Last updated on 2026-02-17 09:50:09 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| Bessel | 14 | ||
| bitops | 14 | ||
| CLA | 14 | ||
| classGraph | 14 | ||
| cluster | 14 | ||
| cobs | 14 | ||
| copula | 5 | 9 | |
| diptest | 14 | ||
| DPQ | 14 | ||
| DPQmpfr | 14 | ||
| expm | 14 | ||
| fracdiff | 14 | ||
| lokern | 14 | ||
| longmemo | 14 | ||
| lpridge | 14 | ||
| nor1mix | 1 | 13 | |
| plugdensity | 2 | 12 | |
| Rmpfr | 14 | ||
| robustbase | 14 | ||
| robustX | 5 | 9 | |
| round | 14 | ||
| sca | 2 | 12 | |
| sfsmisc | 14 | ||
| simest | 3 | 11 | |
| stabledist | 14 | ||
| supclust | 2 | 12 | |
| VLMC | 14 |
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: NOTE: 5, OK: 9
Version: 1.1-6
Check: relative paths in package URLs
Result: NOTE
Found the following (possibly) invalid URL:
URL: ../doc/Frank-Rmpfr
From: man/copula-package.Rd
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.1-6
Check: installed package size
Result: NOTE
installed size is 7.8Mb
sub-directories of 1Mb or more:
R 2.4Mb
doc 3.2Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 1.1-6
Flags: --no-vignettes
Check: installed package size
Result: NOTE
installed size is 7.3Mb
sub-directories of 1Mb or more:
R 2.1Mb
doc 3.2Mb
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: ERROR: 1, OK: 13
Version: 1.3-3
Check: tests
Result: ERROR
Running ‘MW.R’ [0s/0s]
Comparing ‘MW.Rout’ to ‘MW.Rout.save’ ... OK
Running ‘par.R’ [0s/0s]
Running ‘qnorMix-ex.R’ [0s/0s]
Running the tests in ‘tests/qnorMix-ex.R’ failed.
Complete output:
> ## Marron Wand examples are defined as norMix() calls in ../R/zMarrWand-dens.R
> library("nor1mix")
>
> ii <- c(32, 39, 40, 40, 48, 48, 49, 56, 57, 58, 65)
> pp <- 0.486 + ii / 100000 # very constrained set
>
> e <- norMix(mu = c(-0.825,0.275), sigma = sqrt(0.773), w = c(1, 3)/4)
>
> qnorMix(pp, e, trace = TRUE)
1: relE =2.995e-14
[1] -0.007781385 -0.007605111 -0.007579910 -0.007579910 -0.007378307
[6] -0.007378307 -0.007353107 -0.007176708 -0.007151508 -0.007126309
[11] -0.006949786
> ## failed for version <= 1.0-5
>
> q.pp <- -c(7.78151762922529, 7.60511100150266, 7.57991031275271, 7.57991031275271,
+ 7.37830712226037, 7.37830712226037, 7.35310701314534, 7.17670804948685,
+ 7.15150845450588, 7.12630892371882, 6.94991400429199) / 1000
>
> for (m in eval(formals(qnorMix)$method)) {
+ cat("method ", m,":")
+ stopifnot(all.equal(q.pp, qnorMix(pp, e, method = m, tol = 1e-14),
+ tol = 1e-13),# 1.022e-14 (32-bit)
+ abs(qnorMix(rep(1/2, 8), MW.nm10, method = m)) < 1e-14
+ )
+ cat("\n")
+ }
method interpQspline :
method interpspline :
method eachRoot :
method root2 :
>
> ### a "nasty" example (for the newton steps):
> ip <- c(0, 1e-11, 3.33e-09, 7.705488e-05, 0.0001670041, 0.00125378934,
+ 0.00141169953, 0.00357409109, 0.00644073795, 0.00853238955, 0.01361442421,
+ 0.01672761627, 0.02067755849, 0.02124092026, 0.03327537558, 0.03527226553,
+ 0.05365983941, 0.05482289811, 0.05669602608, 0.05982167629)
> qv <- qnorMix(1-ip, MW.nm12, trace=1)
,,1: relE =0.003125
2: relE =0.0005494
3: relE =7.656e-05
> ## now ok
>
> ### --- lower.tail=FALSE did not work correctly at some point
> qv. <- qnorMix(ip, MW.nm12, lower.tail=FALSE, trace=1)#2, maxiter=50)
,,1: relE =0.003125
2: relE =0.0005494
3: relE =7.656e-05
> stopifnot(all.equal(qv, qv., tol = 1e-5))
>
> ## qnorMix(*, log.p=TRUE) currently warns about missing Newton step implementation
> qnorMixLog <- function(p, obj, lower.tail = TRUE, ...)
+ suppressWarnings(qnorMix(p, obj, lower.tail=lower.tail, log.p=TRUE, ...))
> ##
> n2 <- 8
> set.seed(11)
> for(i in 1:50) {
+ cat(i, "", if(i %% 20 == 0)"\n")
+ u0 <- c(0,sort(runif(n2)),1)
+ q0 <- qnorMix(u0, MW.nm2, trace=0, tol=4e-16)
+ qL <- qnorMix(1-u0, MW.nm2, lower.tail=FALSE, trace=0, tol=4e-16)
+ stopifnot(all.equal(pnorMix(q0, MW.nm2), u0, tol=1e-15),
+ all.equal(q0, qL, tol=1e-14))
+ i. <- 2:(n2+1); u0. <- u0[i.]
+ ## --- log.p= TRUE [no Newton steps]
+ q0. <- qnorMixLog(log ( u0.), MW.nm2, tol=4e-16)
+ qL. <- qnorMixLog(log1p(-u0.), MW.nm2, lower.tail=FALSE, tol=4e-16)
+ stopifnot(all.equal(pnorMix(q0, MW.nm2), u0, tol=1e-15),
+ all.equal(q0, qL, tol=1e-14),
+ all.equal(q0., qL., tol=1e-10),
+ all.equal(q0[i.], q0., tol = 6e-6)# no Newton => less accuracy
+ )
+ }; cat("\n")
1 Error: q0 and qL are not equal:
Mean relative difference: 1.037164e-14
Execution halted
Flavor: r-devel-macos-arm64
Current CRAN status: NOTE: 2, OK: 12
Version: 0.8-5
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Martin Maechler <maechler@stat.math.ethz.ch>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = c("Eva", "Herrmann;", "R", "interface", "etc", "by", "Martin"),
family = "Maechler",
role = "aut",
email = "eherrmann@mathematik.tu-darmstadt.de",
comment = "C original"),
person(given = "Martin",
family = "Maechler",
role = "cre",
email = "maechler@stat.math.ethz.ch"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Current CRAN status: OK: 14
Current CRAN status: OK: 14
Current CRAN status: ERROR: 5, OK: 9
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘L1med-tst.R’ [1s/2s]
Running ‘cov-ex.R’ [1s/1s]
Running the tests in ‘tests/cov-ex.R’ failed.
Complete output:
> library(robustX)
> library(robustbase)
> (newRB <- (packageVersion("robustbase") >= "0.99"))
[1] TRUE
>
> sessionInfo()
R Under development (unstable) (2026-02-11 r89406)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux forky/sid
Matrix products: default
BLAS: /home/hornik/tmp/R.check/r-devel-clang/Work/build/lib/libRblas.so
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Vienna
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] robustbase_0.99-7 robustX_1.2-7
loaded via a namespace (and not attached):
[1] DEoptimR_1.1-4 compiler_4.6.0
> packageDescription("robustX")
Package: robustX
Type: Package
Title: 'eXtra' / 'eXperimental' Functionality for Robust Statistics
Version: 1.2-7
Date: 2023-06-14
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"),
email="maechler@stat.math.ethz.ch", comment = c(ORCID =
"0000-0002-8685-9910")) , person("Werner A.", "Stahel",
role="aut", email="stahel@stat.math.ethz.ch") , person("Rolf",
"Turner", role="ctb", email="r.turner@auckland.ac.nz", comment
= "reclas()") , person("Ueli", "Oetliker", role="ctb", comment
= "original version of BACON() and mvBACON for S+") ,
person("Tobias", "Schoch", role="ctb", comment =
"init.sel=\"V2\" for BACON; fix alpha") )
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Description: Robustness -- 'eXperimental', 'eXtraneous', or
'eXtraordinary' Functionality for Robust Statistics. Hence
methods which are not well established, often related to
methods in package 'robustbase'. Amazingly, 'BACON()',
originally by Billor, Hadi, and Velleman (2000)
<doi:10.1016/S0167-9473(99)00101-2> has become established in
places. The "barrow wheel" `rbwheel()` is from Stahel and
Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.
Imports: grDevices, graphics, stats, utils, robustbase (>= 0.92-3)
Suggests: MASS, lattice, pcaPP
Enhances: ICS
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-06-14 21:41:58 UTC; maechler
Author: Martin Maechler [aut, cre]
(<https://orcid.org/0000-0002-8685-9910>), Werner A. Stahel
[aut], Rolf Turner [ctb] (reclas()), Ueli Oetliker [ctb]
(original version of BACON() and mvBACON for S+), Tobias Schoch
[ctb] (init.sel="V2" for BACON; fix alpha)
Repository: CRAN
Date/Publication: 2023-06-16 07:30:02 UTC
Built: R 4.6.0; ; 2026-02-12 10:40:13 UTC; unix
-- File: /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/robustX/Meta/package.rds
> (ourBLAS <- grepl(print(normalizePath(R.home())),
+ normalizePath(extSoftVersion()[["BLAS"]]), fixed = TRUE))
[1] "/home/hornik/tmp/R.check/r-devel-clang/Work/build"
[1] TRUE
> ## need extended precision (typically *includes* 64-bit):
> doCheck <- (.Machine$sizeof.longdouble >= 16)
> cat("doCheck (= have long double):", doCheck,"\n")
doCheck (= have long double): TRUE
>
> if(!dev.interactive(orNone=TRUE)) pdf("cov-ex.pdf")
>
> covNN.1 <- robustX:::covNNC1 ## the original definition (2003)
>
> data(iris)
> system.time(cN1 <- covNN.1(iris[-5]))
user system elapsed
0.174 0.015 0.189
> system.time(cN <- covNNC (iris[-5]))# faster indeed
user system elapsed
0.088 0.000 0.169
>
> ## report.and.stop.if.not.all.equal
> report.stopifnot.all.eq <- function(a,b, tol, ...) {
+ call <- sys.call()
+ ae <- all.equal(a,b, tol=tol, ...)
