R Under development (unstable) (2023-11-02 r85465 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(lme4) Loading required package: Matrix > n <- nrow(sleepstudy) > op <- options(warn = 1, # show as they happen ("false" convergence warnings) + useFancyQuotes = FALSE) > > if (.Platform$OS.type != "windows") { + ##' remove all attributes but names + dropA <- function(x) `attributes<-`(x, list(names = names(x))) + ##' transform result of "numeric" all.equal.list() to a named vector + all.eqL <- function(x1, x2, ...) { + r <- sub("^Component ", '', all.equal(x1, x2, tolerance = 0, ...)) + r <- strsplit(sub(": Mean relative difference:", "&&", r), + split="&&", fixed=TRUE) + setNames(as.numeric(vapply(r, `[`, "1.234", 2L)), + ## drop surrounding "..." + nm = sub('"$', '', substring(vapply(r, `[`, "nam", 1L), first=2))) + } + seedF <- function(s) { + if(s %in% c(6, 39, 52, 57, 63, 74, 76, 86)) + switch(as.character(s) + , "52"=, "63"=, "74" = 2 + , "6"=, "39" = 3 + , "86" = 8 # needs 4 on Lnx-64b + , "76" = 70 # needs 42 on Lnx-64b + , "57" = 90 # needs 52 on Lnx-64b + ) + else if(s %in% c(1, 12, 15, 34, 36, 41, 42, 43, 49, 55, 59, 67, 80, 85)) ## seeds 41,59, .. 15 + 1.0 + else ## seeds 22, 20, and better + 0.25 + } + ## be fast, running only 10 seeds by default: + sMax <- if(lme4:::testLevel() > 1) 99L else 9L + mySeeds <- 0L:sMax + + lapply(setNames(,mySeeds), function(seed) { + cat("\n------ random seed =", seed, "---------\n") + set.seed(seed) + v <- rpois(n,1) + 1 + w <- 1/v + cat("weights w:\n") + fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy, REML=FALSE, weights = w); cat("..2:\n") + fm2 <- lmer(Reaction ~ Days + (1 | Subject), sleepstudy, REML=FALSE, weights = w) + cat("weights w*10:\n") + fm1.10 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy, REML=FALSE, weights = w*10);cat("..2:\n") + fm2.10 <- lmer(Reaction ~ Days + (1 | Subject), sleepstudy, REML=FALSE, weights = w*10) + ## + ano12... <- dropA(anova(fm1, fm2 )) + ano12.10 <- dropA(anova(fm1.10, fm2.10)) + print(aEQ <- all.eqL(ano12..., ano12.10)) # showing differences + if(!exists("notChisq")) + notChisq <<- + local({ n <- names(ano12...) + grep("Chisq", n, value=TRUE, fixed=TRUE, invert=TRUE) }) + stopifnot( + all.equal(ano12...$Chisq, + ano12.10$Chisq, tol = 1e-6 * seedF(seed)) + , + all.equal(ano12...[notChisq], + ano12.10[notChisq], tol= 1.5e-8 * seedF(seed)) + ) + aEQ + }) -> rallEQ + + cat("=====================================\n") + + rallEQ <- t(simplify2array(rallEQ)) + notChisq <- intersect(notChisq, colnames(rallEQ)) + ## sort according to "severity": + srallEQ <- rallEQ[with(as.data.frame(rallEQ), order(AIC, Chisq)), ] + round(log10(srallEQ), 2) + saveRDS(srallEQ, "priorWeightsMod_relerr.rds") + + if(!dev.interactive(orNone=TRUE)) pdf("priorWeightsMod_relerr.pdf") + + matplot(mySeeds, log10(srallEQ), type="l", xlab=NA) ; grid() + legend("topleft", ncol=3, bty="n", + paste(1:6, colnames(srallEQ), sep = ": "), col=1:6, lty=1:6) + tolD <- sqrt(.Machine$double.eps) # sqrt(eps_C) + abline(h = log10(tolD), col = "forest green", lty=3) + axis(4, at=log10(tolD), label=quote(sqrt(epsilon[c])), las=1) + LRG <- which(srallEQ[,"AIC"] > tolD) + if (length(LRG)>0) { + text(LRG, log10(srallEQ[LRG, "AIC"]), names(LRG), cex = .8) + } + + ## how close are we .. + str(tF <- sapply(mySeeds, seedF)) + round(sort( rallEQ[, "Chisq"] / (tF * 1e-6 ), decreasing=TRUE), 1) + round(sort(apply(rallEQ[,notChisq] / (tF * 1.5e-8), 1, max), decreasing=TRUE), 1) + } ## skip on windows (for speed) > options(op) > > proc.time() user system elapsed 1.76 0.26 2.01