CRAN Package Check Results for Package uwIntroStats

Last updated on 2018-05-24 17:49:52 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.0.5 14.97 97.69 112.66 ERROR
r-devel-linux-x86_64-debian-gcc 0.0.5 12.09 82.48 94.57 ERROR
r-devel-linux-x86_64-fedora-clang 0.0.5 155.35 ERROR
r-devel-linux-x86_64-fedora-gcc 0.0.5 146.70 ERROR
r-devel-windows-ix86+x86_64 0.0.5 20.00 122.00 142.00 ERROR
r-patched-linux-x86_64 0.0.5 16.87 95.75 112.62 ERROR
r-patched-solaris-x86 0.0.5 190.70 ERROR
r-release-linux-x86_64 0.0.5 13.04 94.87 107.91 ERROR
r-release-windows-ix86+x86_64 0.0.5 28.00 253.00 281.00 OK
r-release-osx-x86_64 0.0.5 ERROR
r-oldrel-windows-ix86+x86_64 0.0.5 14.00 117.00 131.00 ERROR
r-oldrel-osx-x86_64 0.0.5 OK

Check Details

Version: 0.0.5
Check: examples
Result: ERROR
    Running examples in ‘uwIntroStats-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: regress
    > ### Title: General Regression for an Arbitrary Functional
    > ### Aliases: regress fitted.uRegress print.augCoefficients print.uRegress
    > ### uLRtest uWaldtest termTraverse explode indentNames getLevels testList
    > ### pasteTwo processTerm addArgs pasteOn pasteOnSpline pastePair
    > ### movingSum myNext reFormatReg createCols checkNesting splitOnParen
    > ### reFormat equal
    > ### Keywords: ~kwd1 ~kwd2
    >
    > ### ** Examples
    >
    > # Loading required libraries
    > library(survival)
    > library(sandwich)
    >
    > # Reading in a dataset
    > mri <- read.table("http://www.emersonstatistics.com/datasets/mri.txt",header=TRUE)
    >
    > # Creating a Surv object to reflect time to death
    > mri$ttodth <- Surv(mri$obstime,mri$death)
    >
    > # Attaching the mri dataset
    > attach(mri)
    >
    > # Linear regression of atrophy on age
    > regress("mean", atrophy~age, data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ age, data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -36.870 -8.589 -0.870 7.666 51.203
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept -16.06 6.256 6.701 -29.22 -2.907
    [2] age 0.6980 0.08368 0.09002 0.5213 0.8747
     F stat df Pr(>F)
    [1] Intercept 5.75 1 0.0168
    [2] age 60.12 1 < 0.00005
    
    Residual standard error: 12.36 on 733 degrees of freedom
    Multiple R-squared: 0.08669, Adjusted R-squared: 0.08545
    F-statistic: 60.12 on 1 and 733 DF, p-value: 2.988e-14
    
    >
    > ## Linear regression of atrophy on male and race and their interaction,
    > ## with a multiple-partial F-test on the race-age interaction
    > regress("mean", atrophy~ male + U(ra=~race*age), data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ male + U(ra = ~race *
     age), data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -33.438 -8.368 -0.462 7.372 53.253
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept 2.199 13.24 14.53 -26.33 30.73
    [2] male 6.003 0.8850 0.8815 4.273 7.734
     ra
    [3] race -15.30 8.902 9.660 -34.26 3.664
    [4] age 0.4255 0.1770 0.1943 0.04399 0.8070
    [5] race:age 0.1954 0.1186 0.1287 -0.05726 0.4481
     F stat df Pr(>F)
    [1] Intercept 0.02 1 0.8798
    [2] male 46.37 1 < 0.00005
     ra 21.51 3 < 0.00005
    [3] race 2.51 1 0.1137
    [4] age 4.79 1 0.0289
    [5] race:age 2.31 1 0.1293
    
    Residual standard error: 11.99 on 730 degrees of freedom
    Multiple R-squared: 0.1443, Adjusted R-squared: 0.1397
    F-statistic: 27.23 on 4 and 730 DF, p-value: < 2.2e-16
    
