CRAN Package Check Results for Package umx

Last updated on 2015-09-06 23:47:48.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.50 2.49 53.94 56.43 OK
r-devel-linux-x86_64-debian-gcc 0.50 2.50 50.70 53.20 OK
r-devel-linux-x86_64-fedora-clang 0.50 112.03 OK
r-devel-linux-x86_64-fedora-gcc 0.50 115.48 OK
r-devel-osx-x86_64-clang 0.50 92.66 OK
r-devel-windows-ix86+x86_64 0.50 8.00 143.00 151.00 OK
r-patched-linux-x86_64 0.50 2.68 53.77 56.45 OK
r-patched-solaris-sparc 0.50 566.70 ERROR
r-patched-solaris-x86 0.50 124.00 ERROR
r-release-linux-x86_64 0.50 2.66 53.07 55.73 OK
r-release-osx-x86_64-mavericks 0.50 OK
r-release-windows-ix86+x86_64 0.50 12.00 153.00 165.00 OK
r-oldrel-windows-ix86+x86_64 0.50 13.00 146.00 159.00 OK

Check Details

Version: 0.50
Check: examples
Result: ERROR
    Running examples in ‘umx-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: umxACE
    > ### Title: umxACE
    > ### Aliases: umxACE
    >
    > ### ** Examples
    >
    > # Height, weight, and BMI data from Australian twins.
    > # The total sample has been subdivided into a young cohort, aged 18-30 years,
    > # and an older cohort aged 31 and above.
    > # Cohort 1 Zygosity is coded as follows:
    > # 1 == MZ females 2 == MZ males 3 == DZ females 4 == DZ males 5 == DZ opposite sex pairs
    > # tip: ?twinData to learn more about this data set
    > require(OpenMx)
    > require(umx)
    > data(twinData)
    > tmpTwin <- twinData
    > names(tmpTwin)
     [1] "fam" "age" "zyg" "part" "wt1" "wt2" "ht1" "ht2" "htwt1"
    [10] "htwt2" "bmi1" "bmi2"
    > # "fam", "age", "zyg", "part", "wt1", "wt2", "ht1", "ht2", "htwt1", "htwt2", "bmi1", "bmi2"
    >
    > # Set zygosity to a factor
    > labList = c("MZFF", "MZMM", "DZFF", "DZMM", "DZOS")
    > tmpTwin$zyg = factor(tmpTwin$zyg, levels = 1:5, labels = labList)
    >
    > # Pick the variables
    > selDVs = c("bmi1", "bmi2") # nb: Can also give base name, (i.e., "bmi") AND set suffix.
    > # the function will then make the varnames for each twin using this:
    > # for example. "VarSuffix1" "VarSuffix2"
    > mzData <- tmpTwin[tmpTwin$zyg %in% "MZFF", selDVs]
    > dzData <- tmpTwin[tmpTwin$zyg %in% "DZFF", selDVs]
    > mzData <- mzData[1:200,] # just top 200 so example runs in a couple of secs
    > dzData <- dzData[1:200,]
    > m1 = umxACE(selDVs = selDVs, dzData = dzData, mzData = mzData)
    All variables continuous
    treating data as raw
    > m1 = umxRun(m1)
    Running ACE
    Warning: In model 'ACE' Optimizer returned a non-zero status code 10. Starting values are not feasible. Consider mxTryHard()
    > umxSummary(m1)
    -2 × log(Likelihood)
    'log Lik.' NA (df=4)
    Standardized solution
     a1 c1 e1
    bmi1 0.58 0.58 0.58
    > umxSummaryACE(m1)
    -2 × log(Likelihood)
    'log Lik.' NA (df=4)
    Standardized solution
     a1 c1 e1
    bmi1 0.58 0.58 0.58
    > ## Not run:
    > ##D plot(m1)
    > ## End(Not run)
    > # ADE model (DZ correlation set to .25)
    > m2 = umxACE("ADE", selDVs = selDVs, dzData = dzData, mzData = mzData, dzCr = .25)
    All variables continuous
    treating data as raw
    > m2 = umxRun(m2)
    Running ADE
    Warning: In model 'ADE' Optimizer returned a non-zero status code 10. Starting values are not feasible. Consider mxTryHard()
    > mxCompare(m2, m1) # ADE is better
     base comparison ep minus2LL df AIC diffLL diffdf p
    1 ADE <NA> 4 NA 762 NA NA NA NA
    2 ADE ACE 4 NA 762 NA NA 0 NA
    > umxSummary(m2) # nb: though this is ADE, it's labeled ACE
    -2 × log(Likelihood)
    'log Lik.' NA (df=4)
    Standardized solution
     a1 c1 e1
    bmi1 0.58 0.58 0.58
    >
    >
    > # ===================
    > # = Ordinal example =
    > # ===================
    > require(OpenMx)
    > data(twinData)
    > tmpTwin <- twinData
    > names(tmpTwin)
     [1] "fam" "age" "zyg" "part" "wt1" "wt2" "ht1" "ht2" "htwt1"
    [10] "htwt2" "bmi1" "bmi2"
    > # "fam", "age", "zyg", "part", "wt1", "wt2", "ht1", "ht2", "htwt1", "htwt2", "bmi1", "bmi2"
    >
    > # Set zygosity to a factor
    > labList = c("MZFF", "MZMM", "DZFF", "DZMM", "DZOS")
    > tmpTwin$zyg = factor(tmpTwin$zyg, levels = 1:5, labels = labList)
    >
    > # Cut bmi colum to form ordinal obesity variables
    > ordDVs = c("obese1", "obese2")
    > selDVs = c("obese")
    > obesityLevels = c('normal', 'overweight', 'obese')
    > cutPoints <- quantile(tmpTwin[, "bmi1"], probs = c(.5, .2), na.rm = TRUE)
    > tmpTwin$obese1 <- cut(tmpTwin$bmi1, breaks = c(-Inf, cutPoints, Inf), labels = obesityLevels)
    > tmpTwin$obese2 <- cut(tmpTwin$bmi2, breaks = c(-Inf, cutPoints, Inf), labels = obesityLevels)
    > # Make the ordinal variables into mxFactors (ensure ordered is TRUE, and require levels)
    > tmpTwin[, ordDVs] <- mxFactor(tmpTwin[, ordDVs], levels = obesityLevels)
    > mzData <- tmpTwin[tmpTwin$zyg %in% "MZFF", umx_paste_names(selDVs, "", 1:2)]
    > dzData <- tmpTwin[tmpTwin$zyg %in% "DZFF", umx_paste_names(selDVs, "", 1:2)]
    > mzData <- mzData[1:200,] # just top 200 so example runs in a couple of secs
    > dzData <- dzData[1:200,]
    > str(mzData)
    'data.frame': 200 obs. of 2 variables:
     $ obese1: Ord.factor w/ 3 levels "normal"<"overweight"<..: 2 2 2 3 1 3 2 1 1 3 ...
     $ obese2: Ord.factor w/ 3 levels "normal"<"overweight"<..: 1 1 1 3 1 3 2 1 1 2 ...
    > m1 = umxACE(selDVs = selDVs, dzData = dzData, mzData = mzData, suffix = '')
    umxACE found 1 pairs of ordinal variables:'obese1' and 'obese2'
    treating data as raw
    > m1 = mxRun(m1)
    Running ACE
    Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
     Can only omxRemoveRowsAndColumns once
    Calls: mxRun -> runHelper -> .Call
    Execution halted
Flavor: r-patched-solaris-sparc

