CRAN Package Check Results for Package logmult

Last updated on 2020-07-06 21:50:30 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.7.1 14.38 144.06 158.44 OK
r-devel-linux-x86_64-debian-gcc 0.7.1 14.01 110.51 124.52 OK
r-devel-linux-x86_64-fedora-clang 0.7.1 198.29 OK
r-devel-linux-x86_64-fedora-gcc 0.7.1 189.49 OK
r-devel-windows-ix86+x86_64 0.7.1 32.00 155.00 187.00 OK
r-patched-linux-x86_64 0.7.1 15.79 142.53 158.32 OK
r-patched-solaris-x86 0.7.1 266.20 OK
r-release-linux-x86_64 0.7.1 11.98 143.11 155.09 OK
r-release-osx-x86_64 0.7.1 OK
r-release-windows-ix86+x86_64 0.7.1 23.00 149.00 172.00 OK
r-oldrel-osx-x86_64 0.7.1 OK
r-oldrel-windows-ix86+x86_64 0.7.1 21.00 194.00 215.00 ERROR

Check Details

Version: 0.7.1
Check: tests
Result: ERROR
     Running 'Becker-Clogg1989.R' [1s]
     Running 'Clogg-Shihadeh1994.R' [3s]
     Running 'Goodman1979.R' [3s]
     Running 'Goodman1991.R' [3s]
     Running 'Wong2010-2.7.R' [1s]
     Running 'Wong2010-4.7.R' [0s]
     Running 'Yamaguchi1990.R' [3s]
     Running 'hmskewL.R' [7s]
     Running 'iac.R' [11s]
     Running 'maor.R' [7s]
     Running 'ras.R' [3s]
     Running 'supplementary.R' [5s]
     Running 'vanderHeijden-Mooijaart1995.R' [3s]
    Running the tests in 'tests/hmskewL.R' failed.
    Complete output:
     > # Artificial example to check the hmskewL model
     >
     > library(logmult)
     Loading required package: gnm
    
     Attaching package: 'logmult'
    
     The following object is masked from 'package:gnm':
    
