* using log directory 'd:/Rcompile/CRANpkg/local/3.6/robustbase.Rcheck' * using R version 3.6.3 (2020-02-29) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: ISO8859-1 * checking for file 'robustbase/DESCRIPTION' ... OK * this is package 'robustbase' version '0.93-7' * checking package namespace information ... OK * checking package dependencies ... OK * 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 'robustbase' can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking 'build' directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * loading checks for arch 'i386' ** checking whether the package can be loaded ... OK ** checking whether the package can be loaded with stated dependencies ... OK ** checking whether the package can be unloaded cleanly ... OK ** checking whether the namespace can be loaded with stated dependencies ... OK ** checking whether the namespace can be unloaded cleanly ... OK ** checking loading without being on the library search path ... OK ** checking use of S3 registration ... OK * loading checks for arch 'x64' ** checking whether the package can be loaded ... OK ** checking whether the package can be loaded with stated dependencies ... OK ** checking whether the package can be unloaded cleanly ... OK ** checking whether the namespace can be loaded with stated dependencies ... OK ** checking whether the namespace can be unloaded cleanly ... OK ** checking loading without being on the library search path ... OK ** checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... [32s] OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking contents of 'data' directory ... OK * checking data for non-ASCII characters ... OK * checking data for ASCII and uncompressed saves ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking line endings in Makefiles ... OK * checking compilation flags in Makevars ... OK * checking for GNU extensions in Makefiles ... OK * checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK * checking pragmas in C/C++ headers and code ... OK * checking compiled code ... OK * checking sizes of PDF files under 'inst/doc' ... OK * checking installed files from 'inst/doc' ... OK * checking files in 'vignettes' ... OK * checking examples ... ** running examples for arch 'i386' ... [39s] OK ** running examples for arch 'x64' ... [45s] OK * checking for unstated dependencies in 'tests' ... OK * checking tests ... ** running tests for arch 'i386' ... [135s] ERROR Running 'LTS-specials.R' [1s] Running 'MCD-specials.R' [1s] Comparing 'MCD-specials.Rout' to 'MCD-specials.Rout.save' ... OK Running 'MT-tst.R' [10s] Running 'NAcoef.R' [3s] Comparing 'NAcoef.Rout' to 'NAcoef.Rout.save' ... OK Running 'OGK-ex.R' [1s] Comparing 'OGK-ex.Rout' to 'OGK-ex.Rout.save' ... OK Running 'Qn-Sn-plots.R' [1s] Running 'Rsquared.R' [1s] Comparing 'Rsquared.Rout' to 'Rsquared.Rout.save' ... OK Running 'binom-ni-small.R' [1s] Comparing 'binom-ni-small.Rout' to 'binom-ni-small.Rout.save' ... OK Running 'binom-no-x.R' [1s] Running 'comedian-tst.R' [3s] Running 'exact-fit-categorical.R' [1s] Running 'glmrob-1.R' [14s] Running 'glmrob-specials.R' [1s] Running 'huber-etc.R' [1s] Comparing 