Version: 0.50
Check: examples
Result: ERROR
    Running examples in ‘umx-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: umxACE
    > ### Title: umxACE
    > ### Aliases: umxACE
    >
    > ### ** Examples
    >
    > # Height, weight, and BMI data from Australian twins.
    > # The total sample has been subdivided into a young cohort, aged 18-30 years,
    > # and an older cohort aged 31 and above.
    > # Cohort 1 Zygosity is coded as follows:
    > # 1 == MZ females 2 == MZ males 3 == DZ females 4 == DZ males 5 == DZ opposite sex pairs
    > # tip: ?twinData to learn more about this data set
    > require(OpenMx)
    > require(umx)
    > data(twinData)
    > tmpTwin <- twinData
    > names(tmpTwin)
     [1] "fam" "age" "zyg" "part" "wt1" "wt2" "ht1" "ht2" "htwt1"
    [10] "htwt2" "bmi1" "bmi2"
    > # "fam", "age", "zyg", "part", "wt1", "wt2", "ht1", "ht2", "htwt1", "htwt2", "bmi1", "bmi2"
    >
    > # Set zygosity to a factor
    > labList = c("MZFF", "MZMM", "DZFF", "DZMM", "DZOS")
    > tmpTwin$zyg = factor(tmpTwin$zyg, levels = 1:5, labels = labList)
    >
    > # Pick the variables
    > selDVs = c("bmi1", "bmi2") # nb: Can also give base name, (i.e., "bmi") AND set suffix.
    > # the function will then make the varnames for each twin using this:
    > # for example. "VarSuffix1" "VarSuffix2"
    > mzData <- tmpTwin[tmpTwin$zyg %in% "MZFF", selDVs]
    > dzData <- tmpTwin[tmpTwin$zyg %in% "DZFF", selDVs]
    > mzData <- mzData[1:200,] # just top 200 so example runs in a couple of secs
    > dzData <- dzData[1:200,]
    > m1 = umxACE(selDVs = selDVs, dzData = dzData, mzData = mzData)
    All variables continuous
    treating data as raw
    > m1 = umxRun(m1)
    Running ACE
    Warning: In model 'ACE' Optimizer returned a non-zero status code 10. Starting values are not feasible. Consider mxTryHard()
    > umxSummary(m1)
    -2 × log(Likelihood)
    'log Lik.' 2955.482 (df=4)
    Standardized solution
     a1 c1 e1
    bmi1 0.58 0.58 0.58
    > umxSummaryACE(m1)
    -2 × log(Likelihood)
    'log Lik.' 2955.482 (df=4)
    Standardized solution
     a1 c1 e1
    bmi1 0.58 0.58 0.58
    > ## Not run:
    > ##D plot(m1)
    > ## End(Not run)
    > # ADE model (DZ correlation set to .25)
    > m2 = umxACE("ADE", selDVs = selDVs, dzData = dzData, mzData = mzData, dzCr = .25)
    All variables continuous
    treating data as raw
    > m2 = umxRun(m2)
    Running ADE
    Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
     BLAS/LAPACK routine 'DSYMV ' gave error code -5
    Calls: umxRun -> mxRun -> runHelper -> .Call
    Execution halted
Flavor: r-patched-solaris-x86