    >
    > ## Linear regression of atrophy on age, male, race (as a dummy variable), chf,
    > ## and diabetes. There are two multiple partial F-tests and both are named
    > regress("mean", atrophy~age+male+U(rc=~dummy(race)+chf)+U(md=~male+diabetes), data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ age + male + U(rc = ~dummy(race) +
     chf) + U(md = ~male + diabetes), data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -34.003 -8.611 -0.572 7.279 54.064
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept -17.95 6.088 6.593 -30.90 -5.009
    [2] age 0.6862 0.08142 0.08840 0.5127 0.8598
    [3] male 5.879 0.8952 0.8942 4.123 7.635
     rc
     dummy(race)
    [4] race.2 -2.147 1.285 1.255 -4.611 0.3176
    [5] race.3 0.1829 1.826 1.796 -3.343 3.709
    [6] race.4 -2.734 3.508 3.798 -10.19 4.722
    [7] chf 1.919 1.943 2.179 -2.358 6.197
     md
     male 5.879 0.8952 0.8942 4.123 7.635
    [8] diabetes 0.6524 1.450 1.267 -1.836 3.141
     F stat df Pr(>F)
    [1] Intercept 7.41 1 0.0066
    [2] age 60.25 1 < 0.00005
    [3] male 43.23 1 < 0.00005
     rc 1.09 4 0.3598
     dummy(race) 1.14 3 0.3336
    [4] race.2 2.92 1 0.0877
    [5] race.3 0.01 1 0.9189
    [6] race.4 0.52 1 0.4718
    [7] chf 0.78 1 0.3787
     md 22.84 2 < 0.00005
     male 43.23 1 < 0.00005
    [8] diabetes 0.26 1 0.6069
    
     Dummy terms calculated from race, reference = 1
    
    Residual standard error: 12 on 727 degrees of freedom
    Multiple R-squared: 0.1453, Adjusted R-squared: 0.1371
    F-statistic: 15.31 on 7 and 727 DF, p-value: < 2.2e-16
    
    >
    > ## Proportional hazards regression clustered on id
    > ## (here it makes no difference because the ids are unique)
    > regress("hazard", ttodth~ldl, id=ptid, data=mri)
    Warning in coxph(formula, data = data, ...) :
     a variable appears on both the left and right sides of the formula
    Error in eval(predvars, data, env) :
     invalid 'envir' argument of type 'closure'
    Calls: regress ... eval -> eval -> <Anonymous> -> model.frame.default -> eval
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.0.5
Check: re-building of vignette outputs
Result: WARN
    Error in re-building vignettes:
     ...
    Quitting from lines 92-93 (regress_intro.Rmd)
    Error: processing vignette ‘regress_intro.Rmd’ failed with diagnostics:
    object ‘ttodth’ not found
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.0.5
Check: examples
Result: ERROR
    Running examples in ‘uwIntroStats-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: regress
    > ### Title: General Regression for an Arbitrary Functional
    > ### Aliases: regress fitted.uRegress print.augCoefficients print.uRegress
    > ### uLRtest uWaldtest termTraverse explode indentNames getLevels testList
    > ### pasteTwo processTerm addArgs pasteOn pasteOnSpline pastePair
    > ### movingSum myNext reFormatReg createCols checkNesting splitOnParen
    > ### reFormat equal
    > ### Keywords: ~kwd1 ~kwd2
    >
    > ### ** Examples
    >
    > # Loading required libraries
    > library(survival)
    > library(sandwich)
    >
    > # Reading in a dataset
    > mri <- read.table("http://www.emersonstatistics.com/datasets/mri.txt",header=TRUE)
    >
    > # Creating a Surv object to reflect time to death
    > mri$ttodth <- Surv(mri$obstime,mri$death)
    >
    > # Attaching the mri dataset
    > attach(mri)
    >
    > # Linear regression of atrophy on age
    > regress("mean", atrophy~age, data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ age, data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -36.870 -8.589 -0.870 7.666 51.203
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept -16.06 6.256 6.701 -29.22 -2.907
    [2] age 0.6980 0.08368 0.09002 0.5213 0.8747
     F stat df Pr(>F)
    [1] Intercept 5.75 1 0.0168
    [2] age 60.12 1 < 0.00005
    
    Residual standard error: 12.36 on 733 degrees of freedom
    Multiple R-squared: 0.08669, Adjusted R-squared: 0.08545
    F-statistic: 60.12 on 1 and 733 DF, p-value: 2.988e-14
    
