# rm(list = setdiff(ls(),"connection"))
## implement as.R for FLSimpleVector.
## using 1 Random Effects.
FLenv <- new.env(parent = globalenv())
fltbl <- FLTable(getTestTableName("tblMixedModel"), "ObsID")
colnames(fltbl) <- tolower(colnames(fltbl))
## use in
FLenv$mod <- lmer(yval ~ fixval + (1 | ranval), data = fltbl,categoricalFixedEffect=TRUE)
## AIC, Log-Likehhood
test_that("AIC, LogLik:", {
expect_equal(FLenv$mod$logLik,6970.309,tolerance = .001 )
expect_equal(FLenv$mod$AIC,6974.309,tolerance = .001 )
})
## Covar Random
test_that("Covar Random", {
expect_equal(FLenv$mod$CovRandom,260.573310,tolerance = .001 )
})
## fixedcoef and u
test_that("comparing length of fixed coef and u", {
expect_equal(1 + length(FLenv$mod$fixedcoef),length(unique(as.vector(fltbl[,"fixval"]))))
expect_equal(length(FLenv$mod$u),length(unique(as.vector(fltbl[,"ranval"]))))
})
## for 2 Random Effect:
FLenv <- new.env(parent = globalenv())
fltbl <- FLTable(getTestTableName("tblMixedModelInt"), "ObsID")
colnames(fltbl) <- tolower(colnames(fltbl))
FLenv$mod <- lmer(yval ~ fixval + (1 | ranval1) + (1 | ranval2 ), fltbl,categoricalFixedEffect=TRUE)
## AIC, Log-Likehhood
test_that("AIC, LogLik:", {expect_equal(FLenv$mod$logLik,38.6181,tolerance = .001 )
expect_equal(FLenv$mod$AIC,42.6181,tolerance = .001 ) })
## Covar Random
test_that("Covar Random", {
expect_equal(FLenv$mod$CovRandom,c(0.01482593 ,2.38859471),tolerance = .001 )
})
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