+ call[[1]] <- quote(all.equal)
+ if(!isTRUE(ae))
+ stop(sprintf("Not %s:\n%s\n\n", deparse(call),
+ paste(ae, collapse="\n")),
+ call.=FALSE)
+ ## else
+ TRUE
+ }
>
> UN <- function(L) lapply(L, unname)
>
> chk.NN.new.old <- function(cNew, cNold, tol = 2e-15, tol.1 = 20*tol) {
+ stopifnot(is.list(cNold$innc), length(n.i <- names(cNold$innc)) == 4)
+ cat("classification accordance matrix:\n")
+ print(table(new = cNew $classification,
+ old = cNold$classification))
+ report.stopifnot.all.eq(UN(cNew [1:4]),
+ UN(cNold[1:4]), tol=tol.1) &
+ report.stopifnot.all.eq(cNew $innc[n.i],
+ cNold$innc[n.i], tol=tol)
+ }
>
> summ.NN <- function(cNN, digits = 3) {
+ cbind(class = cNN$classification,
+ pprob = round(cNN$postprob, digits),
+ incc.p= round(cNN$innc$postprob, digits))
+ }
>
> s1 <- summ.NN(cN1)
> ss <- summ.NN(cN)
> if(isTRUE(all.equal(ss, s1))) ss else cbind(ss, s1)
class pprob incc.p class pprob incc.p
[1,] 1 1.000 1.000 1 1.000 1.000
[2,] 1 1.000 1.000 1 1.000 1.000
[3,] 1 1.000 1.000 1 1.000 1.000
[4,] 1 1.000 1.000 1 1.000 1.000
[5,] 1 1.000 1.000 1 1.000 1.000
[6,] 1 1.000 0.171 1 1.000 0.171
[7,] 1 1.000 1.000 1 1.000 1.000
[8,] 1 1.000 1.000 1 1.000 1.000
[9,] 1 1.000 1.000 1 1.000 1.000
[10,] 1 1.000 1.000 1 1.000 1.000
[11,] 1 1.000 1.000 1 1.000 1.000
[12,] 1 1.000 1.000 1 1.000 1.000
[13,] 1 1.000 1.000 1 1.000 1.000
[14,] 1 1.000 1.000 1 1.000 1.000
[15,] 1 1.000 0.000 1 0.998 0.000
[16,] 0 0.000 0.000 0 0.000 0.000
[17,] 1 1.000 0.718 1 1.000 0.718
[18,] 1 1.000 1.000 1 1.000 1.000
[19,] 1 1.000 0.002 1 1.000 0.002
[20,] 1 1.000 1.000 1 1.000 1.000
[21,] 1 1.000 1.000 1 1.000 1.000
[22,] 1 1.000 1.000 1 1.000 1.000
[23,] 1 1.000 1.000 1 1.000 1.000
[24,] 1 1.000 1.000 1 1.000 1.000
[25,] 1 1.000 1.000 1 1.000 1.000
[26,] 1 1.000 1.000 1 1.000 1.000
[27,] 1 1.000 1.000 1 1.000 1.000
[28,] 1 1.000 1.000 1 1.000 1.000
[29,] 1 1.000 1.000 1 1.000 1.000
[30,] 1 1.000 1.000 1 1.000 1.000
[31,] 1 1.000 1.000 1 1.000 1.000
[32,] 1 1.000 1.000 1 1.000 1.000
[33,] 1 1.000 0.000 1 1.000 0.000
[34,] 0 0.000 0.000 0 0.000 0.000
[35,] 1 1.000 1.000 1 1.000 1.000
[36,] 1 1.000 1.000 1 1.000 1.000
[37,] 1 1.000 1.000 1 1.000 1.000
[38,] 1 1.000 1.000 1 1.000 1.000
[39,] 1 1.000 1.000 1 1.000 1.000
[40,] 1 1.000 1.000 1 1.000 1.000
[41,] 1 1.000 1.000 1 1.000 1.000
[42,] 0 0.000 0.000 0 0.000 0.000
[43,] 1 1.000 1.000 1 1.000 1.000
[44,] 1 1.000 1.000 1 1.000 1.000
[45,] 1 1.000 1.000 1 1.000 1.000
[46,] 1 1.000 1.000 1 1.000 1.000
[47,] 1 1.000 1.000 1 1.000 1.000
[48,] 1 1.000 1.000 1 1.000 1.000
[49,] 1 1.000 1.000 1 1.000 1.000
[50,] 1 1.000 1.000 1 1.000 1.000
[51,] 1 1.000 0.058 1 1.000 0.058
[52,] 1 1.000 1.000 1 1.000 1.000
[53,] 1 1.000 1.000 1 1.000 1.000
[54,] 1 1.000 0.773 1 1.000 0.773
[55,] 1 1.000 1.000 1 1.000 1.000
[56,] 1 1.000 1.000 1 1.000 1.000
[57,] 1 1.000 0.999 1 1.000 0.999
[58,] 1 1.000 0.000 1 1.000 0.000
[59,] 1 1.000 1.000 1 1.000 1.000
[60,] 1 1.000 1.000 1 1.000 1.000
[61,] 0 0.000 0.000 0 0.000 0.000
[62,] 1 1.000 1.000 1 1.000 1.000
[63,] 1 0.611 0.000 0 0.000 0.000
[64,] 1 1.000 1.000 1 1.000 1.000
[65,] 1 1.000 1.000 1 1.000 1.000
[66,] 1 1.000 1.000 1 1.000 1.000
[67,] 1 1.000 1.000 1 1.000 1.000
[68,] 1 1.000 1.000 1 1.000 1.000
[69,] 1 0.786 0.000 0 0.000 0.000
[70,] 1 1.000 1.000 1 1.000 1.000
[71,] 1 1.000 1.000 1 1.000 1.000
[72,] 1 1.000 1.000 1 1.000 1.000
[73,] 1 1.000 1.000 1 1.000 1.000
[74,] 1 1.000 1.000 1 1.000 1.000
[75,] 1 1.000 1.000 1 1.000 1.000
[76,] 1 1.000 1.000 1 1.000 1.000
[77,] 1 1.000 1.000 1 1.000 1.000
[78,] 1 1.000 1.000 1 1.000 1.000
[79,] 1 1.000 1.000 1 1.000 1.000
[80,] 1 1.000 1.000 1 1.000 1.000
[81,] 1 1.000 1.000 1 1.000 1.000
[82,] 1 1.000 0.999 1 1.000 0.999
[83,] 1 1.000 1.000 1 1.000 1.000
[84,] 1 1.000 1.000 1 1.000 1.000
[85,] 1 1.000 1.000 1 1.000 1.000
[86,] 1 1.000 0.000 1 1.000 0.000
[87,] 1 1.000 1.000 1 1.000 1.000
[88,] 1 1.000 0.000 1 1.000 0.000
[89,] 1 1.000 1.000 1 1.000 1.000
[90,] 1 1.000 1.000 1 1.000 1.000
[91,] 1 1.000 1.000 1 1.000 1.000
[92,] 1 1.000 1.000 1 1.000 1.000
[93,] 1 1.000 1.000 1 1.000 1.000
[94,] 1 0.944 0.000 0 0.001 0.000
[95,] 1 1.000 1.000 1 1.000 1.000
[96,] 1 1.000 1.000 1 1.000 1.000
[97,] 1 1.000 1.000 1 1.000 1.000
[98,] 1 1.000 1.000 1 1.000 1.000
[99,] 1 1.000 0.000 1 1.000 0.000
[100,] 1 1.000 1.000 1 1.000 1.000
[101,] 1 1.000 0.000 1 1.000 0.000
[102,] 1 1.000 1.000 1 1.000 1.000
[103,] 1 1.000 1.000 1 1.000 1.000
[104,] 1 1.000 1.000 1 1.000 1.000
[105,] 1 1.000 1.000 1 1.000 1.000
[106,] 1 1.000 0.000 1 0.998 0.000
[107,] 1 1.000 0.000 0 0.317 0.000
[108,] 1 1.000 0.000 1 1.000 0.000
[109,] 1 1.000 0.000 1 0.999 0.000
[110,] 0 0.000 0.000 0 0.000 0.000
[111,] 1 1.000 1.000 1 1.000 1.000
[112,] 1 1.000 1.000 1 1.000 1.000
[113,] 1 1.000 1.000 1 1.000 1.000
[114,] 1 1.000 0.000 1 1.000 0.000
[115,] 1 1.000 0.899 1 1.000 0.899
[116,] 1 1.000 1.000 1 1.000 1.000
[117,] 1 1.000 1.000 1 1.000 1.000
[118,] 0 0.000 0.000 0 0.000 0.000
[119,] 0 0.000 0.000 0 0.000 0.000
[120,] 0 0.028 0.000 0 0.000 0.000
[121,] 1 1.000 1.000 1 1.000 1.000
[122,] 1 1.000 1.000 1 1.000 1.000
[123,] 0 0.000 0.000 0 0.000 0.000
[124,] 1 1.000 1.000 1 1.000 1.000
[125,] 1 1.000 1.000 1 1.000 1.000
[126,] 1 1.000 0.229 1 1.000 0.229
[127,] 1 1.000 1.000 1 1.000 1.000
[128,] 1 1.000 1.000 1 1.000 1.000
[129,] 1 1.000 1.000 1 1.000 1.000
[130,] 1 1.000 0.702 1 1.000 0.702
[131,] 1 1.000 0.000 0 0.357 0.000
[132,] 0 0.000 0.000 0 0.000 0.000
[133,] 1 1.000 1.000 1 1.000 1.000
[134,] 1 1.000 1.000 1 1.000 1.000
[135,] 1 1.000 0.818 1 1.000 0.818
[136,] 1 1.000 0.000 1 0.999 0.000
[137,] 1 1.000 0.000 1 1.000 0.000
[138,] 1 1.000 1.000 1 1.000 1.000
[139,] 1 1.000 1.000 1 1.000 1.000
[140,] 1 1.000 1.000 1 1.000 1.000
[141,] 1 1.000 1.000 1 1.000 1.000
[142,] 1 1.000 1.000 1 1.000 1.000
[143,] 1 1.000 1.000 1 1.000 1.000
[144,] 1 1.000 1.000 1 1.000 1.000
[145,] 1 1.000 1.000 1 1.000 1.000
[146,] 1 1.000 1.000 1 1.000 1.000
[147,] 1 1.000 0.991 1 1.000 0.991
[148,] 1 1.000 1.000 1 1.000 1.000
[149,] 1 1.000 0.000 1 1.000 0.000
[150,] 1 1.000 1.000 1 1.000 1.000
>
>
> try( # testing (tol=0 too small)
+ chk.NN.new.old(cN, cN1, tol=0)
+ )
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error : Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
> ## This used to fail when we use R's instead of BLAS matrix products:
> if(doCheck)
+ chk.NN.new.old(cN, cN1, tol = 4e-15) # seen 1.1e-15 work
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error: Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘L1med-tst.R’ [1s/2s]
Running ‘cov-ex.R’ [1s/1s]
Running the tests in ‘tests/cov-ex.R’ failed.
