* using log directory 'd:/RCompile/CRANincoming/R-devel/asremlPlus.Rcheck' * using R version 4.5.0 beta (2025-04-02 r88102 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 14.2.0 GNU Fortran (GCC) 14.2.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * checking for file 'asremlPlus/DESCRIPTION' ... OK * this is package 'asremlPlus' version '4.4.47' * checking CRAN incoming feasibility ... [17s] NOTE Maintainer: 'Chris Brien ' Suggests or Enhances not in mainstream repositories: asreml * checking package namespace information ... OK * checking package dependencies ... INFO Package which this enhances but not available for checking: 'asreml' * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking whether package 'asremlPlus' can be installed ... OK * checking installed package size ... 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[19s] ERROR Running examples in 'asremlPlus-Ex.R' failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: pairdiffsTransform.alldiffs > ### Title: Calculates the differences between nominated pairs of > ### predictions stored in an 'alldiffs.object'. > ### Aliases: pairdiffsTransform.alldiffs pairdiffsTransform > ### Keywords: asreml > > ### ** Examples > > #### Form the differences for log(RGR) for Salinity > load(system.file("extdata", "testDiffs.rda", package = "asremlPlus", mustWork = TRUE)) > #### For the ratios for Cl per WU Temperature - use backtransforms of log-predictions > Preds.ratio.ClUp <- pairdiffsTransform(diffs.ClUp, + pairs.factor = "Temperature", + first.levels = "Hot", + second.levels = "Cool", + error.intervals = "halfLeast", + tables = "backtransforms") #Backtransforms are ratios #### Backtransforms of predictions for ClUp from Temperature:Salinity:Genotype Salinity Genotype backtransformed.predictions standard.error 1 Control 1 0.9440984 NA 2 Control 2 1.1386891 NA 3 Control 3 1.0716081 NA 4 Control 4 0.6347434 NA 5 Control 5 0.3603608 NA 6 Control 6 0.7780791 NA 7 Control 7 0.4700932 NA 8 Control 8 0.3766150 NA 9 Control 9 0.4483630 NA 10 Control 10 0.3172156 NA 11 Salt 1 1.3363073 NA 12 Salt 2 1.0144083 NA 13 Salt 3 0.6973966 NA 14 Salt 4 0.7185586 NA 15 Salt 5 1.6836110 NA 16 Salt 6 0.3203425 NA 17 Salt 7 2.8858561 NA 18 Salt 8 1.6384383 NA 19 Salt 9 0.9463362 NA 20 Salt 10 1.0001309 NA upper.halfLeastSignificant.limit lower.halfLeastSignificant.limit est.status 1 1.5311877 0.5821114 Estimable 2 1.8467848 0.7020920 Estimable 3 1.7379893 0.6607312 Estimable 4 1.0294597 0.3913696 Estimable 5 0.5844518 0.2221910 Estimable 6 1.2619288 0.4797473 Estimable 7 0.7624215 0.2898497 Estimable 8 0.6108138 0.2322130 Estimable 9 0.7271783 0.2764513 Estimable 10 0.5144767 0.1955885 Estimable 11 2.1672923 0.8239393 Estimable 12 1.6452198 0.6254630 Estimable 13 1.1310738 0.4300002 Estimable 14 1.1653955 0.4430483 Estimable 15 2.7305674 1.0380795 Estimable 16 0.5195480 0.1975165 Estimable 17 4.6804307 1.7793588 Estimable 18 2.6573039 1.0102270 Estimable 19 1.5348170 0.5834912 Estimable 20 1.6220640 0.6166599 Estimable > > #### Form the differences for Nitrogen compared to no Nitrogen > data("Oats.dat") > ## Not run: > ##D m1.asr <- asreml(Yield ~ Nitrogen*Variety, > ##D random=~Blocks/Wplots, > ##D data=Oats.dat) > ##D current.asrt <- as.asrtests(m1.asr) > ##D wald.tab <- current.asrt$wald.tab > ##D Var.diffs <- predictPlus(m1.asr, classify="Nitrogen:Variety", pairwise = TRUE, > ##D Vmatrix = TRUE, error.intervals = "halfLeast", > ##D LSDtype = "factor", LSDby = "Variety", > ##D wald.tab = wald.tab) > ## End(Not run) > > ## Use lme4 and emmmeans to get predictions and associated statistics > if (requireNamespace("lmerTest", quietly = TRUE) & + requireNamespace("emmeans", quietly = TRUE)) + { + m1.lmer <- lmerTest::lmer(Yield ~ Nitrogen*Variety + (1|Blocks/Wplots), + data=Oats.dat) + ## Set up a wald.tab + int <- as.data.frame(rbind(rep(NA,4))) + rownames(int) <- "(Intercept)" + wald.tab <- anova(m1.lmer, ddf = "Kenward", type = 1)[,3:6] + names(wald.tab) <- names(int) <- c("Df", "denDF", "F.inc", "Pr") + wald.tab <- rbind(int, wald.tab) + #Get predictions + Var.emm <- emmeans::emmeans(m1.lmer, specs = ~ Nitrogen:Variety) + Var.preds <- summary(Var.emm) + ## Modify Var.preds to be compatible with a predictions.frame + Var.preds <- as.predictions.frame(Var.preds, predictions = "emmean", + se = "SE", interval.type = "CI", + interval.names = c("lower.CL", "upper.CL")) + Var.vcov <- vcov(Var.emm) + Var.sed <- NULL + den.df <- wald.tab[match("Variety", rownames(wald.tab)), "denDF"] + + #Create alldiffs object + Var.diffs <- as.alldiffs(predictions = Var.preds, + sed = Var.sed, vcov = Var.vcov, + classify = "Nitrogen:Variety", response = "Yield", tdf = den.df) + } Error in pf(q = Fvalue, df1 = ndf, df2 = ddf, lower.tail = FALSE) : Non-numeric argument to mathematical function Calls: anova ... contestMD -> contestMD.lmerModLmerTest -> mk_Ftable -> pf Execution halted * checking for unstated dependencies in 'tests' ... OK * checking tests ... OK Running 'testthat.R' * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... OK * checking PDF version of manual ... [34s] OK * checking HTML version of manual ... [32s] OK * DONE Status: 1 ERROR, 1 NOTE