    >
    > ## Linear regression of atrophy on male and race and their interaction,
    > ## with a multiple-partial F-test on the race-age interaction
    > regress("mean", atrophy~ male + U(ra=~race*age), data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ male + U(ra = ~race *
     age), data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -33.438 -8.368 -0.462 7.372 53.253
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept 2.199 13.24 14.53 -26.33 30.73
    [2] male 6.003 0.8850 0.8815 4.273 7.734
     ra
    [3] race -15.30 8.902 9.660 -34.26 3.664
    [4] age 0.4255 0.1770 0.1943 0.04399 0.8070
    [5] race:age 0.1954 0.1186 0.1287 -0.05726 0.4481
     F stat df Pr(>F)
    [1] Intercept 0.02 1 0.8798
    [2] male 46.37 1 < 0.00005
     ra 21.51 3 < 0.00005
    [3] race 2.51 1 0.1137
    [4] age 4.79 1 0.0289
    [5] race:age 2.31 1 0.1293
    
    Residual standard error: 11.99 on 730 degrees of freedom
    Multiple R-squared: 0.1443, Adjusted R-squared: 0.1397
    F-statistic: 27.23 on 4 and 730 DF, p-value: < 2.2e-16
    
    >
    > ## Linear regression of atrophy on age, male, race (as a dummy variable), chf,
    > ## and diabetes. There are two multiple partial F-tests and both are named
    > regress("mean", atrophy~age+male+U(rc=~dummy(race)+chf)+U(md=~male+diabetes), data=mri)
    
    Call:
    regress(fnctl = "mean", formula = atrophy ~ age + male + U(rc = ~dummy(race) +
     chf) + U(md = ~male + diabetes), data = mri)
    
    Residuals:
     Min 1Q Median 3Q Max
    -34.003 -8.611 -0.572 7.279 54.064
    
    Coefficients:
     Estimate Naive SE Robust SE 95%L 95%H
    [1] Intercept -17.95 6.088 6.593 -30.90 -5.009
    [2] age 0.6862 0.08142 0.08840 0.5127 0.8598
    [3] male 5.879 0.8952 0.8942 4.123 7.635
     rc
     dummy(race)
    [4] race.2 -2.147 1.285 1.255 -4.611 0.3176
    [5] race.3 0.1829 1.826 1.796 -3.343 3.709
    [6] race.4 -2.734 3.508 3.798 -10.19 4.722
    [7] chf 1.919 1.943 2.179 -2.358 6.197
     md
     male 5.879 0.8952 0.8942 4.123 7.635
    [8] diabetes 0.6524 1.450 1.267 -1.836 3.141
     F stat df Pr(>F)
    [1] Intercept 7.41 1 0.0066
    [2] age 60.25 1 < 0.00005
    [3] male 43.23 1 < 0.00005
     rc 1.09 4 0.3598
     dummy(race) 1.14 3 0.3336
    [4] race.2 2.92 1 0.0877
    [5] race.3 0.01 1 0.9189
    [6] race.4 0.52 1 0.4718
    [7] chf 0.78 1 0.3787
     md 22.84 2 < 0.00005
     male 43.23 1 < 0.00005
    [8] diabetes 0.26 1 0.6069
    
     Dummy terms calculated from race, reference = 1
    
    Residual standard error: 12 on 727 degrees of freedom
    Multiple R-squared: 0.1453, Adjusted R-squared: 0.1371
    F-statistic: 15.31 on 7 and 727 DF, p-value: < 2.2e-16
    
    >
    > ## Proportional hazards regression clustered on id
    > ## (here it makes no difference because the ids are unique)
    > regress("hazard", ttodth~ldl, id=ptid, data=mri)
    Warning in coxph(formula, data = data, ...) :
     a variable appears on both the left and right sides of the formula
    Error in eval(predvars, data, env) :
     invalid 'envir' argument of type 'closure'
    Calls: regress ... eval -> eval -> <Anonymous> -> model.frame.default -> eval
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-solaris-x86, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.0.5
Check: re-building of vignette outputs
Result: WARN
    Error in re-building vignettes:
     ...
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Quitting from lines 92-93 (regress_intro.Rmd)
    Error: processing vignette 'regress_intro.Rmd' failed with diagnostics:
    object 'ttodth' not found
    Execution halted
Flavors: r-patched-solaris-x86, r-release-osx-x86_64