Complete output:
> library(robustX)
> library(robustbase)
> (newRB <- (packageVersion("robustbase") >= "0.99"))
[1] TRUE
>
> sessionInfo()
R Under development (unstable) (2026-02-14 r89420)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux forky/sid
Matrix products: default
BLAS: /home/hornik/tmp/R.check/r-devel-gcc/Work/build/lib/libRblas.so
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.1; LAPACK version 3.12.0
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Vienna
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] robustbase_0.99-7 robustX_1.2-7
loaded via a namespace (and not attached):
[1] DEoptimR_1.1-4 compiler_4.6.0
> packageDescription("robustX")
Package: robustX
Type: Package
Title: 'eXtra' / 'eXperimental' Functionality for Robust Statistics
Version: 1.2-7
Date: 2023-06-14
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"),
email="maechler@stat.math.ethz.ch", comment = c(ORCID =
"0000-0002-8685-9910")) , person("Werner A.", "Stahel",
role="aut", email="stahel@stat.math.ethz.ch") , person("Rolf",
"Turner", role="ctb", email="r.turner@auckland.ac.nz", comment
= "reclas()") , person("Ueli", "Oetliker", role="ctb", comment
= "original version of BACON() and mvBACON for S+") ,
person("Tobias", "Schoch", role="ctb", comment =
"init.sel=\"V2\" for BACON; fix alpha") )
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Description: Robustness -- 'eXperimental', 'eXtraneous', or
'eXtraordinary' Functionality for Robust Statistics. Hence
methods which are not well established, often related to
methods in package 'robustbase'. Amazingly, 'BACON()',
originally by Billor, Hadi, and Velleman (2000)
<doi:10.1016/S0167-9473(99)00101-2> has become established in
places. The "barrow wheel" `rbwheel()` is from Stahel and
Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.
Imports: grDevices, graphics, stats, utils, robustbase (>= 0.92-3)
Suggests: MASS, lattice, pcaPP
Enhances: ICS
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-06-14 21:41:58 UTC; maechler
Author: Martin Maechler [aut, cre]
(<https://orcid.org/0000-0002-8685-9910>), Werner A. Stahel
[aut], Rolf Turner [ctb] (reclas()), Ueli Oetliker [ctb]
(original version of BACON() and mvBACON for S+), Tobias Schoch
[ctb] (init.sel="V2" for BACON; fix alpha)
Repository: CRAN
Date/Publication: 2023-06-16 07:30:02 UTC
Built: R 4.6.0; ; 2026-02-16 09:58:18 UTC; unix
-- File: /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/robustX/Meta/package.rds
> (ourBLAS <- grepl(print(normalizePath(R.home())),
+ normalizePath(extSoftVersion()[["BLAS"]]), fixed = TRUE))
[1] "/home/hornik/tmp/R.check/r-devel-gcc/Work/build"
[1] TRUE
> ## need extended precision (typically *includes* 64-bit):
> doCheck <- (.Machine$sizeof.longdouble >= 16)
> cat("doCheck (= have long double):", doCheck,"\n")
doCheck (= have long double): TRUE
>
> if(!dev.interactive(orNone=TRUE)) pdf("cov-ex.pdf")
>
> covNN.1 <- robustX:::covNNC1 ## the original definition (2003)
>
> data(iris)
> system.time(cN1 <- covNN.1(iris[-5]))
user system elapsed
0.107 0.014 0.123
> system.time(cN <- covNNC (iris[-5]))# faster indeed
user system elapsed
0.048 0.000 0.054
>
> ## report.and.stop.if.not.all.equal
> report.stopifnot.all.eq <- function(a,b, tol, ...) {
+ call <- sys.call()
+ ae <- all.equal(a,b, tol=tol, ...)
+ call[[1]] <- quote(all.equal)
+ if(!isTRUE(ae))
+ stop(sprintf("Not %s:\n%s\n\n", deparse(call),
+ paste(ae, collapse="\n")),
+ call.=FALSE)
+ ## else
+ TRUE
+ }
>
> UN <- function(L) lapply(L, unname)
>
> chk.NN.new.old <- function(cNew, cNold, tol = 2e-15, tol.1 = 20*tol) {
+ stopifnot(is.list(cNold$innc), length(n.i <- names(cNold$innc)) == 4)
+ cat("classification accordance matrix:\n")
+ print(table(new = cNew $classification,
+ old = cNold$classification))
+ report.stopifnot.all.eq(UN(cNew [1:4]),
+ UN(cNold[1:4]), tol=tol.1) &
+ report.stopifnot.all.eq(cNew $innc[n.i],
+ cNold$innc[n.i], tol=tol)
+ }
>
> summ.NN <- function(cNN, digits = 3) {
+ cbind(class = cNN$classification,
+ pprob = round(cNN$postprob, digits),
+ incc.p= round(cNN$innc$postprob, digits))
+ }
>
> s1 <- summ.NN(cN1)
> ss <- summ.NN(cN)
> if(isTRUE(all.equal(ss, s1))) ss else cbind(ss, s1)
class pprob incc.p class pprob incc.p
[1,] 1 1.000 1.000 1 1.000 1.000
[2,] 1 1.000 1.000 1 1.000 1.000
[3,] 1 1.000 1.000 1 1.000 1.000
[4,] 1 1.000 1.000 1 1.000 1.000
[5,] 1 1.000 1.000 1 1.000 1.000
[6,] 1 1.000 0.171 1 1.000 0.171
[7,] 1 1.000 1.000 1 1.000 1.000
[8,] 1 1.000 1.000 1 1.000 1.000
[9,] 1 1.000 1.000 1 1.000 1.000
[10,] 1 1.000 1.000 1 1.000 1.000
[11,] 1 1.000 1.000 1 1.000 1.000
[12,] 1 1.000 1.000 1 1.000 1.000
[13,] 1 1.000 1.000 1 1.000 1.000
[14,] 1 1.000 1.000 1 1.000 1.000
[15,] 1 1.000 0.000 1 0.998 0.000
[16,] 0 0.000 0.000 0 0.000 0.000
[17,] 1 1.000 0.718 1 1.000 0.718
[18,] 1 1.000 1.000 1 1.000 1.000
[19,] 1 1.000 0.002 1 1.000 0.002
[20,] 1 1.000 1.000 1 1.000 1.000
[21,] 1 1.000 1.000 1 1.000 1.000
[22,] 1 1.000 1.000 1 1.000 1.000
[23,] 1 1.000 1.000 1 1.000 1.000
[24,] 1 1.000 1.000 1 1.000 1.000
[25,] 1 1.000 1.000 1 1.000 1.000
[26,] 1 1.000 1.000 1 1.000 1.000
[27,] 1 1.000 1.000 1 1.000 1.000
[28,] 1 1.000 1.000 1 1.000 1.000
[29,] 1 1.000 1.000 1 1.000 1.000
[30,] 1 1.000 1.000 1 1.000 1.000
[31,] 1 1.000 1.000 1 1.000 1.000
[32,] 1 1.000 1.000 1 1.000 1.000
[33,] 1 1.000 0.000 1 1.000 0.000
[34,] 0 0.000 0.000 0 0.000 0.000
[35,] 1 1.000 1.000 1 1.000 1.000
[36,] 1 1.000 1.000 1 1.000 1.000
[37,] 1 1.000 1.000 1 1.000 1.000
[38,] 1 1.000 1.000 1 1.000 1.000
[39,] 1 1.000 1.000 1 1.000 1.000
[40,] 1 1.000 1.000 1 1.000 1.000
[41,] 1 1.000 1.000 1 1.000 1.000
[42,] 0 0.000 0.000 0 0.000 0.000
[43,] 1 1.000 1.000 1 1.000 1.000
[44,] 1 1.000 1.000 1 1.000 1.000
[45,] 1 1.000 1.000 1 1.000 1.000
[46,] 1 1.000 1.000 1 1.000 1.000
[47,] 1 1.000 1.000 1 1.000 1.000
[48,] 1 1.000 1.000 1 1.000 1.000
[49,] 1 1.000 1.000 1 1.000 1.000
[50,] 1 1.000 1.000 1 1.000 1.000
[51,] 1 1.000 0.058 1 1.000 0.058
[52,] 1 1.000 1.000 1 1.000 1.000
[53,] 1 1.000 1.000 1 1.000 1.000
[54,] 1 1.000 0.773 1 1.000 0.773
[55,] 1 1.000 1.000 1 1.000 1.000
[56,] 1 1.000 1.000 1 1.000 1.000
[57,] 1 1.000 0.999 1 1.000 0.999
[58,] 1 1.000 0.000 1 1.000 0.000
[59,] 1 1.000 1.000 1 1.000 1.000
[60,] 1 1.000 1.000 1 1.000 1.000
[61,] 0 0.000 0.000 0 0.000 0.000
[62,] 1 1.000 1.000 1 1.000 1.000
[63,] 1 0.611 0.000 0 0.000 0.000
[64,] 1 1.000 1.000 1 1.000 1.000
[65,] 1 1.000 1.000 1 1.000 1.000
[66,] 1 1.000 1.000 1 1.000 1.000
[67,] 1 1.000 1.000 1 1.000 1.000
[68,] 1 1.000 1.000 1 1.000 1.000
[69,] 1 0.786 0.000 0 0.000 0.000
[70,] 1 1.000 1.000 1 1.000 1.000
[71,] 1 1.000 1.000 1 1.000 1.000
