------------------------------------------
# library(glmmTMB)
# set.seed(101)
# dd <- data.frame(y = rpois(500, exp(1)))
# table(dd$y)
# ##  0   1   2   3   4   5   6   7   8   9
# ## 34  91 117 116  68  45  17   7   3   2
# dd <- dd[dd$y>1,,drop=FALSE]
# table(dd$y)
# ##   2   3   4   5   6   7   8   9
# ## 117 116  68  45  17   7   3   2
# glmmTMB(y ~ 1, family = "zo_truncated_poisson", data = dd)