'huber-etc.Rout' to 'huber-etc.Rout.save' ... OK Running 'large-values.R' [1s] Running 'lmrob-data.R' [6s] Running 'lmrob-ex12.R' [6s] Running 'lmrob-methods.R' [1s] Comparing 'lmrob-methods.Rout' to 'lmrob-methods.Rout.save' ... OK Running 'lmrob-psifns.R' [6s] Comparing 'lmrob-psifns.Rout' to 'lmrob-psifns.Rout.save' ... OK Running 'm-s-estimator.R' [4s] Running 'mc-etc.R' [1s] Running 'mc-strict.R' [8s] Running 'nlregrob-tst.R' [20s] Running 'nlrob-tst.R' [4s] Running 'poisson-ex.R' [3s] Running 'psi-rho-etc.R' [1s] Comparing 'psi-rho-etc.Rout' to 'psi-rho-etc.Rout.save' ... OK Running 'small-sample.R' [10s] Comparing 'small-sample.Rout' to 'small-sample.Rout.save' ... OK Running 'subsample.R' [9s] Running 'tlts.R' [1s] Comparing 'tlts.Rout' to 'tlts.Rout.save' ... OK Running 'tmcd.R' [12s] Running 'weights.R' [1s] Comparing 'weights.Rout' to 'weights.Rout.save' ...442,443c442,443 < Warning message: < In lf.cov(object, complete = complete, ...) : --- > Warning messages: > 1: In lf.cov(object, complete = complete, ...) : 444a445,446 > 2: In lf.cov(object, complete = complete, ...) : > .vcov.avar1: negative diag() fixed up; consider 'cov=".vcov.w."' instead Running 'wgt-himed-xtra.R' [4s] Running 'wgt-himed.R' [1s] Comparing 'wgt-himed.Rout' to 'wgt-himed.Rout.save' ...12,14d11 < > stopifnot(is.na(wgt.himedian(numeric()))) < > ## hi-median() seg.faulted or inf.looped till Jan.3, 2021 < > Running the tests in 'tests/mc-strict.R' failed. Complete output: > > #### Testing medcouple mc() and related functions > > ### here, we do "strict tests" -- hence no *.Rout.save > ### hence, can also produce non-reproducible output such as timing > > library(robustbase) > for(f in system.file("xtraR", c("mcnaive.R", # -> mcNaive() + "platform-sessionInfo.R"), + package = "robustbase", mustWork=TRUE)) { + cat("source(",f,"):\n", sep="") + source(f) + } source(D:/temp/Rtmpgn1XM9/RLIBS_119f839aa1be0/robustbase/xtraR/mcnaive.R): source(D:/temp/Rtmpgn1XM9/RLIBS_119f839aa1be0/robustbase/xtraR/platform-sessionInfo.R): > source(system.file("test-tools-1.R", package="Matrix", mustWork=TRUE)) Loading required package: tools > assertEQm12 <- function(x,y, giveRE=TRUE, ...) + assert.EQ(x,y, tol = 1e-12, giveRE=giveRE, ...) > ## ^^ shows *any* difference ("tol = 0") unless there is no difference at all > ## > c.time <- function(...) cat('Time elapsed: ', ..., '\n') > S.time <- function(expr) c.time(system.time(expr)) > DO <- function(...) S.time(stopifnot(...)) > > mS <- moreSessionInfo(print.=TRUE) List of 4 $ sizeof.long : int 4 $ sizeof.longlong : int 8 $ sizeof.longdouble: int 12 $ sizeof.pointer : int 4 32 bit platform type 'windows' ==> onWindows: TRUE arch: x86 osVersion (0): Windows Server 2008 x64 (build 6003) Service Pack 2 osVersion: Windows Server 2008 x64 (build 6003) Service Pack 2 + BLAS "is" Lapack: TRUE | BLAS=OpenBLAS: FALSE | Lapack=OpenBLAS: FALSE strictR: FALSE > > (doExtras <- robustbase:::doExtras())# TRUE if interactive() or activated by envvar [1] FALSE > > > n.set <- c(1:99, 1e5L+ 0:1) # large n gave integer overflow in earlier versions > DO(0 == sapply(n.set, function(n) mc(seq_len(n)))) Time