[72,] 1 1.000 1.000 1 1.000 1.000
[73,] 1 1.000 1.000 1 1.000 1.000
[74,] 1 1.000 1.000 1 1.000 1.000
[75,] 1 1.000 1.000 1 1.000 1.000
[76,] 1 1.000 1.000 1 1.000 1.000
[77,] 1 1.000 1.000 1 1.000 1.000
[78,] 1 1.000 1.000 1 1.000 1.000
[79,] 1 1.000 1.000 1 1.000 1.000
[80,] 1 1.000 1.000 1 1.000 1.000
[81,] 1 1.000 1.000 1 1.000 1.000
[82,] 1 1.000 0.999 1 1.000 0.999
[83,] 1 1.000 1.000 1 1.000 1.000
[84,] 1 1.000 1.000 1 1.000 1.000
[85,] 1 1.000 1.000 1 1.000 1.000
[86,] 1 1.000 0.000 1 1.000 0.000
[87,] 1 1.000 1.000 1 1.000 1.000
[88,] 1 1.000 0.000 1 1.000 0.000
[89,] 1 1.000 1.000 1 1.000 1.000
[90,] 1 1.000 1.000 1 1.000 1.000
[91,] 1 1.000 1.000 1 1.000 1.000
[92,] 1 1.000 1.000 1 1.000 1.000
[93,] 1 1.000 1.000 1 1.000 1.000
[94,] 1 0.944 0.000 0 0.001 0.000
[95,] 1 1.000 1.000 1 1.000 1.000
[96,] 1 1.000 1.000 1 1.000 1.000
[97,] 1 1.000 1.000 1 1.000 1.000
[98,] 1 1.000 1.000 1 1.000 1.000
[99,] 1 1.000 0.000 1 1.000 0.000
[100,] 1 1.000 1.000 1 1.000 1.000
[101,] 1 1.000 0.000 1 1.000 0.000
[102,] 1 1.000 1.000 1 1.000 1.000
[103,] 1 1.000 1.000 1 1.000 1.000
[104,] 1 1.000 1.000 1 1.000 1.000
[105,] 1 1.000 1.000 1 1.000 1.000
[106,] 1 1.000 0.000 1 0.998 0.000
[107,] 1 1.000 0.000 0 0.317 0.000
[108,] 1 1.000 0.000 1 1.000 0.000
[109,] 1 1.000 0.000 1 0.999 0.000
[110,] 0 0.000 0.000 0 0.000 0.000
[111,] 1 1.000 1.000 1 1.000 1.000
[112,] 1 1.000 1.000 1 1.000 1.000
[113,] 1 1.000 1.000 1 1.000 1.000
[114,] 1 1.000 0.000 1 1.000 0.000
[115,] 1 1.000 0.899 1 1.000 0.899
[116,] 1 1.000 1.000 1 1.000 1.000
[117,] 1 1.000 1.000 1 1.000 1.000
[118,] 0 0.000 0.000 0 0.000 0.000
[119,] 0 0.000 0.000 0 0.000 0.000
[120,] 0 0.028 0.000 0 0.000 0.000
[121,] 1 1.000 1.000 1 1.000 1.000
[122,] 1 1.000 1.000 1 1.000 1.000
[123,] 0 0.000 0.000 0 0.000 0.000
[124,] 1 1.000 1.000 1 1.000 1.000
[125,] 1 1.000 1.000 1 1.000 1.000
[126,] 1 1.000 0.229 1 1.000 0.229
[127,] 1 1.000 1.000 1 1.000 1.000
[128,] 1 1.000 1.000 1 1.000 1.000
[129,] 1 1.000 1.000 1 1.000 1.000
[130,] 1 1.000 0.702 1 1.000 0.702
[131,] 1 1.000 0.000 0 0.357 0.000
[132,] 0 0.000 0.000 0 0.000 0.000
[133,] 1 1.000 1.000 1 1.000 1.000
[134,] 1 1.000 1.000 1 1.000 1.000
[135,] 1 1.000 0.818 1 1.000 0.818
[136,] 1 1.000 0.000 1 0.999 0.000
[137,] 1 1.000 0.000 1 1.000 0.000
[138,] 1 1.000 1.000 1 1.000 1.000
[139,] 1 1.000 1.000 1 1.000 1.000
[140,] 1 1.000 1.000 1 1.000 1.000
[141,] 1 1.000 1.000 1 1.000 1.000
[142,] 1 1.000 1.000 1 1.000 1.000
[143,] 1 1.000 1.000 1 1.000 1.000
[144,] 1 1.000 1.000 1 1.000 1.000
[145,] 1 1.000 1.000 1 1.000 1.000
[146,] 1 1.000 1.000 1 1.000 1.000
[147,] 1 1.000 0.991 1 1.000 0.991
[148,] 1 1.000 1.000 1 1.000 1.000
[149,] 1 1.000 0.000 1 1.000 0.000
[150,] 1 1.000 1.000 1 1.000 1.000
>
>
> try( # testing (tol=0 too small)
+ chk.NN.new.old(cN, cN1, tol=0)
+ )
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error : Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
> ## This used to fail when we use R's instead of BLAS matrix products:
> if(doCheck)
+ chk.NN.new.old(cN, cN1, tol = 4e-15) # seen 1.1e-15 work
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error: Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘L1med-tst.R’
Running ‘cov-ex.R’
Running the tests in ‘tests/cov-ex.R’ failed.
Complete output:
> library(robustX)
> library(robustbase)
> (newRB <- (packageVersion("robustbase") >= "0.99"))
[1] TRUE
>
> sessionInfo()
R Under development (unstable) (2026-02-12 r89409)
Platform: x86_64-pc-linux-gnu
Running under: Fedora Linux 42 (Workstation Edition)
Matrix products: default
BLAS: /data/gannet/ripley/R/R-clang/lib/libRblas.so
LAPACK: /data/gannet/ripley/R/R-clang/lib/libRlapack.so; LAPACK version 3.12.1
locale:
[1] LC_CTYPE=en_GB.utf8 LC_NUMERIC=C
[3] LC_TIME=en_GB.UTF-8 LC_COLLATE=C
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/London
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] robustbase_0.99-7 robustX_1.2-7
loaded via a namespace (and not attached):
[1] DEoptimR_1.1-4 compiler_4.6.0
> packageDescription("robustX")
Package: robustX
Type: Package
Title: 'eXtra' / 'eXperimental' Functionality for Robust Statistics
Version: 1.2-7
Date: 2023-06-14
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"),
email="maechler@stat.math.ethz.ch", comment = c(ORCID =
"0000-0002-8685-9910")) , person("Werner A.", "Stahel",
role="aut", email="stahel@stat.math.ethz.ch") , person("Rolf",
"Turner", role="ctb", email="r.turner@auckland.ac.nz", comment
= "reclas()") , person("Ueli", "Oetliker", role="ctb", comment
= "original version of BACON() and mvBACON for S+") ,
person("Tobias", "Schoch", role="ctb", comment =
"init.sel=\"V2\" for BACON; fix alpha") )
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Description: Robustness -- 'eXperimental', 'eXtraneous', or
'eXtraordinary' Functionality for Robust Statistics. Hence
methods which are not well established, often related to
methods in package 'robustbase'. Amazingly, 'BACON()',
originally by Billor, Hadi, and Velleman (2000)
<doi:10.1016/S0167-9473(99)00101-2> has become established in
places. The "barrow wheel" `rbwheel()` is from Stahel and
Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.
Imports: grDevices, graphics, stats, utils, robustbase (>= 0.92-3)
Suggests: MASS, lattice, pcaPP
Enhances: ICS
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-06-14 21:41:58 UTC; maechler
Author: Martin Maechler [aut, cre]
(<https://orcid.org/0000-0002-8685-9910>), Werner A. Stahel
[aut], Rolf Turner [ctb] (reclas()), Ueli Oetliker [ctb]
(original version of BACON() and mvBACON for S+), Tobias Schoch
[ctb] (init.sel="V2" for BACON; fix alpha)
Repository: CRAN
Date/Publication: 2023-06-16 07:30:02 UTC
Built: R 4.6.0; ; 2026-02-16 04:33:22 UTC; unix
-- File: /data/gannet/ripley/R/packages/tests-clang/robustX.Rcheck/robustX/Meta/package.rds
> (ourBLAS <- grepl(print(normalizePath(R.home())),
+ normalizePath(extSoftVersion()[["BLAS"]]), fixed = TRUE))
[1] "/data/gannet/ripley/R/R-clang"
[1] TRUE
> ## need extended precision (typically *includes* 64-bit):
> doCheck <- (.Machine$sizeof.longdouble >= 16)
> cat("doCheck (= have long double):", doCheck,"\n")
doCheck (= have long double): TRUE
>
> if(!dev.interactive(orNone=TRUE)) pdf("cov-ex.pdf")
>
> covNN.1 <- robustX:::covNNC1 ## the original definition (2003)
>
> data(iris)
> system.time(cN1 <- covNN.1(iris[-5]))
user system elapsed
0.306 0.028 0.353
> system.time(cN <- covNNC (iris[-5]))# faster indeed
user system elapsed
0.150 0.000 0.318
>
> ## report.and.stop.if.not.all.equal
> report.stopifnot.all.eq <- function(a,b, tol, ...) {
+ call <- sys.call()
+ ae <- all.equal(a,b, tol=tol, ...)
