tests/testthat/test-weight.R

In glmmTMB: Generalized Linear Mixed Models using Template Model Builder

stopifnot(require("testthat"),
          require("glmmTMB"),
          require("MASS"))

set.seed(1)
nrep <- 20
nsim <- 5
sdi <- .1
sdii <- .2
rho <- -.1
slope <- .8
ni<-100

dat <- expand.grid(i=1:ni, rep=1:nrep , x=c(0 ,.2, .4))
RE <- MASS::mvrnorm(n = ni, mu =c(0, 0),
		Sigma = matrix(c(sdi*sdi, rho*sdi*sdii, rho*sdi*sdii ,sdii*sdii),2,2))
inddat <- transform(dat, y=rpois(n=nrow(dat),
                                lambda = exp(RE[i,1] + x*(slope + RE[i,2]))))

## aggdat = ddply(inddat, ~i+x+y, summarize, freq=length(rep))

aggdat <- with(inddat,as.data.frame(table(i,x,y),
                                   stringsAsFactors=FALSE))
aggdat <- aggdat[with(aggdat,order(i,x,y)),] ## cosmetic/match previous
aggdat <- subset(aggdat,Freq>0)              ## drop zero categories
aggdat <- transform(aggdat,
                   i=as.integer(i),
                   x=as.numeric(x),
                   y=as.numeric(y))
## only difference from previous is name of weights arg (Freq vs freq)

test_that("Weights can be an argument", {
    wei_glmmtmb <<- glmmTMB(y ~ x+(x|i), data=aggdat, weight=Freq,
                            family="poisson")
        expect_equal(unname(fixef(wei_glmmtmb)$cond),
                            c(-0.00907013282660578, 0.944062427131668),
                     tolerance=1e-6)
})


test_that("Return weights", {
  expect_equal(weights(wei_glmmtmb), aggdat$Freq)
  expect_equal(weights(wei_glmmtmb, type="prior"), aggdat$Freq)
  ## partial matching
  expect_equal(weights(wei_glmmtmb, type="prior"), aggdat$Freq)
  expect_error(weights(wei_glmmtmb, type = "working"), "should be")
  expect_warning(weights(wei_glmmtmb, junk = "abc"),
                 "unused arguments ignored")
})



ind_glmmtmb <<- glmmTMB(y ~ x+(x|i), data=inddat, family="poisson")

test_that("Estimates are the same", {
	expect_equal(summary(wei_glmmtmb)$coefficients$cond, summary(ind_glmmtmb)$coefficients$cond, tolerance=1e-6)
	expect_equal(ranef(wei_glmmtmb), ranef(ind_glmmtmb), tolerance=1e-5)
	expect_equal(AIC(wei_glmmtmb), AIC(ind_glmmtmb), tolerance=1e-5)
})