Nothing
cat(crayon::yellow("\ntest obsInfo:"))
# data("Salamanders", package = "glmmTMB")
# (foo <- fitme(count ~ spp * mined + (1 |site), data=Salamanders, family=negbin(link=log), method=c("ML","obs"), verbose=c(TRACE=F)))
# testthat::expect_equal(logLik(foo), c(p_v=-815.678491998 ))
data(scotlip)
(foo <- fitme(cases ~ I(prop.ag/10)+(1|gridcode),
family=negbin(link=log), data=scotlip, method=c("ML","obs")))
testthat::expect_equal(logLik(foo), c(P_v=-181.60802361 ))
data(wafers)
(foo <- fitme(y ~1+(1|batch),family=Gamma(log), #fixed=list(lambda=c("1"=0.01213306), phi=0.2255785),
data=wafers,method=c("ML","obs"), verbose=c(TRACE=F)))
testthat::expect_equal(logLik(foo), c(P_v=-1224.65219293 ))
{
data("clinics")
(foo <- fitme(cbind(npos,nneg)~1+(1|clinic), method=c("ML","obs"),
family=binomial(cloglog),data=clinics))
testthat::expect_equal(logLik(foo), c(P_v=-40.4244068868))
}
{
data("wafers")
me <- fitme(y ~ 1+(1|batch), family=Gamma(log), data=wafers)
set.seed(123)
y2 <- simulate(me, type="residual")
wafmv <- wafers
wafmv$batch2 <- wafmv$batch
wafmv$y2 <- y2
wafmv$ly <- log(wafmv$y)
wafmv$y3 <- log(y2)
(me1 <- fitme(formula=ly ~ 1+(1|batch), family=Gamma(log), method=c("ML","obs"), data=wafmv))
(me2 <- fitme(formula=y3 ~ 1+(1|batch2), family=Gamma(log), method=c("ML","obs"), data=wafmv))
(zut1 <- fitmv(submodels=list(mod1=list(formula=ly ~ 1+(1|batch), family=Gamma(log)),
mod2=list(formula=y3 ~ 1+(1|batch2), family=Gamma(log))),
method=c("ML","obs"),
data=wafmv))
testthat::expect_true(diff(range(logLik(me1)+logLik(me2),logLik(zut1)))<1e-5)
testthat::expect_true(diff(range( predict(zut1, newdata=zut1$data)-predict(zut1)))<1e-14)
testthat::expect_true(diff(range( get_predVar(zut1, newdata=zut1$data)-get_predVar(zut1)))<1e-14)
update_resp(zut1,newresp = simulate(zut1))
}
if (spaMM.getOption("example_maxtime")>3) {
data("scotlip")
adjfit <- fitmv(submodels=list(mod1=list(formula=cases~I(prop.ag/10) +adjacency(1|gridcode)+offset(log(expec)),family=poisson()),
mod2=list(formula=cases~I(prop.ag/10) +(1|gridcode)+offset(log(expec)),family=poisson(),rand.family=list(Gamma(log)))),
adjMatrix=Nmatrix,data=scotlip)
std_lev <- hatvalues(adjfit, type="std", force=TRUE, which="both")
testthat::test_that("Whether hatvalues() works on mv fit moreover, with obsInfo)",
testthat::expect_true(diff(range(c(std_lev$ranef -adjfit$lev_lam,std_lev$resid -adjfit$lev_phi)))<1e-14) )
}
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