+ call[[1]] <- quote(all.equal)
+ if(!isTRUE(ae))
+ stop(sprintf("Not %s:\n%s\n\n", deparse(call),
+ paste(ae, collapse="\n")),
+ call.=FALSE)
+ ## else
+ TRUE
+ }
>
> UN <- function(L) lapply(L, unname)
>
> chk.NN.new.old <- function(cNew, cNold, tol = 2e-15, tol.1 = 20*tol) {
+ stopifnot(is.list(cNold$innc), length(n.i <- names(cNold$innc)) == 4)
+ cat("classification accordance matrix:\n")
+ print(table(new = cNew $classification,
+ old = cNold$classification))
+ report.stopifnot.all.eq(UN(cNew [1:4]),
+ UN(cNold[1:4]), tol=tol.1) &
+ report.stopifnot.all.eq(cNew $innc[n.i],
+ cNold$innc[n.i], tol=tol)
+ }
>
> summ.NN <- function(cNN, digits = 3) {
+ cbind(class = cNN$classification,
+ pprob = round(cNN$postprob, digits),
+ incc.p= round(cNN$innc$postprob, digits))
+ }
>
> s1 <- summ.NN(cN1)
> ss <- summ.NN(cN)
> if(isTRUE(all.equal(ss, s1))) ss else cbind(ss, s1)
class pprob incc.p class pprob incc.p
[1,] 1 1.000 1.000 1 1.000 1.000
[2,] 1 1.000 1.000 1 1.000 1.000
[3,] 1 1.000 1.000 1 1.000 1.000
[4,] 1 1.000 1.000 1 1.000 1.000
[5,] 1 1.000 1.000 1 1.000 1.000
[6,] 1 1.000 0.171 1 1.000 0.171
[7,] 1 1.000 1.000 1 1.000 1.000
[8,] 1 1.000 1.000 1 1.000 1.000
[9,] 1 1.000 1.000 1 1.000 1.000
[10,] 1 1.000 1.000 1 1.000 1.000
[11,] 1 1.000 1.000 1 1.000 1.000
[12,] 1 1.000 1.000 1 1.000 1.000
[13,] 1 1.000 1.000 1 1.000 1.000
[14,] 1 1.000 1.000 1 1.000 1.000
[15,] 1 1.000 0.000 1 0.998 0.000
[16,] 0 0.000 0.000 0 0.000 0.000
[17,] 1 1.000 0.718 1 1.000 0.718
[18,] 1 1.000 1.000 1 1.000 1.000
[19,] 1 1.000 0.002 1 1.000 0.002
[20,] 1 1.000 1.000 1 1.000 1.000
[21,] 1 1.000 1.000 1 1.000 1.000
[22,] 1 1.000 1.000 1 1.000 1.000
[23,] 1 1.000 1.000 1 1.000 1.000
[24,] 1 1.000 1.000 1 1.000 1.000
[25,] 1 1.000 1.000 1 1.000 1.000
[26,] 1 1.000 1.000 1 1.000 1.000
[27,] 1 1.000 1.000 1 1.000 1.000
[28,] 1 1.000 1.000 1 1.000 1.000
[29,] 1 1.000 1.000 1 1.000 1.000
[30,] 1 1.000 1.000 1 1.000 1.000
[31,] 1 1.000 1.000 1 1.000 1.000
[32,] 1 1.000 1.000 1 1.000 1.000
[33,] 1 1.000 0.000 1 1.000 0.000
[34,] 0 0.000 0.000 0 0.000 0.000
[35,] 1 1.000 1.000 1 1.000 1.000
[36,] 1 1.000 1.000 1 1.000 1.000
[37,] 1 1.000 1.000 1 1.000 1.000
[38,] 1 1.000 1.000 1 1.000 1.000
[39,] 1 1.000 1.000 1 1.000 1.000
[40,] 1 1.000 1.000 1 1.000 1.000
[41,] 1 1.000 1.000 1 1.000 1.000
[42,] 0 0.000 0.000 0 0.000 0.000
[43,] 1 1.000 1.000 1 1.000 1.000
[44,] 1 1.000 1.000 1 1.000 1.000
[45,] 1 1.000 1.000 1 1.000 1.000
[46,] 1 1.000 1.000 1 1.000 1.000
[47,] 1 1.000 1.000 1 1.000 1.000
[48,] 1 1.000 1.000 1 1.000 1.000
[49,] 1 1.000 1.000 1 1.000 1.000
[50,] 1 1.000 1.000 1 1.000 1.000
[51,] 1 1.000 0.058 1 1.000 0.058
[52,] 1 1.000 1.000 1 1.000 1.000
[53,] 1 1.000 1.000 1 1.000 1.000
[54,] 1 1.000 0.773 1 1.000 0.773
[55,] 1 1.000 1.000 1 1.000 1.000
[56,] 1 1.000 1.000 1 1.000 1.000
[57,] 1 1.000 0.999 1 1.000 0.999
[58,] 1 1.000 0.000 1 1.000 0.000
[59,] 1 1.000 1.000 1 1.000 1.000
[60,] 1 1.000 1.000 1 1.000 1.000
[61,] 0 0.000 0.000 0 0.000 0.000
[62,] 1 1.000 1.000 1 1.000 1.000
[63,] 1 0.611 0.000 0 0.000 0.000
[64,] 1 1.000 1.000 1 1.000 1.000
[65,] 1 1.000 1.000 1 1.000 1.000
[66,] 1 1.000 1.000 1 1.000 1.000
[67,] 1 1.000 1.000 1 1.000 1.000
[68,] 1 1.000 1.000 1 1.000 1.000
[69,] 1 0.786 0.000 0 0.000 0.000
[70,] 1 1.000 1.000 1 1.000 1.000
[71,] 1 1.000 1.000 1 1.000 1.000
[72,] 1 1.000 1.000 1 1.000 1.000
[73,] 1 1.000 1.000 1 1.000 1.000
[74,] 1 1.000 1.000 1 1.000 1.000
[75,] 1 1.000 1.000 1 1.000 1.000
[76,] 1 1.000 1.000 1 1.000 1.000
[77,] 1 1.000 1.000 1 1.000 1.000
[78,] 1 1.000 1.000 1 1.000 1.000
[79,] 1 1.000 1.000 1 1.000 1.000
[80,] 1 1.000 1.000 1 1.000 1.000
[81,] 1 1.000 1.000 1 1.000 1.000
[82,] 1 1.000 0.999 1 1.000 0.999
[83,] 1 1.000 1.000 1 1.000 1.000
[84,] 1 1.000 1.000 1 1.000 1.000
[85,] 1 1.000 1.000 1 1.000 1.000
[86,] 1 1.000 0.000 1 1.000 0.000
[87,] 1 1.000 1.000 1 1.000 1.000
[88,] 1 1.000 0.000 1 1.000 0.000
[89,] 1 1.000 1.000 1 1.000 1.000
[90,] 1 1.000 1.000 1 1.000 1.000
[91,] 1 1.000 1.000 1 1.000 1.000
[92,] 1 1.000 1.000 1 1.000 1.000
[93,] 1 1.000 1.000 1 1.000 1.000
[94,] 1 0.944 0.000 0 0.001 0.000
[95,] 1 1.000 1.000 1 1.000 1.000
[96,] 1 1.000 1.000 1 1.000 1.000
[97,] 1 1.000 1.000 1 1.000 1.000
[98,] 1 1.000 1.000 1 1.000 1.000
[99,] 1 1.000 0.000 1 1.000 0.000
[100,] 1 1.000 1.000 1 1.000 1.000
[101,] 1 1.000 0.000 1 1.000 0.000
[102,] 1 1.000 1.000 1 1.000 1.000
[103,] 1 1.000 1.000 1 1.000 1.000
[104,] 1 1.000 1.000 1 1.000 1.000
[105,] 1 1.000 1.000 1 1.000 1.000
[106,] 1 1.000 0.000 1 0.998 0.000
[107,] 1 1.000 0.000 0 0.317 0.000
[108,] 1 1.000 0.000 1 1.000 0.000
[109,] 1 1.000 0.000 1 0.999 0.000
[110,] 0 0.000 0.000 0 0.000 0.000
[111,] 1 1.000 1.000 1 1.000 1.000
[112,] 1 1.000 1.000 1 1.000 1.000
[113,] 1 1.000 1.000 1 1.000 1.000
[114,] 1 1.000 0.000 1 1.000 0.000
[115,] 1 1.000 0.899 1 1.000 0.899
[116,] 1 1.000 1.000 1 1.000 1.000
[117,] 1 1.000 1.000 1 1.000 1.000
[118,] 0 0.000 0.000 0 0.000 0.000
[119,] 0 0.000 0.000 0 0.000 0.000
[120,] 0 0.028 0.000 0 0.000 0.000
[121,] 1 1.000 1.000 1 1.000 1.000
[122,] 1 1.000 1.000 1 1.000 1.000
[123,] 0 0.000 0.000 0 0.000 0.000
[124,] 1 1.000 1.000 1 1.000 1.000
[125,] 1 1.000 1.000 1 1.000 1.000
[126,] 1 1.000 0.229 1 1.000 0.229
[127,] 1 1.000 1.000 1 1.000 1.000
[128,] 1 1.000 1.000 1 1.000 1.000
[129,] 1 1.000 1.000 1 1.000 1.000
[130,] 1 1.000 0.702 1 1.000 0.702
[131,] 1 1.000 0.000 0 0.357 0.000
[132,] 0 0.000 0.000 0 0.000 0.000
[133,] 1 1.000 1.000 1 1.000 1.000
[134,] 1 1.000 1.000 1 1.000 1.000
[135,] 1 1.000 0.818 1 1.000 0.818
[136,] 1 1.000 0.000 1 0.999 0.000
[137,] 1 1.000 0.000 1 1.000 0.000
[138,] 1 1.000 1.000 1 1.000 1.000
[139,] 1 1.000 1.000 1 1.000 1.000
[140,] 1 1.000 1.000 1 1.000 1.000
[141,] 1 1.000 1.000 1 1.000 1.000
[142,] 1 1.000 1.000 1 1.000 1.000
[143,] 1 1.000 1.000 1 1.000 1.000
[144,] 1 1.000 1.000 1 1.000 1.000
[145,] 1 1.000 1.000 1 1.000 1.000
[146,] 1 1.000 1.000 1 1.000 1.000
[147,] 1 1.000 0.991 1 1.000 0.991
[148,] 1 1.000 1.000 1 1.000 1.000
[149,] 1 1.000 0.000 1 1.000 0.000
[150,] 1 1.000 1.000 1 1.000 1.000
>
>
> try( # testing (tol=0 too small)
+ chk.NN.new.old(cN, cN1, tol=0)
+ )
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error : Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
> ## This used to fail when we use R's instead of BLAS matrix products:
> if(doCheck)
+ chk.NN.new.old(cN, cN1, tol = 4e-15) # seen 1.1e-15 work
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error: Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.2-7
Check: tests
Result: ERROR
Running ‘L1med-tst.R’
Running ‘cov-ex.R’
Running the tests in ‘tests/cov-ex.R’ failed.
Complete output:
> library(robustX)
> library(robustbase)
> (newRB <- (packageVersion("robustbase") >= "0.99"))
[1] TRUE
>
> sessionInfo()
R Under development (unstable) (2026-02-07 r89380)
Platform: x86_64-pc-linux-gnu
Running under: Fedora Linux 42 (Workstation Edition)
Matrix products: default
BLAS: /data/gannet/ripley/R/R-devel/lib/libRblas.so
LAPACK: /usr/lib64/liblapack.so.3.12.0 LAPACK version 3.12.0
locale:
[1] LC_CTYPE=en_GB.utf8 LC_NUMERIC=C
[3] LC_TIME=en_GB.UTF-8 LC_COLLATE=C
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/London
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] robustbase_0.99-7 robustX_1.2-7
loaded via a namespace (and not attached):
[1] DEoptimR_1.1-4 compiler_4.6.0
> packageDescription("robustX")
Package: robustX
Type: Package
Title: 'eXtra' / 'eXperimental' Functionality for Robust Statistics
Version: 1.2-7
Date: 2023-06-14
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"),
email="maechler@stat.math.ethz.ch", comment = c(ORCID =
"0000-0002-8685-9910")) , person("Werner A.", "Stahel",
role="aut", email="stahel@stat.math.ethz.ch") , person("Rolf",
"Turner", role="ctb", email="r.turner@auckland.ac.nz", comment
= "reclas()") , person("Ueli", "Oetliker", role="ctb", comment
= "original version of BACON() and mvBACON for S+") ,
person("Tobias", "Schoch", role="ctb", comment =
"init.sel=\"V2\" for BACON; fix alpha") )
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Description: Robustness -- 'eXperimental', 'eXtraneous', or
'eXtraordinary' Functionality for Robust Statistics. Hence
methods which are not well established, often related to
methods in package 'robustbase'. Amazingly, 'BACON()',
originally by Billor, Hadi, and Velleman (2000)
<doi:10.1016/S0167-9473(99)00101-2> has become established in
places. The "barrow wheel" `rbwheel()` is from Stahel and
Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.