elapsed: 0.08 0 0.08 NA NA > DO(0 == sapply(n.set, function(n) mc(seq_len(n), doRefl=FALSE))) Time elapsed: 0.08 0 0.08 NA NA > > DO(0 == sapply(1:100, function(n) mcNaive(seq_len(n), "simple"))) Time elapsed: 0.14 0 0.12 NA NA > DO(0 == sapply(1:100, function(n) mcNaive(seq_len(n), "h.use" ))) Time elapsed: 0.05 0 0.05 NA NA > > > x1 <- c(1, 2, 7, 9, 10) > mcNaive(x1) # = -1/3 [1] -0.3333333 > assertEQm12(-1/3, mcNaive(x1, "simple")) > assertEQm12(-1/3, mcNaive(x1, "h.use")) > assertEQm12(-1/3, mc(x1)) > > x2 <- c(-1, 0, 0, 0, 1, 2) > mcNaive(x2, meth="simple") # = 0 - which is wrong [1] 0 > mcNaive(x2, meth="h.use") # = 1/6 = 0.16666 [1] 0.1666667 > assertEQm12(1/6, mc(x2)) > assertEQm12(1/6, mcNaive(x2, "h.use")) > > x4 <- c(1:5,7,10,15,25, 1e15) ## - bombed in orignal algo > mcNaive(x4,"h.use") # 0.5833333 [1] 0.5833333 > assertEQm12( 7/12, mcNaive(x4, "h.use")) > assertEQm12( 7/12, mcNaive(x4, "simple")) > assertEQm12( 7/12, mc( x4, doRefl= FALSE)) > assertEQm12(-7/12, mc(-x4, doRefl= FALSE)) > > > set.seed(17) > for(n in 3:50) { + cat(" ") + for(k in 1:5) { + x <- rlnorm(n) + mc1 <- mc(x) + mc2 <- mcNaive(x, method = "simple") + mc3 <- mcNaive(x, method = "h.use" ) + stopifnot(all.equal(mc1, mc3, tolerance = 1e-10),# 1e-12 not quite ok + mc2 == mc3) + cat(".") + } + }; cat("\n") ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... ..... > > ###---- Strict tests of adjOutlyingness(): > ### ================= changed after long-standing bug fix in Oct.2014 > ## as this calls, sample.int() and we carefully compare specific seed examples, need > RNGversion("3.6.0") # == RNGversion("4.0.2") .. > RNGversion("3.5.0") ## [TODO: adapt to "current" RNG settings] Warning message: In RNGkind("Mersenne-Twister", "Inversion", "Rounding") : non-uniform 'Rounding' sampler used > > set.seed(1); S.time(a1.1 <- adjOutlyingness(longley)) Time elapsed: 0.19 0 0.17 NA NA > set.seed(11); S.time(a1.2 <- adjOutlyingness(longley)) Time elapsed: 0.31 0 0.31 NA NA > ## > set.seed(2); S.time(a2 <- adjOutlyingness(hbk)) Time elapsed: 0.17 0 0.17 NA NA > set.seed(3); S.time(a3 <- adjOutlyingness(hbk[, 1:3]))# the 'X' space Time elapsed: 0.11 0 0.19 NA NA > set.seed(4); S.time(a4 <- adjOutlyingness(milk)) # obs.63 = obs.64 Time elapsed: 0.17 0 0.19 NA NA > set.seed(5); S.time(a5 <- adjOutlyingness(wood)) Time elapsed: 0.14 0 0.16 NA NA > set.seed(6); S.time(a6 <- adjOutlyingness(wood[, 1:5]))# the 'X' space Time elapsed: 0.11 0 0.13 NA NA > > ## 32-bit <-> 64-bit different results {tested on Linux only} > is32 <- .Machine$sizeof.pointer == 4 ## <- should work for Linux/MacOS/Windows > isMac <- Sys.info()[["sysname"]] == "Darwin" > isSun <- Sys.info()[["sysname"]] == "SunOS" > Rnk <- function(u) rank(unname(u), ties.method = "first") > ## to use for testing below: > cat("\nRnk(a3 $ adjout): "); dput(Rnk(a3$adjout), control= {}) Rnk(a3 $ adjout): c(62, 64, 68, 71, 70, 65, 66, 63, 69, 67, 73, 75, 72, 74, 25, 52, 44, 3, 11, 33, 6, 21, 29, 28, 59, 9, 12, 13, 37, 27, 43, 35, 22, 55, 14, 2, 26, 46, 54, 15, 23, 41, 40, 32, 60, 30, 61, 19, 16, 8, 39, 53, 51, 48, 20, 47, 50, 42, 7, 38, 17, 57, 45, 18, 24, 34, 4, 58, 56, 5, 1, 10, 31, 36, 