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Type 'q()' to quit R. > 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: 1.31 0.12 1.42 NA NA > > > > proc.time() user system elapsed 1.31 0.12 1.42