Imports: grDevices, graphics, stats, utils, robustbase (>= 0.92-3)
Suggests: MASS, lattice, pcaPP
Enhances: ICS
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-06-14 21:41:58 UTC; maechler
Author: Martin Maechler [aut, cre]
(<https://orcid.org/0000-0002-8685-9910>), Werner A. Stahel
[aut], Rolf Turner [ctb] (reclas()), Ueli Oetliker [ctb]
(original version of BACON() and mvBACON for S+), Tobias Schoch
[ctb] (init.sel="V2" for BACON; fix alpha)
Repository: CRAN
Date/Publication: 2023-06-16 07:30:02 UTC
Built: R 4.6.0; ; 2026-02-09 21:10:39 UTC; unix
-- File: /data/gannet/ripley/R/packages/tests-devel/robustX.Rcheck/robustX/Meta/package.rds
> (ourBLAS <- grepl(print(normalizePath(R.home())),
+ normalizePath(extSoftVersion()[["BLAS"]]), fixed = TRUE))
[1] "/data/gannet/ripley/R/R-devel"
[1] TRUE
> ## need extended precision (typically *includes* 64-bit):
> doCheck <- (.Machine$sizeof.longdouble >= 16)
> cat("doCheck (= have long double):", doCheck,"\n")
doCheck (= have long double): TRUE
>
> if(!dev.interactive(orNone=TRUE)) pdf("cov-ex.pdf")
>
> covNN.1 <- robustX:::covNNC1 ## the original definition (2003)
>
> data(iris)
> system.time(cN1 <- covNN.1(iris[-5]))
user system elapsed
0.289 0.022 0.315
> system.time(cN <- covNNC (iris[-5]))# faster indeed
user system elapsed
0.136 0.000 0.138
>
> ## report.and.stop.if.not.all.equal
> report.stopifnot.all.eq <- function(a,b, tol, ...) {
+ call <- sys.call()
+ ae <- all.equal(a,b, tol=tol, ...)
+ call[[1]] <- quote(all.equal)
+ if(!isTRUE(ae))
+ stop(sprintf("Not %s:\n%s\n\n", deparse(call),
+ paste(ae, collapse="\n")),
+ call.=FALSE)
+ ## else
+ TRUE
+ }
>
> UN <- function(L) lapply(L, unname)
>
> chk.NN.new.old <- function(cNew, cNold, tol = 2e-15, tol.1 = 20*tol) {
+ stopifnot(is.list(cNold$innc), length(n.i <- names(cNold$innc)) == 4)
+ cat("classification accordance matrix:\n")
+ print(table(new = cNew $classification,
+ old = cNold$classification))
+ report.stopifnot.all.eq(UN(cNew [1:4]),
+ UN(cNold[1:4]), tol=tol.1) &
+ report.stopifnot.all.eq(cNew $innc[n.i],
+ cNold$innc[n.i], tol=tol)
+ }
>
> summ.NN <- function(cNN, digits = 3) {
+ cbind(class = cNN$classification,
+ pprob = round(cNN$postprob, digits),
+ incc.p= round(cNN$innc$postprob, digits))
+ }
>
> s1 <- summ.NN(cN1)
> ss <- summ.NN(cN)
> if(isTRUE(all.equal(ss, s1))) ss else cbind(ss, s1)
class pprob incc.p class pprob incc.p
[1,] 1 1.000 1.000 1 1.000 1.000
[2,] 1 1.000 1.000 1 1.000 1.000
[3,] 1 1.000 1.000 1 1.000 1.000
[4,] 1 1.000 1.000 1 1.000 1.000
[5,] 1 1.000 1.000 1 1.000 1.000
[6,] 1 1.000 0.171 1 1.000 0.171
[7,] 1 1.000 1.000 1 1.000 1.000
[8,] 1 1.000 1.000 1 1.000 1.000
[9,] 1 1.000 1.000 1 1.000 1.000
[10,] 1 1.000 1.000 1 1.000 1.000
[11,] 1 1.000 1.000 1 1.000 1.000
[12,] 1 1.000 1.000 1 1.000 1.000
[13,] 1 1.000 1.000 1 1.000 1.000
[14,] 1 1.000 1.000 1 1.000 1.000
[15,] 1 1.000 0.000 1 0.998 0.000
[16,] 0 0.000 0.000 0 0.000 0.000
[17,] 1 1.000 0.718 1 1.000 0.718
[18,] 1 1.000 1.000 1 1.000 1.000
[19,] 1 1.000 0.002 1 1.000 0.002
[20,] 1 1.000 1.000 1 1.000 1.000
[21,] 1 1.000 1.000 1 1.000 1.000
[22,] 1 1.000 1.000 1 1.000 1.000
[23,] 1 1.000 1.000 1 1.000 1.000
[24,] 1 1.000 1.000 1 1.000 1.000
[25,] 1 1.000 1.000 1 1.000 1.000
[26,] 1 1.000 1.000 1 1.000 1.000
[27,] 1 1.000 1.000 1 1.000 1.000
[28,] 1 1.000 1.000 1 1.000 1.000
[29,] 1 1.000 1.000 1 1.000 1.000
[30,] 1 1.000 1.000 1 1.000 1.000
[31,] 1 1.000 1.000 1 1.000 1.000
[32,] 1 1.000 1.000 1 1.000 1.000
[33,] 1 1.000 0.000 1 1.000 0.000
[34,] 0 0.000 0.000 0 0.000 0.000
[35,] 1 1.000 1.000 1 1.000 1.000
[36,] 1 1.000 1.000 1 1.000 1.000
[37,] 1 1.000 1.000 1 1.000 1.000
[38,] 1 1.000 1.000 1 1.000 1.000
[39,] 1 1.000 1.000 1 1.000 1.000
[40,] 1 1.000 1.000 1 1.000 1.000
[41,] 1 1.000 1.000 1 1.000 1.000
[42,] 0 0.000 0.000 0 0.000 0.000
[43,] 1 1.000 1.000 1 1.000 1.000
[44,] 1 1.000 1.000 1 1.000 1.000
[45,] 1 1.000 1.000 1 1.000 1.000
[46,] 1 1.000 1.000 1 1.000 1.000
[47,] 1 1.000 1.000 1 1.000 1.000
[48,] 1 1.000 1.000 1 1.000 1.000
[49,] 1 1.000 1.000 1 1.000 1.000
[50,] 1 1.000 1.000 1 1.000 1.000
[51,] 1 1.000 0.058 1 1.000 0.058
[52,] 1 1.000 1.000 1 1.000 1.000
[53,] 1 1.000 1.000 1 1.000 1.000
[54,] 1 1.000 0.773 1 1.000 0.773
[55,] 1 1.000 1.000 1 1.000 1.000
[56,] 1 1.000 1.000 1 1.000 1.000
[57,] 1 1.000 0.999 1 1.000 0.999
[58,] 1 1.000 0.000 1 1.000 0.000
[59,] 1 1.000 1.000 1 1.000 1.000
[60,] 1 1.000 1.000 1 1.000 1.000
[61,] 0 0.000 0.000 0 0.000 0.000
[62,] 1 1.000 1.000 1 1.000 1.000
[63,] 1 0.611 0.000 0 0.000 0.000
[64,] 1 1.000 1.000 1 1.000 1.000
[65,] 1 1.000 1.000 1 1.000 1.000
[66,] 1 1.000 1.000 1 1.000 1.000
[67,] 1 1.000 1.000 1 1.000 1.000
[68,] 1 1.000 1.000 1 1.000 1.000
[69,] 1 0.786 0.000 0 0.000 0.000
[70,] 1 1.000 1.000 1 1.000 1.000
[71,] 1 1.000 1.000 1 1.000 1.000
[72,] 1 1.000 1.000 1 1.000 1.000
[73,] 1 1.000 1.000 1 1.000 1.000
[74,] 1 1.000 1.000 1 1.000 1.000
[75,] 1 1.000 1.000 1 1.000 1.000
[76,] 1 1.000 1.000 1 1.000 1.000
[77,] 1 1.000 1.000 1 1.000 1.000
[78,] 1 1.000 1.000 1 1.000 1.000
[79,] 1 1.000 1.000 1 1.000 1.000
[80,] 1 1.000 1.000 1 1.000 1.000
[81,] 1 1.000 1.000 1 1.000 1.000
[82,] 1 1.000 0.999 1 1.000 0.999
[83,] 1 1.000 1.000 1 1.000 1.000
[84,] 1 1.000 1.000 1 1.000 1.000
[85,] 1 1.000 1.000 1 1.000 1.000
[86,] 1 1.000 0.000 1 1.000 0.000
[87,] 1 1.000 1.000 1 1.000 1.000
[88,] 1 1.000 0.000 1 1.000 0.000
[89,] 1 1.000 1.000 1 1.000 1.000
[90,] 1 1.000 1.000 1 1.000 1.000
[91,] 1 1.000 1.000 1 1.000 1.000
[92,] 1 1.000 1.000 1 1.000 1.000
[93,] 1 1.000 1.000 1 1.000 1.000
[94,] 1 0.944 0.000 0 0.001 0.000
[95,] 1 1.000 1.000 1 1.000 1.000
[96,] 1 1.000 1.000 1 1.000 1.000
[97,] 1 1.000 1.000 1 1.000 1.000
[98,] 1 1.000 1.000 1 1.000 1.000
[99,] 1 1.000 0.000 1 1.000 0.000
[100,] 1 1.000 1.000 1 1.000 1.000
[101,] 1 1.000 0.000 1 1.000 0.000
[102,] 1 1.000 1.000 1 1.000 1.000
[103,] 1 1.000 1.000 1 1.000 1.000
[104,] 1 1.000 1.000 1 1.000 1.000
[105,] 1 1.000 1.000 1 1.000 1.000
[106,] 1 1.000 0.000 1 0.998 0.000
[107,] 1 1.000 0.000 0 0.317 0.000
[108,] 1 1.000 0.000 1 1.000 0.000
[109,] 1 1.000 0.000 1 0.999 0.000
[110,] 0 0.000 0.000 0 0.000 0.000
[111,] 1 1.000 1.000 1 1.000 1.000
[112,] 1 1.000 1.000 1 1.000 1.000
[113,] 1 1.000 1.000 1 1.000 1.000
[114,] 1 1.000 0.000 1 1.000 0.000
[115,] 1 1.000 0.899 1 1.000 0.899
[116,] 1 1.000 1.000 1 1.000 1.000
[117,] 1 1.000 1.000 1 1.000 1.000
[118,] 0 0.000 0.000 0 0.000 0.000
[119,] 0 0.000 0.000 0 0.000 0.000
[120,] 0 0.028 0.000 0 0.000 0.000
[121,] 1 1.000 1.000 1 1.000 1.000
[122,] 1 1.000 1.000 1 1.000 1.000
[123,] 0 0.000 0.000 0 0.000 0.000
[124,] 1 1.000 1.000 1 1.000 1.000
[125,] 1 1.000 1.000 1 1.000 1.000
[126,] 1 1.000 0.229 1 1.000 0.229
[127,] 1 1.000 1.000 1 1.000 1.000
[128,] 1 1.000 1.000 1 1.000 1.000
[129,] 1 1.000 1.000 1 1.000 1.000
[130,] 1 1.000 0.702 1 1.000 0.702
[131,] 1 1.000 0.000 0 0.357 0.000
[132,] 0 0.000 0.000 0 0.000 0.000
[133,] 1 1.000 1.000 1 1.000 1.000
[134,] 1 1.000 1.000 1 1.000 1.000
[135,] 1 1.000 0.818 1 1.000 0.818
[136,] 1 1.000 0.000 1 0.999 0.000
[137,] 1 1.000 0.000 1 1.000 0.000
[138,] 1 1.000 1.000 1 1.000 1.000
[139,] 1 1.000 1.000 1 1.000 1.000
[140,] 1 1.000 1.000 1 1.000 1.000
[141,] 1 1.000 1.000 1 1.000 1.000
[142,] 1 1.000 1.000 1 1.000 1.000
[143,] 1 1.000 1.000 1 1.000 1.000
[144,] 1 1.000 1.000 1 1.000 1.000
[145,] 1 1.000 1.000 1 1.000 1.000
[146,] 1 1.000 1.000 1 1.000 1.000
[147,] 1 1.000 0.991 1 1.000 0.991
[148,] 1 1.000 1.000 1 1.000 1.000
[149,] 1 1.000 0.000 1 1.000 0.000
[150,] 1 1.000 1.000 1 1.000 1.000
>
>
> try( # testing (tol=0 too small)
+ chk.NN.new.old(cN, cN1, tol=0)
+ )
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error : Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
> ## This used to fail when we use R's instead of BLAS matrix products:
> if(doCheck)
+ chk.NN.new.old(cN, cN1, tol = 4e-15) # seen 1.1e-15 work
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error: Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.2-7
Check: tests
Result: ERROR
Running 'L1med-tst.R' [1s]
Running 'cov-ex.R' [1s]
Running the tests in 'tests/cov-ex.R' failed.
