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> require(lme4)
Loading required package: lme4
Loading required package: Matrix
> source(system.file("test-tools-1.R", package = "Matrix"))# identical3() etc
Loading required package: tools
> 
> ## use old (<=3.5.2) sample() algorithm if necessary
> if ("sample.kind" %in% names(formals(RNGkind))) {
+     suppressWarnings(RNGkind("Mersenne-Twister", "Inversion", "Rounding"))
+ }
> 
> ## Check that quasi families throw an error
> assertError(lmer(cbind(incidence, size - incidence) ~ period + (1|herd),
+                  data = cbpp, family = quasibinomial))
> assertError(lmer(incidence ~ period + (1|herd),
+                  data = cbpp, family = quasipoisson))
> assertError(lmer(incidence ~ period + (1|herd),
+                  data = cbpp, family = quasi))
> 
> ## check bug found by Kevin Buhr
> set.seed(7)
> n <- 10
> X <- data.frame(y=runif(n), x=rnorm(n), z=sample(c("A","B"), n, TRUE))
> fm <- lmer(log(y) ~ x | z, data=X)  ## ignore grouping factors with
boundary (singular) fit: see help('isSingular')
> ## gave error inside  model.frame()
> stopifnot(all.equal(c(`(Intercept)` = -0.834544), fixef(fm), tolerance=.01))
> 
> ## is "Nelder_Mead" default optimizer?
> (isNM   <- formals(lmerControl)$optimizer == "Nelder_Mead")
[1] FALSE
> (isOldB <- formals(lmerControl)$optimizer == "bobyqa")
[1] FALSE
> (isOldTol <- environment(nloptwrap)$defaultControl$xtol_abs == 1e-6)
[1] FALSE
> 
> if (.Platform$OS.type != "windows") withAutoprint({
+ 
+     source(system.file("testdata", "lme-tst-funs.R", package="lme4", mustWork=TRUE))# -> uc()
+ 
+     ## check working of Matrix methods on  vcov(.) etc ----------------------
+     fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
+      V  <- vcov(fm)
+     (V1 <- vcov(fm1))
+     (C1 <- chol(V1))
+     dput(dV <- as.numeric(diag(V))) # 0.17607818634.. [x86_64, F Lnx 36]
+     TOL <- 0 # to show the differences below
+     TOL <- 1e-5 # for the check
+     stopifnot(exprs = {
+         all.equal(dV, uc(if(isNM)     0.176076 else if(isOldB) 0.176068575 else
+                          if(isOldTol) 0.1761714 else           0.1760782),
+                   tolerance = 9*TOL) # seen 7.8e-8; Apple clang 14.0.3 had 6.3783e-5
+         all.equal(sqrt(dV), as.numeric(chol(V)), tol = 1e-12)
+         all.equal(diag(V1), uc(`(Intercept)` = 46.5751, Days = 2.38947), tolerance = 40*TOL)# 5e-7 (for "all" algos)
+         is(C1, "dtrMatrix") # was inherits(C1, "Cholesky")
+         dim(C1) == c(2,2)
+         all.equal(as.numeric(C1), # 6.8245967  0. -0.2126263  1.5310962 [x86_64, F Lnx 36]
+                   c(6.82377, 0, -0.212575, 1.53127), tolerance=20*TOL)# 1.2e-4  ("all" algos)
+         dim(chol(crossprod(getME(fm1, "Z")))) == 36
+     })
+     ## printing
+     signif(chol(crossprod(getME(fm, "Z"))), 5) # -> simple 4 x 4 sparse
+ 
+     showProc.time() #
+ 
+     ## From: Stephane Laurent
+     ## To:   r-sig-mixed-models@..
+     ## "crash with the latest update of lme4"
+     ##
+     ## .. example for which lmer() crashes with the last update of lme4 ...{R-forge},
+     ## .. but not with version CRAN version (0.999999-0)
+     lsDat <- data.frame(
+         Operator = as.factor(rep(1:5, c(3,4,8,8,8))),
+         Part = as.factor(
+             c(2L, 3L, 5L,
+               1L, 1L, 2L, 3L,
+               1L, 1L, 2L, 2L, 3L, 3L, 4L, 5L,
+               1L, 2L, 3L, 3L, 4L, 4L, 5L, 5L,
+               1L, 2L, 2L, 3L, 3L, 4L, 5L, 5L)),
+         y =
+             c(0.34, -1.23, -2.46,
+               -0.84, -1.57,-0.31, -0.18,
+               -0.94, -0.81, 0.77, 0.4, -2.37, -2.78, 1.29, -0.95,
+               -1.58, -2.06, -3.11,-3.2, -0.1, -0.49,-2.02, -0.75,
+               1.71,  -0.85, -1.19, 0.13, 1.35, 1.92, 1.04,  1.08))
+ 
+     xtabs( ~ Operator + Part, data=lsDat) # --> 4 empty cells, quite a few with only one obs.:
+     ##         Part
+     ## Operator 1 2 3 4 5
+     ##        1 0 1 1 0 1
+     ##        2 2 1 1 0 0
+     ##        3 2 2 2 1 1
+     ##        4 1 1 2 2 2
+     ##        5 1 2 2 1 2
+     lsD29 <- lsDat[1:29, ]
+ 
+     ## FIXME: rank-Z test should probably not happen in this case:
+     (sm3 <- summary(m3 <- lm(y ~ Part*Operator, data=lsDat)))# ok: some interactions not estimable
+     stopifnot(21 == nrow(coef(sm3)))# 21 *are* estimable
+     sm4  <- summary(m4 <- lm(y ~ Part*Operator, data=lsD29))
+     stopifnot(20 == nrow(coef(sm4)))# 20 *are* estimable
+     lf <- lFormula(y ~ (1|Part) + (1|Operator) + (1|Part:Operator), data = lsDat)
+     dim(Zt <- lf$reTrms$Zt)## 31 x 31
+     c(rankMatrix(Zt)) ## 21
+     c(rankMatrix(Zt,method="qr")) ## 31 ||  29 (64 bit Lnx), then 21 (!)
+     c(rankMatrix(t(Zt),method="qr")) ## 30, then 21 !
+     nrow(lsDat)
+     fm3 <- lmer(y ~ (1|Part) + (1|Operator) + (1|Part:Operator), data = lsDat,
+                 control=lmerControl(check.nobs.vs.rankZ="warningSmall"))
+ 
+     lf29 <- lFormula(y ~ (1|Part) + (1|Operator) + (1|Part:Operator), data = lsD29)
+     (fm4 <- update(fm3, data=lsD29))
+     fm4. <- update(fm4, REML=FALSE,
+                    control=lmerControl(optimizer="nloptwrap",
+                                        optCtrl=list(ftol_abs=1e-6,
+                                                     xtol_abs=1e-6)))
+     ## summary(fm4.)
+     stopifnot(
+         all.equal(as.numeric(formatVC(VarCorr(fm4.), digits = 7)[,"Std.Dev."]),
+                   c(1.040664, 0.6359187, 0.5291422, 0.4824796), tol = 1e-4)
+     )
+     showProc.time()
+ 
+ }) ## skip on windows (for speed)
> 
> 
> cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''
Time elapsed:  1.78 0.28 2.04 NA NA 
> 
> 
> 
> proc.time()
   user  system elapsed 
   1.78    0.28    2.04