49) > cat("\nRnk(a4 $ adjout): "); dput(Rnk(a4$adjout), control= {}) Rnk(a4 $ adjout): c(84, 85, 80, 70, 56, 64, 26, 45, 57, 16, 52, 78, 73, 79, 76, 75, 68, 61, 58, 69, 34, 3, 7, 10, 22, 12, 62, 66, 59, 9, 35, 39, 6, 38, 30, 37, 42, 46, 19, 72, 83, 65, 48, 82, 44, 31, 71, 55, 51, 53, 32, 67, 14, 1, 11, 2, 36, 18, 43, 28, 4, 13, 40, 41, 23, 29, 20, 27, 47, 86, 50, 15, 63, 77, 81, 33, 54, 24, 5, 25, 8, 60, 17, 49, 74, 21) > > (i.a4Out <- which(!a4$nonOut)) # varies "wildly" [1] 70 > { + if(is32 && !isMac) + all.equal(i.a4Out, c(1, 2, 41, 70)) + ## and this is "typically" true, but not for a 64-bit Linux version bypassing BLAS in matprod + else if(isSun || isMac) + TRUE + else + all.equal(i.a4Out, c(9:19, 23:27,57, 59, 70, 77)) # '70' only 64b-Fedora_32, Dec.2020 + } [1] "Numeric: lengths (1, 4) differ" > > ## only for ATLAS (BLAS/Lapack), not all are TRUE; which ones? > if(!all(a5$nonOut)) + print(which(!a5$nonOut)) # if we know, enable check below > > stopifnot(exprs = { + which(!a2$nonOut) == 1:14 + which(!a3$nonOut) == 1:14 + ## 'longley', 'wood' have no outliers in the "adjOut" sense: + ## FIXME: longley is platform dependent too + { if(isMac) TRUE + else if(mS$ strictR) sum(a1.2$nonOut) >= 15 # sum(.) = 16 [nb-mm3, Oct.2014] + else ## however, openBLAS Fedora Linux /usr/bin/R gives sum(a1.2$nonOut) = 13 + sum(a1.2$nonOut) >= 13 + } + if(doExtras) { + if(mS$ strictR) a5$nonOut + else ## not for ATLAS + sum(a5$nonOut) >= 18 # 18: OpenBLAS + } else TRUE + a6$nonOut[-20] + ## hbk (n = 75) : + abs(Rnk(a3$adjout) - + c(62, 64, 68, 71, 70, 65, 66, 63, 69, 67, 73, 75, 72, 74, 25, + 52, 44, 5, 11, 33, 6, 21, 29, 28, 59, 9, 12, 13, 37, 27, + 43, 35, 22, 55, 14, 2, 26, 46, 54, 15, 23, 41, 40, 32, 60, + 30, 61, 19, 16, 8, 39, 53, 51, 48, 20, 47, 50, 42, 7, 38, + 17, 57, 45, 18, 24, 34, 3, 58, 56, 4, 1, 10, 31, 36, 49) + ) <= 3 ## all 0 on 32-bit Linux + }) > > ## milk (n = 86) : -- Quite platform dependent! > r <- Rnk(a4$adjout) > r64 <- ## the 64-bit (ubuntu 14.04, nb-mm3) values: + c(65, 66, 61, 56, 47, 51, 19, 37, 74, 67, 79, 86, 83, 84, 85, + 82, 81, 73, 80, 55, 27, 3, 70, 68, 78, 76, 77, 53, 48, 8, + 29, 33, 6, 32, 28, 31, 36, 40, 22, 58, 64, 52, 39, 63, 44, + 30, 57, 46, 43, 45, 25, 54, 12, 1, 9, 2, 71, 14, 75, 23, + 4, 10, 34, 35, 17, 24, 15, 20, 38, 72, 42, 13, 50, 60, 62, + 26, 69, 18, 5, 21, 7, 49, 11, 41, 59, 16) > r32 <- ## Linux 32bit (florence: 3.14.8-100.fc19.i686.PAE) + c(78, 79, 72, 66, 52, 61, 22, 41, 53, 14, 74, 85, 82, 83, 84, + 80, 81, 56, 73, 65, 30, 3, 16, 17, 68, 57, 58, 63, 54, 8, + 32, 37, 6, 36, 31, 35, 40, 44, 25, 69, 77, 62, 43, 76, 48, + 34, 67, 51, 47, 49, 28, 64, 12, 1, 9, 2, 33, 15, 59, 26, + 4, 10, 38, 39, 20, 27, 18, 23, 42, 86, 46, 13, 60, 71, 75, + 29, 50, 21, 5, 24, 7, 55, 11, 45, 70, 19) > d <- (r - if (is32) r32 else r64) > cbind(r, d) r d [1,] 84 6 [2,] 85 6 [3,] 80 8 [4,] 70 4 [5,] 56 4 [6,] 64 3 [7,] 26 4 [8,] 45 4 [9,] 57 4 [10,] 16 2 [11,] 52 -22 [12,] 78 -7 [13,] 73 -9 [14,] 79 -4 [15,] 76 -8 [16,] 75 -5 [17,] 68 -13 [18,] 61 5 [19,] 58 -15 [20,] 69 4 [21,] 34 4 [22,] 3 0 [23,] 7 -9 [24,] 10 -7 [25,] 22 -46 [26,] 12 -45 [27,] 62 4 [28,] 66 3 [29,] 59 5 [30,] 9 1 [31,] 35 3 [32,] 39 2 [33,] 6 0 [34,] 38 2 [35,] 30 -1 [36,] 37 2 [37,] 42 2 [38,] 46 2 [39,] 19 -6 [40,] 72 3 [41,] 83 6 [42,] 65 3 [43,] 48 5 [44,] 82 6 [45,] 44 -4 [46,] 31 -3 [47,] 71 4 [48,] 55 4 [49,] 51 4 [50,] 53 4 [51,] 32 4 [52,] 67 3 [53,] 14 2 [54,] 1 0 [55,] 11 2 [56,] 2 0 [57,] 36 3 [58,] 18 3 [59,] 43 -16 [60,] 28 2 [61,] 4 0 [62,] 13 3 [63,] 40 2 [64,] 41 2 [65,] 23 3 [66,] 29 2 [67,] 20 2 [68,] 27 4 [69,] 47 5 [70,] 86 0 [71,] 50 4 [72,] 15 2 [73,] 63 3 [74,] 77 6 [75,] 81 6 [76,] 33 4 [77,] 54 4 [78,] 24 3 [79,] 5 0 [80,] 25 1 [81,] 8 1 [82,] 60 5 [83,] 17 6 [84,] 49 4 [85,] 74 4 [86,] 21 2 > table(abs(d)) 0 1 2 3 4 5 6 7 8 9 13 15 16 22 45 46 7 4 15 13 21 6 8 2 2 2 1 1 1 1 1 1 > cumsum(table(abs(d))) # <=> unscaled ecdf(d) 0 1 2 3 4 5 6 7 8 9 13 15 16 22 45 46 7 11 26 39 60 66 74 76 78 80 81 82 83 84 85 86 > > ## For the biggest part (79 out of 86), the ranks are "close": > ## 2014: still true, but in a different sense.. > ## ^ typically, but e.g., *not* when using non-BLAS matprod(): > sum(abs(d) <= 17) >= 78 [1] TRUE > sum(abs(d) <= 13) >= 75 [1] TRUE > > > RNGversion("3.6.0") # == RNGversion("4.0.2") .. > > ## check of adjOutlyingness *free* bug > ## reported by Kaveh Vakili > set.seed(-37665251) > X <- matrix(rnorm(100*5),100,5) > Z <- matrix(rnorm(100*5,0,1/100),10,5) > Z <- sweep(Z, 2, c(5,rep(0,4)), FUN="+") > X[91:100,] <- Z > for (i in 1:10) { + ## this would produce an error in the 6th iteration + aa <- adjOutlyingness(x=X,ndir=250) + } > > ## Check "high"-dimensional Noise ... typically mc() did *not* converge for some re-centered columns > ## Example by Valentin Todorov: > n <- 50 > p <- 30 > set.seed(1) # MM > a <- matrix(rnorm(n * p), nrow=n, ncol=p) > str(a) num [1:50, 1:30] -0.626 0.184 -0.836 1.595 0.33 ... > kappa(a) # 20.42 (~ 10--20 or so; definitely not close to singular) [1] 20.42296 > a.a <- adjOutlyingness(a, mcScale=FALSE, # <- my own recommendation + trace.lev=1) keeping *all* 250 normalized directions med <- colMedians(Y): 250 values; summary(): Min. 1st Qu. Median Mean 3rd Qu. Max. 0.002157 0.052337 0.106917 0.128326 0.175055 0.582199 Columnwise mc() got 250 values; summary(): Min. 1st Qu. Median Mean 3rd Qu. Max. -1.00000 -0.35003 -0.08430 -0.12565 0.09606 1.00000 250 lower & upper Y (:= X - med(.)) values: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0000000 0.0000000 0.0000000 0.2340537 0.0000841 2.9154090 Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00000 0.00000 0.00000 0.07054 0.00000 2.69953 outlyingnesses for all directions (of which max(.) will be chosen: 0% 25% 50% 75% 100% 0.000000e+00 1.749008e-01 5.558390e-01 3.425042e+14 1.354116e+16 > a.s <- adjOutlyingness(a, mcScale=TRUE, trace.lev=1) keeping *all* 250 normalized directions med <- colMedians(Y): 250 values; summary(): Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0006641 0.0700928 0.1242860 0.1483769 0.2124847 0.5023069 Columnwise mc() got 250 values; summary(): Min. 1st Qu. Median Mean 3rd Qu. Max. -1.00000 -0.61958 -0.15346 -0.20492 0.07268 1.00000 250 lower & upper Y (:= X - med(.)) values: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00000 0.00000 0.00000 0.39893 0.09289 3.43848 Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00000 0.00000 0.00000 0.09298 0.00000 3.08440 outlyingnesses for all directions (of which max(.) will be chosen: 0% 25% 50% 75% 100% 0.000000e+00 1.702128e-01 5.454545e-01 3.598388e+14 1.397720e+16 > > str(a.a) # surprisingly high 'adjout' values "all similar" -> no outliers .. hmm .. ??? List of 7 $ adjout : num [1:50] 3.77e+15 4.83e+15 1.35e+16 8.29e+15 6.94e+15 ... $ iter : int 250 $ ndir.final : int 250 $ MCadjout : num 0.15 $ Qalph.adjout: Named num [1:2] 4.49e+15 7.25e+15 ..- attr(*, "names")= chr [1:2] "25%" "75%" $ cutoff : Named num 1.38e+16 ..- attr(*, "names")= chr "75%" $ nonOut : logi [1:50] TRUE TRUE TRUE TRUE TRUE TRUE ... > stopifnot(exprs = { + ## a.a : + identical(a.a$nonOut, local({r <- rep(TRUE, 50); r[22] <- FALSE; r})) + all.equal(a.a$MCadjout, 0.136839766177, tol = 1e-12) # seen 7.65e-14 + ## a.s : + a.s$nonOut # all TRUE + all.equal(a.s$MCadjout, 0.32284906741568, tol = 1e-13) # seen 2.2e-15 + }) Error: identical(a.a$nonOut, local({ .... is not TRUE Execution halted ** running tests for arch 'x64' ... [151s] OK Running 'LTS-specials.R' [1s] Running 'MCD-specials.R' [1s] Comparing 'MCD-specials.Rout' to 'MCD-specials.Rout.save' ... OK Running 'MT-tst.R' [12s] Running 'NAcoef.R' [3s] Comparing 'NAcoef.Rout' to 'NAcoef.Rout.save' ... OK Running 'OGK-ex.R' [1s] Comparing 'OGK-ex.Rout' to 'OGK-ex.Rout.save' ... OK Running 'Qn-Sn-plots.R' [1s] Running 'Rsquared.R' [1s] Comparing 'Rsquared.Rout' to 'Rsquared.Rout.save' ... OK Running 'binom-ni-small.R' [1s] Comparing 'binom-ni-small.Rout' to 'binom-ni-small.Rout.save' ... OK Running 'binom-no-x.R' [1s] Running 'comedian-tst.R' [3s] Running 'exact-fit-categorical.R' [1s] Running 'glmrob-1.R' [17s] Running 'glmrob-specials.R' [1s] Running 'huber-etc.R' [1s] Comparing 'huber-etc.Rout' to 'huber-etc.Rout.save' ... OK Running 'large-values.R' [1s] Running 'lmrob-data.R' [6s] Running 'lmrob-ex12.R' [6s] Running 'lmrob-methods.R' [1s] Comparing 'lmrob-methods.Rout' to 'lmrob-methods.Rout.save' ... OK Running 'lmrob-psifns.R' [6s] Comparing 'lmrob-psifns.Rout' to 'lmrob-psifns.Rout.save' ... OK Running 'm-s-estimator.R' [4s] Running 'mc-etc.R' [1s] Running 'mc-strict.R' [12s] Running 'nlregrob-tst.R' [23s] Running 'nlrob-tst.R' [5s] Running 'poisson-ex.R' [3s] Running 'psi-rho-etc.R' [1s] Comparing 'psi-rho-etc.Rout' to 'psi-rho-etc.Rout.save' ... OK Running 'small-sample.R' [12s] Comparing 'small-sample.Rout' to 'small-sample.Rout.save' ... OK Running 'subsample.R' [8s] Running 'tlts.R' [1s] Comparing 'tlts.Rout' to 'tlts.Rout.save' ... OK Running 'tmcd.R' [12s] Running 'weights.R' [1s] Comparing 'weights.Rout' to 'weights.Rout.save' ... OK Running 'wgt-himed-xtra.R' [4s] Running 'wgt-himed.R' [1s] Comparing 'wgt-himed.Rout' to 'wgt-himed.Rout.save' ...12,14d11 < > stopifnot(is.na(wgt.himedian(numeric()))) < > ## hi-median() seg.faulted or inf.looped till Jan.3, 2021 < > * checking for unstated dependencies in vignettes ... OK * checking package vignettes in 'inst/doc' ... OK * checking re-building of vignette outputs ... [90s] OK * checking PDF version of manual ... OK * DONE Status: 1 ERROR