Complete output:
> library(robustX)
> library(robustbase)
> (newRB <- (packageVersion("robustbase") >= "0.99"))
[1] TRUE
>
> sessionInfo()
R Under development (unstable) (2026-02-13 r89414 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows Server 2022 x64 (build 20348)
Matrix products: default
LAPACK version 3.12.1
locale:
[1] LC_COLLATE=C LC_CTYPE=German_Germany.utf8
[3] LC_MONETARY=C LC_NUMERIC=C
[5] LC_TIME=C
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] robustbase_0.99-7 robustX_1.2-7
loaded via a namespace (and not attached):
[1] DEoptimR_1.1-4 compiler_4.6.0
> packageDescription("robustX")
Package: robustX
Type: Package
Title: 'eXtra' / 'eXperimental' Functionality for Robust Statistics
Version: 1.2-7
Date: 2023-06-14
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"),
email="maechler@stat.math.ethz.ch", comment = c(ORCID =
"0000-0002-8685-9910")) , person("Werner A.", "Stahel",
role="aut", email="stahel@stat.math.ethz.ch") , person("Rolf",
"Turner", role="ctb", email="r.turner@auckland.ac.nz", comment
= "reclas()") , person("Ueli", "Oetliker", role="ctb", comment
= "original version of BACON() and mvBACON for S+") ,
person("Tobias", "Schoch", role="ctb", comment =
"init.sel=\"V2\" for BACON; fix alpha") )
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Description: Robustness -- 'eXperimental', 'eXtraneous', or
'eXtraordinary' Functionality for Robust Statistics. Hence
methods which are not well established, often related to
methods in package 'robustbase'. Amazingly, 'BACON()',
originally by Billor, Hadi, and Velleman (2000)
<doi:10.1016/S0167-9473(99)00101-2> has become established in
places. The "barrow wheel" `rbwheel()` is from Stahel and
Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.
Imports: grDevices, graphics, stats, utils, robustbase (>= 0.92-3)
Suggests: MASS, lattice, pcaPP
Enhances: ICS
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-06-14 21:41:58 UTC; maechler
Author: Martin Maechler [aut, cre]
(<https://orcid.org/0000-0002-8685-9910>), Werner A. Stahel
[aut], Rolf Turner [ctb] (reclas()), Ueli Oetliker [ctb]
(original version of BACON() and mvBACON for S+), Tobias Schoch
[ctb] (init.sel="V2" for BACON; fix alpha)
Repository: CRAN
Date/Publication: 2023-06-16 07:30:02 UTC
Built: R 4.6.0; ; 2026-02-14 02:19:01 UTC; windows
-- File: D:/RCompile/CRANpkg/lib/4.6/robustX/Meta/package.rds
> (ourBLAS <- grepl(print(normalizePath(R.home())),
+ normalizePath(extSoftVersion()[["BLAS"]]), fixed = TRUE))
[1] "D:\\RCompile\\recent\\R"
[1] FALSE
Warning message:
In normalizePath(path.expand(path), winslash, mustWork) :
path[1]="": Das System kann den angegebenen Pfad nicht finden
> ## need extended precision (typically *includes* 64-bit):
> doCheck <- (.Machine$sizeof.longdouble >= 16)
> cat("doCheck (= have long double):", doCheck,"\n")
doCheck (= have long double): TRUE
>
> if(!dev.interactive(orNone=TRUE)) pdf("cov-ex.pdf")
>
> covNN.1 <- robustX:::covNNC1 ## the original definition (2003)
>
> data(iris)
> system.time(cN1 <- covNN.1(iris[-5]))
user system elapsed
0.14 0.00 0.14
> system.time(cN <- covNNC (iris[-5]))# faster indeed
user system elapsed
0.06 0.01 0.08
>
> ## report.and.stop.if.not.all.equal
> report.stopifnot.all.eq <- function(a,b, tol, ...) {
+ call <- sys.call()
+ ae <- all.equal(a,b, tol=tol, ...)
+ call[[1]] <- quote(all.equal)
+ if(!isTRUE(ae))
+ stop(sprintf("Not %s:\n%s\n\n", deparse(call),
+ paste(ae, collapse="\n")),
+ call.=FALSE)
+ ## else
+ TRUE
+ }
>
> UN <- function(L) lapply(L, unname)
>
> chk.NN.new.old <- function(cNew, cNold, tol = 2e-15, tol.1 = 20*tol) {
+ stopifnot(is.list(cNold$innc), length(n.i <- names(cNold$innc)) == 4)
+ cat("classification accordance matrix:\n")
+ print(table(new = cNew $classification,
+ old = cNold$classification))
+ report.stopifnot.all.eq(UN(cNew [1:4]),
+ UN(cNold[1:4]), tol=tol.1) &
+ report.stopifnot.all.eq(cNew $innc[n.i],
+ cNold$innc[n.i], tol=tol)
+ }
>
> summ.NN <- function(cNN, digits = 3) {
+ cbind(class = cNN$classification,
+ pprob = round(cNN$postprob, digits),
+ incc.p= round(cNN$innc$postprob, digits))
+ }
>
> s1 <- summ.NN(cN1)
> ss <- summ.NN(cN)
> if(isTRUE(all.equal(ss, s1))) ss else cbind(ss, s1)
class pprob incc.p class pprob incc.p
[1,] 1 1.000 1.000 1 1.000 1.000
[2,] 1 1.000 1.000 1 1.000 1.000
[3,] 1 1.000 1.000 1 1.000 1.000
[4,] 1 1.000 1.000 1 1.000 1.000
[5,] 1 1.000 1.000 1 1.000 1.000
[6,] 1 1.000 0.171 1 1.000 0.171
[7,] 1 1.000 1.000 1 1.000 1.000
[8,] 1 1.000 1.000 1 1.000 1.000
[9,] 1 1.000 1.000 1 1.000 1.000
[10,] 1 1.000 1.000 1 1.000 1.000
[11,] 1 1.000 1.000 1 1.000 1.000
[12,] 1 1.000 1.000 1 1.000 1.000
[13,] 1 1.000 1.000 1 1.000 1.000
[14,] 1 1.000 1.000 1 1.000 1.000
[15,] 1 1.000 0.000 1 0.998 0.000
[16,] 0 0.000 0.000 0 0.000 0.000
[17,] 1 1.000 0.718 1 1.000 0.718
[18,] 1 1.000 1.000 1 1.000 1.000
[19,] 1 1.000 0.002 1 1.000 0.002
[20,] 1 1.000 1.000 1 1.000 1.000
[21,] 1 1.000 1.000 1 1.000 1.000
[22,] 1 1.000 1.000 1 1.000 1.000
[23,] 1 1.000 1.000 1 1.000 1.000
[24,] 1 1.000 1.000 1 1.000 1.000
[25,] 1 1.000 1.000 1 1.000 1.000
[26,] 1 1.000 1.000 1 1.000 1.000
[27,] 1 1.000 1.000 1 1.000 1.000
[28,] 1 1.000 1.000 1 1.000 1.000
[29,] 1 1.000 1.000 1 1.000 1.000
[30,] 1 1.000 1.000 1 1.000 1.000
[31,] 1 1.000 1.000 1 1.000 1.000
[32,] 1 1.000 1.000 1 1.000 1.000
[33,] 1 1.000 0.000 1 1.000 0.000
[34,] 0 0.000 0.000 0 0.000 0.000
[35,] 1 1.000 1.000 1 1.000 1.000
[36,] 1 1.000 1.000 1 1.000 1.000
[37,] 1 1.000 1.000 1 1.000 1.000
[38,] 1 1.000 1.000 1 1.000 1.000
[39,] 1 1.000 1.000 1 1.000 1.000
[40,] 1 1.000 1.000 1 1.000 1.000
[41,] 1 1.000 1.000 1 1.000 1.000
[42,] 0 0.000 0.000 0 0.000 0.000
[43,] 1 1.000 1.000 1 1.000 1.000
[44,] 1 1.000 1.000 1 1.000 1.000
[45,] 1 1.000 1.000 1 1.000 1.000
[46,] 1 1.000 1.000 1 1.000 1.000
[47,] 1 1.000 1.000 1 1.000 1.000
[48,] 1 1.000 1.000 1 1.000 1.000
[49,] 1 1.000 1.000 1 1.000 1.000
[50,] 1 1.000 1.000 1 1.000 1.000
[51,] 1 1.000 0.058 1 1.000 0.058
[52,] 1 1.000 1.000 1 1.000 1.000
[53,] 1 1.000 1.000 1 1.000 1.000
[54,] 1 1.000 0.773 1 1.000 0.773
[55,] 1 1.000 1.000 1 1.000 1.000
[56,] 1 1.000 1.000 1 1.000 1.000
[57,] 1 1.000 0.999 1 1.000 0.999
[58,] 1 1.000 0.000 1 1.000 0.000
[59,] 1 1.000 1.000 1 1.000 1.000
[60,] 1 1.000 1.000 1 1.000 1.000
[61,] 0 0.000 0.000 0 0.000 0.000
[62,] 1 1.000 1.000 1 1.000 1.000
[63,] 1 0.611 0.000 0 0.000 0.000
[64,] 1 1.000 1.000 1 1.000 1.000
[65,] 1 1.000 1.000 1 1.000 1.000
[66,] 1 1.000 1.000 1 1.000 1.000
[67,] 1 1.000 1.000 1 1.000 1.000
[68,] 1 1.000 1.000 1 1.000 1.000
