Last updated on 2026-07-23 20:51:43 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.18.10 | 20.63 | 360.70 | 381.33 | OK | |
| r-devel-linux-x86_64-debian-gcc | 2.18.10 | 12.58 | 257.00 | 269.58 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.18.10 | 35.00 | 562.71 | 597.71 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 2.18.10 | 13.00 | 237.94 | 250.94 | OK | |
| r-devel-windows-x86_64 | 2.18.10 | 22.00 | 377.00 | 399.00 | OK | |
| r-patched-linux-x86_64 | 2.18.10 | 19.70 | 344.05 | 363.75 | OK | |
| r-release-linux-x86_64 | 2.18.10 | 16.94 | 344.46 | 361.40 | OK | |
| r-release-macos-arm64 | 2.18.10 | 5.00 | 105.00 | 110.00 | OK | |
| r-release-macos-x86_64 | 2.18.10 | 13.00 | 433.00 | 446.00 | OK | |
| r-release-windows-x86_64 | 2.18.10 | 21.00 | 381.00 | 402.00 | OK | |
| r-oldrel-macos-arm64 | 2.18.10 | 5.00 | 98.00 | 103.00 | OK | |
| r-oldrel-macos-x86_64 | 2.18.10 | 13.00 | 301.00 | 314.00 | OK | |
| r-oldrel-windows-x86_64 | 2.18.10 | 29.00 | 589.00 | 618.00 | OK |
Version: 2.18.10
Check: tests
Result: ERROR
Running ‘test_asis.R’ [4s/7s]
Running ‘test_basics.R’ [4s/5s]
Running ‘test_bayesqgcomp.R’ [4s/6s]
Running ‘test_boot_ints.R’ [4s/5s]
Running ‘test_bootchooser.R’ [5s/7s]
Running ‘test_ee.R’ [19s/26s]
Running ‘test_factor.R’ [3s/5s]
Running ‘test_id.R’ [3s/4s]
Running ‘test_mice.R’ [4s/5s]
Running ‘test_multinomial.R’ [0s/0s]
Running ‘test_numeric.R’ [5s/6s]
Running ‘test_poisson.R’ [3s/4s]
Running ‘test_splits.R’ [3s/4s]
Running ‘test_weights.R’ [3s/3s]
Running the tests in ‘tests/test_mice.R’ failed.
Complete output:
> cat("# multiple imputation through chained equations test\n")
# multiple imputation through chained equations test
> library("qgcomp")
>
> N = 100
> set.seed(123)
> dat <- data.frame(y=runif(N), x1=runif(N), x2=runif(N), z=runif(N))
> true = qgcomp.noboot(f=y ~ z + x1 + x2, expnms = c('x1', 'x2'),
+ data=dat, q=2, family=gaussian())
> mdat <- dat
> mdat$x1 = ifelse(mdat$x1>0.5, mdat$x1, NA)
> mdat$x2 = ifelse(mdat$x2>0.75, mdat$x2, NA)
> true <- qgcomp.noboot(f=y ~ z + x1 + x2, expnms = c('x1', 'x2'),
+ data=dat, q=2, family=gaussian())
> cc <- qgcomp.noboot(f=y ~ z + x1 + x2, expnms = c('x1', 'x2'),
+ data=mdat[complete.cases(mdat),], q=2, family=gaussian())
>
>
> cdat = mdat
> cdat$x1 = ifelse(is.na(cdat$x1), 0.5/sqrt(2), cdat$x1)
> #data = cdat
> ff <- function(data){
+ nms = names(data)
+ j = which(nms == "x2")
+ f <- function(){
+ nms = names(data)
+ res = mice.impute.leftcenslognorm(y=cdat$x2,
+ ry=!is.na(cdat$x2),
+ x=cdat[,c("x1", "y", "z")],
+ wy=is.na(cdat$x2),
+ lod=NULL,
+ debug=TRUE)
+ res
+ }
+ f()
+ }
>
> # works when LOD is not specified and based on minimum non-missing value
> ff(cdat)
nmissing totalN min_imp max_imp lod
76.0000000 100.0000000 0.2824309 0.7535210 0.7542474
[1] 0.5453289 0.7109321 0.3605570 0.5747998 0.4428659 0.4427317 0.7396423
[8] 0.5830133 0.4287472 0.4378637 0.6174782 0.5343448 0.6282190 0.5254711
[15] 0.7184175 0.5974780 0.4503221 0.5888934 0.4601973 0.7131059 0.6614395
[22] 0.6303634 0.5791908 0.7535210 0.4323473 0.4850550 0.4034150 0.4922787
[29] 0.5147324 0.4608162 0.4244618 0.5302258 0.7037658 0.5409285 0.7210124
[36] 0.6894536 0.6459240 0.5560192 0.6067892 0.5441831 0.5934005 0.5841008
[43] 0.5180733 0.5091407 0.5424166 0.7223845 0.6892315 0.6587788 0.4633582
[50] 0.4730208 0.7430643 0.4910895 0.5933055 0.4927373 0.6530058 0.5515121
[57] 0.4020280 0.6577928 0.5352044 0.6777720 0.4020968 0.7010210 0.5850679
[64] 0.6439272 0.6364347 0.6080783 0.6576341 0.2824309 0.4555476 0.5146143
[71] 0.4707193 0.7166695 0.5613156 0.5550838 0.7337432 0.5124557
>
>
> f0 <- function(data, j){
+ print(sys.parent())
+ mice.impute.leftcenslognorm(y=data$x2,
+ ry=!is.na(data$x2),
+ x=data[,c("x1", "y", "z")],
+ wy=is.na(data$x2),
+ lod=c(NA, 0.5, 0.75, NA),
+ debug=TRUE)
+ }
>
> f1 <- function(data, j){
+ print(sys.parent())
+ #print(eval(as.name("data"), envir = parent.frame(n=1)))