     se
    
     > data(ocg1973)
     >
     > tab <- array(ocg1973, dim=c(nrow(ocg1973), ncol(ocg1973), 2))
     >
     > model <- hmskewL(tab[5:1, 5:1,], weighting="uniform", start=NA)
     Running base model to find starting values...
     Running real model...
     Initialising
     Running main iterations..........
     Done
     Warning message:
     Using make.unique() to make default parameter labels unique
     > ass <- model$assoc
     >
     > # First score for Farmers is slightly different from the original article
     > stopifnot(isTRUE(all.equal(round(ass$row[,,1] * sqrt(ass$phi[1,1]), d=2)[5:1,],
     + matrix(c(-0.08, -0.2, -0.23, -0.11, 0.61,
     + 0.34, 0.3, -0.13, -0.51, 0), 5, 2),
     + check.attributes=FALSE)))
     > stopifnot(isTRUE(all.equal(round(ass$row[,,1] * sqrt(ass$phi[2,1]), d=2)[5:1,],
     + matrix(c(-0.08, -0.2, -0.23, -0.11, 0.61,
     + 0.34, 0.3, -0.13, -0.51, 0), 5, 2),
     + check.attributes=FALSE)))
     >
     > model2 <- hmskewL(tab[5:1, 5:1,], weighting="uniform", layer.effect.skew="heterogeneous")
     Initialising
     Running start-up iterations..
     Running main iterations........
     Done
     Warning message:
     Using make.unique() to make default parameter labels unique
     > stopifnot(isTRUE(all.equal(model$assoc$phi, model2$assoc$phi)))
     > stopifnot(isTRUE(all.equal(model$assoc$row[,,1], model2$assoc$row[,,1])))
     >
     >
     > # EGP class of cohabiting spouses where one is 30-60 (last occupation for inactive persons)
     > # French Labour Force Surveys, 1969 and 2011
     > tab2 <- structure(c(261L, 43L, 21L, 5L, 7L, 26L, 5L, 16L, 17L, 7L, 1L,
     + 483L, 394L, 215L, 53L, 58L, 117L, 37L, 185L, 232L, 104L, 11L,
     + 565L, 457L, 528L, 139L, 116L, 201L, 19L, 469L, 788L, 368L, 14L,
     + 148L, 195L, 399L, 306L, 96L, 213L, 50L, 321L, 1327L, 1344L, 123L,
     + 17L, 9L, 11L, 3L, 33L, 37L, 4L, 12L, 13L, 11L, 1L, 165L, 70L,
     + 105L, 77L, 573L, 878L, 55L, 78L, 188L, 181L, 11L, 9L, 3L, 34L,
     + 7L, 23L, 36L, 1918L, 13L, 88L, 228L, 87L, 26L, 10L, 16L, 3L,
     + 0L, 1L, 2L, 27L, 31L, 24L, 1L, 88L, 115L, 191L, 57L, 50L, 98L,
     + 32L, 201L, 552L, 493L, 19L, 49L, 115L, 317L, 122L, 58L, 110L,
     + 38L, 316L, 1301L, 1622L, 66L, 0L, 3L, 9L, 6L, 4L, 13L, 15L, 7L,
     + 56L, 135L, 143L, 919L, 189L, 54L, 32L, 74L, 64L, 19L, 113L, 86L,
     + 40L, 3L, 875L, 519L, 183L, 97L, 129L, 129L, 62L, 329L, 343L,
     + 195L, 12L, 513L, 330L, 271L, 126L, 188L, 145L, 70L, 382L, 578L,
     + 388L, 15L, 250L, 236L, 180L, 217L, 126L, 155L, 52L, 356L, 965L,
     + 634L, 42L, 28L, 8L, 10L, 5L, 59L, 14L, 2L, 20L, 30L, 6L, 1L,
     + 61L, 30L, 20L, 7L, 52L, 106L, 4L, 23L, 38L, 17L, 2L, 4L, 1L,
     + 2L, 4L, 6L, 3L, 135L, 4L, 7L, 8L, 2L, 53L, 19L, 7L, 3L, 8L, 6L,
     + 3L, 39L, 31L, 22L, 2L, 28L, 44L, 34L, 20L, 19L, 16L, 11L, 64L,
     + 165L, 105L, 9L, 41L, 35L, 42L, 52L, 20L, 38L, 10L, 111L, 299L,
     + 309L, 12L, 1L, 3L, 2L, 2L, 0L, 4L, 25L, 4L, 32L, 19L, 16L),
     + .Dim = c(11L, 11L, 2L), class="table",
     + .Dimnames = structure(list(H = c("I", "II", "IIIa", "IIIb", "IVa",
     + "IVb", "IVc", "V", "VI", "VIIa", "VIIb"),
     + F = c("I", "II", "IIIa", "IIIb", "IVa", "IVb",
     + "IVc", "V", "VI", "VIIa", "VIIb"),
     + T = c("1969", "2011")),
     + .Names = c("M", "W", "T")))
     >
     > model2 <- hmskewL(tab2, start=NA)
     Running base model to find starting values...
     Running real model...
     Initialising
     Running main iterations.........................................................
     ...
     Done
     Warning message:
     Using make.unique() to make default parameter labels unique
     >
     > stopifnot(isTRUE(all.equal(round(c(model2$assoc$phi), 2), c(0.18, 0.04, 0.18, 0.04))))
     > stopifnot(isTRUE(all.equal(round(c(model2$assoc$row), 2),
     + c(1.97, 1.38, 0.05, -0.24, -1.02, 0.57, -0.79, -0.16, -0.14, -1.32, -1.56,
     + 0, -0.03, -0.94, 0.98, -0.10, 0.71, 2.65, -0.86, -0.66, -0.77, 0.79))))
     >
     > # Test anova
     > indep <- gnm(Freq ~ M*T + W*T, data=tab2, family=poisson)
     > anova(indep, model2, test="LR")
     Analysis of Deviance Table
    
     Model 1: Freq ~ M + T + M:T + W + T:W
     Model 2: Freq ~ M + W + T + M:T + W:T + T:Symm(M, W) + Mult(T, HMSkew(M,
     W)) - 1
     Resid. Df Resid. Dev Df Deviance Pr(>Chi)
     1 200 23558
     2 72 181 128 23377 < 2.2e-16 ***
     ---
     Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
     > anova(indep, model2, test="Chisq")
     Analysis of Deviance Table
    
     Model 1: Freq ~ M + T + M:T + W + T:W
     Model 2: Freq ~ M + W + T + M:T + W:T + T:Symm(M, W) + Mult(T, HMSkew(M,
     W)) - 1
     Resid. Df Resid. Dev Df Deviance Pr(>Chi)
     1 200 23558
     2 72 181 128 23377 < 2.2e-16 ***
     ---
     Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
     >
     >
     > # Check that plotting works for both symmetric and skew-symmetric components
     > model <- hmskewL(tab[5:1, 5:1,], nd.symm=1, layer.effect.symm="homogeneous")
     Initialising
     Running start-up iterations..
     Running main iterations...
     Deviance is not finite
     Warning messages:
     1: Using make.unique() to make default parameter labels unique
     2: Algorithm failed - no model could be estimated
     > plot(model)
     Error in plot.window(...) : need finite 'xlim' values
     Calls: plot -> plot.default -> localWindow -> plot.window
     In addition: Warning messages:
     1: In min(x) : no non-missing arguments to min; returning Inf
     2: In max(x) : no non-missing arguments to max; returning -Inf
     3: In min(x) : no non-missing arguments to min; returning Inf
     4: In max(x) : no non-missing arguments to max; returning -Inf
     Execution halted
Flavor: r-oldrel-windows-ix86+x86_64