[69,] 1 0.786 0.000 0 0.000 0.000
[70,] 1 1.000 1.000 1 1.000 1.000
[71,] 1 1.000 1.000 1 1.000 1.000
[72,] 1 1.000 1.000 1 1.000 1.000
[73,] 1 1.000 1.000 1 1.000 1.000
[74,] 1 1.000 1.000 1 1.000 1.000
[75,] 1 1.000 1.000 1 1.000 1.000
[76,] 1 1.000 1.000 1 1.000 1.000
[77,] 1 1.000 1.000 1 1.000 1.000
[78,] 1 1.000 1.000 1 1.000 1.000
[79,] 1 1.000 1.000 1 1.000 1.000
[80,] 1 1.000 1.000 1 1.000 1.000
[81,] 1 1.000 1.000 1 1.000 1.000
[82,] 1 1.000 0.999 1 1.000 0.999
[83,] 1 1.000 1.000 1 1.000 1.000
[84,] 1 1.000 1.000 1 1.000 1.000
[85,] 1 1.000 1.000 1 1.000 1.000
[86,] 1 1.000 0.000 1 1.000 0.000
[87,] 1 1.000 1.000 1 1.000 1.000
[88,] 1 1.000 0.000 1 1.000 0.000
[89,] 1 1.000 1.000 1 1.000 1.000
[90,] 1 1.000 1.000 1 1.000 1.000
[91,] 1 1.000 1.000 1 1.000 1.000
[92,] 1 1.000 1.000 1 1.000 1.000
[93,] 1 1.000 1.000 1 1.000 1.000
[94,] 1 0.944 0.000 0 0.001 0.000
[95,] 1 1.000 1.000 1 1.000 1.000
[96,] 1 1.000 1.000 1 1.000 1.000
[97,] 1 1.000 1.000 1 1.000 1.000
[98,] 1 1.000 1.000 1 1.000 1.000
[99,] 1 1.000 0.000 1 1.000 0.000
[100,] 1 1.000 1.000 1 1.000 1.000
[101,] 1 1.000 0.000 1 1.000 0.000
[102,] 1 1.000 1.000 1 1.000 1.000
[103,] 1 1.000 1.000 1 1.000 1.000
[104,] 1 1.000 1.000 1 1.000 1.000
[105,] 1 1.000 1.000 1 1.000 1.000
[106,] 1 1.000 0.000 1 0.998 0.000
[107,] 1 1.000 0.000 0 0.317 0.000
[108,] 1 1.000 0.000 1 1.000 0.000
[109,] 1 1.000 0.000 1 0.999 0.000
[110,] 0 0.000 0.000 0 0.000 0.000
[111,] 1 1.000 1.000 1 1.000 1.000
[112,] 1 1.000 1.000 1 1.000 1.000
[113,] 1 1.000 1.000 1 1.000 1.000
[114,] 1 1.000 0.000 1 1.000 0.000
[115,] 1 1.000 0.899 1 1.000 0.899
[116,] 1 1.000 1.000 1 1.000 1.000
[117,] 1 1.000 1.000 1 1.000 1.000
[118,] 0 0.000 0.000 0 0.000 0.000
[119,] 0 0.000 0.000 0 0.000 0.000
[120,] 0 0.028 0.000 0 0.000 0.000
[121,] 1 1.000 1.000 1 1.000 1.000
[122,] 1 1.000 1.000 1 1.000 1.000
[123,] 0 0.000 0.000 0 0.000 0.000
[124,] 1 1.000 1.000 1 1.000 1.000
[125,] 1 1.000 1.000 1 1.000 1.000
[126,] 1 1.000 0.229 1 1.000 0.229
[127,] 1 1.000 1.000 1 1.000 1.000
[128,] 1 1.000 1.000 1 1.000 1.000
[129,] 1 1.000 1.000 1 1.000 1.000
[130,] 1 1.000 0.702 1 1.000 0.702
[131,] 1 1.000 0.000 0 0.357 0.000
[132,] 0 0.000 0.000 0 0.000 0.000
[133,] 1 1.000 1.000 1 1.000 1.000
[134,] 1 1.000 1.000 1 1.000 1.000
[135,] 1 1.000 0.818 1 1.000 0.818
[136,] 1 1.000 0.000 1 0.999 0.000
[137,] 1 1.000 0.000 1 1.000 0.000
[138,] 1 1.000 1.000 1 1.000 1.000
[139,] 1 1.000 1.000 1 1.000 1.000
[140,] 1 1.000 1.000 1 1.000 1.000
[141,] 1 1.000 1.000 1 1.000 1.000
[142,] 1 1.000 1.000 1 1.000 1.000
[143,] 1 1.000 1.000 1 1.000 1.000
[144,] 1 1.000 1.000 1 1.000 1.000
[145,] 1 1.000 1.000 1 1.000 1.000
[146,] 1 1.000 1.000 1 1.000 1.000
[147,] 1 1.000 0.991 1 1.000 0.991
[148,] 1 1.000 1.000 1 1.000 1.000
[149,] 1 1.000 0.000 1 1.000 0.000
[150,] 1 1.000 1.000 1 1.000 1.000
>
>
> try( # testing (tol=0 too small)
+ chk.NN.new.old(cN, cN1, tol=0)
+ )
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error : Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
> ## This used to fail when we use R's instead of BLAS matrix products:
> if(doCheck)
+ chk.NN.new.old(cN, cN1, tol = 4e-15) # seen 1.1e-15 work
classification accordance matrix:
old
new 0 1
0 10 0
1 5 135
Error: Not all.equal(UN(cNew[1:4]), UN(cNold[1:4]), tol = tol.1):
Component "cov": Mean relative difference: 0.01479474
Component "mu": Mean relative difference: 0.003191909
Component "postprob": Mean relative difference: 0.1351993
Component "classification": Mean relative difference: 1
Execution halted
Flavor: r-devel-windows-x86_64
Current CRAN status: OK: 14
Current CRAN status: NOTE: 2, OK: 12
Version: 0.9-2
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Martin Maechler <maechler@stat.math.ethz.ch>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Valentin",
family = "Rousson",
role = "aut",
email = "rousson@ifspm.unizh.ch"),
person(given = "Martin",
family = "Maechler",
role = c("aut", "cre"),
email = "maechler@stat.math.ethz.ch"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Current CRAN status: OK: 14
Current CRAN status: ERROR: 3, OK: 11
Version: 0.4-1-1
Check: tests
Result: ERROR
Running ‘ex_cvx.R’ [26s/26s]
Running ‘fastmerge-ex.R’ [1s/1s]
Running ‘smooth.pen_agcv.R’ [0s/1s]
Running the tests in ‘tests/smooth.pen_agcv.R’ failed.
Complete output:
> library(simest)
>
> ## Test smooth.pen.reg(*, agcv=TRUE) ---------------
>
> ## -- Using a subset of R's sunspots data ------
> osV <- abbreviate(gsub("[^[:alnum:]]", '', sub("\\(.*", '', osVersion)), 12)
>
> if(!dev.interactive(TRUE)) pdf(paste0("smooth.pen_sunsp__", osV, ".pdf"), width = 9, height=5)
>
> str(ssp <- window(sunspot.m2014, start = 1900))
Error: object 'sunspot.m2014' not found
Execution halted
Flavor: r-oldrel-macos-arm64
Version: 0.4-1-1
Check: tests
Result: ERROR
Running ‘ex_cvx.R’ [56s/130s]
Running ‘fastmerge-ex.R’ [5s/9s]
Running ‘smooth.pen_agcv.R’ [2s/4s]
Running the tests in ‘tests/smooth.pen_agcv.R’ failed.
Complete output:
> library(simest)
>
> ## Test smooth.pen.reg(*, agcv=TRUE) ---------------
>
> ## -- Using a subset of R's sunspots data ------
> osV <- abbreviate(gsub("[^[:alnum:]]", '', sub("\\(.*", '', osVersion)), 12)
>
> if(!dev.interactive(TRUE)) pdf(paste0("smooth.pen_sunsp__", osV, ".pdf"), width = 9, height=5)
>
> str(ssp <- window(sunspot.m2014, start = 1900))
Error: object 'sunspot.m2014' not found
Execution halted
Flavor: r-oldrel-macos-x86_64
Version: 0.4-1-1
Check: tests
Result: ERROR
Running 'ex_cvx.R' [86s]
Running 'fastmerge-ex.R' [6s]
Running 'smooth.pen_agcv.R' [2s]
Running the tests in 'tests/smooth.pen_agcv.R' failed.
Complete output:
> library(simest)
>
> ## Test smooth.pen.reg(*, agcv=TRUE) ---------------
>
> ## -- Using a subset of R's sunspots data ------
> osV <- abbreviate(gsub("[^[:alnum:]]", '', sub("\\(.*", '', osVersion)), 12)
>
> if(!dev.interactive(TRUE)) pdf(paste0("smooth.pen_sunsp__", osV, ".pdf"), width = 9, height=5)
>
> str(ssp <- window(sunspot.m2014, start = 1900))
Error: object 'sunspot.m2014' not found
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 14
Current CRAN status: NOTE: 2, OK: 12
Version: 1.1-1
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Martin Maechler <maechler@stat.math.ethz.ch>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Marcel",
family = "Dettling",
role = "aut",
email = "marcel.dettling@zhaw.ch"),
person(given = "Martin",
family = "Maechler",
role = c("aut", "cre"),
email = "maechler@stat.math.ethz.ch"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Current CRAN status: OK: 14