+ f0(data, j=j)
+ }
>
> f2 <- function(data, j){
+ print(sys.parent())
+ f1(data, j)
+ }
> f3 <- function(data, j){
+ print(sys.parent())
+ f2(data, j)
+ }
> f4 <- function(data, j){
+ print(sys.parent())
+ f3(data, j)
+ }
> # none of these appears to work because "j" is never found
> f1(cdat, 3)
[1] 0
[1] 1
nmissing totalN min_imp max_imp
76 100 NA NA
integer(0)
NULL
fub1 fub2 fub3 fub4 fub5 fub6 fub7 fub8 fub9 fub10 fub11 fub12 fub13
NA NA NA NA NA NA NA NA NA NA NA NA NA
fub14 fub15 fub16 fub17 fub18 fub19 fub20 fub21 fub22 fub23 fub24 fub25 fub26
NA NA NA NA NA NA NA NA NA NA NA NA NA
fub27 fub28 fub29 fub30 fub31 fub32 fub33 fub34 fub35 fub36 fub37 fub38 fub39
NA NA NA NA NA NA NA NA NA NA NA NA NA
fub40 fub41 fub42 fub43 fub44 fub45 fub46 fub47 fub48 fub49 fub50 fub51 fub52
NA NA NA NA NA NA NA NA NA NA NA NA NA
fub53 fub54 fub55 fub56 fub57 fub58 fub59 fub60 fub61 fub62 fub63 fub64 fub65
NA NA NA NA NA NA NA NA NA NA NA NA NA
fub66 fub67 fub68 fub69 fub70 fub71 fub72 fub73 fub74 fub75 fub76
NA NA NA NA NA NA NA NA NA NA NA
lod1 lod2 lod3 lod4
NA 0.50 0.75 NA
numeric(0)
returny u linear.predictors scale
1 NA NA -0.011606509 0.05505391
2 NA NA -0.147965769 0.05505391
3 NA NA -0.001667315 0.05505391
4 NA NA -0.031577640 0.05505391
5 NA NA -0.221665698 0.05505391
6 NA NA -0.115086759 0.05505391
7 NA NA -0.068173103 0.05505391
8 NA NA -0.096001595 0.05505391
9 NA NA -0.119095996 0.05505391
10 NA NA -0.090487262 0.05505391
11 NA NA -0.070995402 0.05505391
12 NA NA -0.121652547 0.05505391
13 NA NA -0.096162075 0.05505391
14 NA NA -0.094961191 0.05505391
15 NA NA -0.149741153 0.05505391
16 NA NA -0.088545316 0.05505391
17 NA NA -0.234337557 0.05505391
18 NA NA -0.017345246 0.05505391
19 NA NA -0.128256851 0.05505391
20 NA NA -20.000000000 0.05505391
21 NA NA -20.000000000 0.05505391
22 NA NA -20.000000000 0.05505391
23 NA NA -20.000000000 0.05505391
24 NA NA -20.000000000 0.05505391
25 NA NA -20.000000000 0.05505391
26 NA NA -20.000000000 0.05505391
27 NA NA -20.000000000 0.05505391
28 NA NA -20.000000000 0.05505391
29 NA NA -20.000000000 0.05505391
30 NA NA -20.000000000 0.05505391
31 NA NA -20.000000000 0.05505391
32 NA NA -20.000000000 0.05505391
33 NA NA -20.000000000 0.05505391
34 NA NA -20.000000000 0.05505391
35 NA NA -20.000000000 0.05505391
36 NA NA -20.000000000 0.05505391
37 NA NA -20.000000000 0.05505391
38 NA NA -20.000000000 0.05505391
39 NA NA -20.000000000 0.05505391
40 NA NA -20.000000000 0.05505391
41 NA NA -20.000000000 0.05505391
42 NA NA -20.000000000 0.05505391
43 NA NA -20.000000000 0.05505391
44 NA NA -20.000000000 0.05505391
45 NA NA -20.000000000 0.05505391
46 NA NA -20.000000000 0.05505391
47 NA NA -20.000000000 0.05505391
48 NA NA -20.000000000 0.05505391
49 NA NA -20.000000000 0.05505391
50 NA NA -20.000000000 0.05505391
51 NA NA -20.000000000 0.05505391
52 NA NA -20.000000000 0.05505391
53 NA NA -20.000000000 0.05505391
54 NA NA -20.000000000 0.05505391
55 NA NA -20.000000000 0.05505391
56 NA NA -20.000000000 0.05505391
57 NA NA -20.000000000 0.05505391
58 NA NA -20.000000000 0.05505391
59 NA NA -20.000000000 0.05505391
60 NA NA -20.000000000 0.05505391
61 NA NA -20.000000000 0.05505391
62 NA NA -20.000000000 0.05505391
63 NA NA -20.000000000 0.05505391
64 NA NA -20.000000000 0.05505391
65 NA NA -20.000000000 0.05505391
66 NA NA -20.000000000 0.05505391
67 NA NA -20.000000000 0.05505391
68 NA NA -20.000000000 0.05505391
69 NA NA -20.000000000 0.05505391
70 NA NA -20.000000000 0.05505391
71 NA NA -20.000000000 0.05505391
72 NA NA -20.000000000 0.05505391
73 NA NA -20.000000000 0.05505391
74 NA NA -20.000000000 0.05505391
75 NA NA -20.000000000 0.05505391
76 NA NA -20.000000000 0.05505391
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA
Warning message:
In mice.impute.leftcenslognorm(y = data$x2, ry = !is.na(data$x2), :*** buffer overflow detected ***: terminated
Aborted
Flavor: r-devel-linux-x86_64-debian-gcc