CRAN Package Check Results for Package conformal

Last updated on 2018-02-21 15:48:48 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2 8.94 106.83 115.77 ERROR
r-devel-linux-x86_64-debian-gcc 0.2 7.13 84.06 91.19 ERROR
r-devel-linux-x86_64-fedora-clang 0.2 139.44 ERROR
r-devel-linux-x86_64-fedora-gcc 0.2 135.92 ERROR
r-devel-windows-ix86+x86_64 0.2 18.00 122.00 140.00 ERROR
r-patched-linux-x86_64 0.2 9.53 109.63 119.16 ERROR
r-patched-solaris-x86 0.2 213.10 ERROR
r-release-linux-x86_64 0.2 7.63 107.87 115.50 ERROR
r-release-windows-ix86+x86_64 0.2 27.00 158.00 185.00 ERROR
r-release-osx-x86_64 0.2 OK
r-oldrel-windows-ix86+x86_64 0.2 20.00 175.00 195.00 ERROR
r-oldrel-osx-x86_64 0.2 OK

Check Details

Version: 0.2
Check: examples
Result: ERROR
    Running examples in ‘conformal-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: ConformalRegression
    > ### Title: Class ConformalRegression: Conformal Prediction for Regression
    > ### Aliases: ConformalRegression
    >
    > ### ** Examples
    >
    >
    > showClass("ConformalRegression")
    Class "ConformalRegression" [package "conformal"]
    
    Slots:
    
    Name: .xData
    Class: environment
    
    Extends:
    Class "envRefClass", directly
    Class ".environment", by class "envRefClass", distance 2
    Class "refClass", by class "envRefClass", distance 2
    Class "environment", by class "envRefClass", distance 3, with explicit coerce
    Class "refObject", by class "envRefClass", distance 3
    > #############################################
    > ### Example
    > #############################################
    >
    > ## NOTE: the model built in this example has low predictive power as
    > ## only little fraction of the training data set is used in order
    > ## to make the example quick to run.
    > ## Thus, the example merely intends to illustrate the code.
    >
    > # Optional for parallel training
    > #library(doMC)
    > #registerDoMC(cores=4)
    >
    > data(LogS)
    >
    > # Remove part of the data to allow for quick training
    > LogSTrain <- LogSTrain[1:20]
    > LogSTest <- LogSTest[1:20]
    > LogSDescsTrain <- LogSDescsTrain[1:20,]
    > LogSDescsTest <- LogSDescsTest[1:20,]
    >
    > algorithm <- "svmRadial"
    > tune.grid <- expand.grid(.sigma = expGrid(power.from=-10, power.to=-6, power.by=2, base=2),
    + .C = c(1,10,100))
    > trControl <- trainControl(method = "cv", number=5,savePredictions=TRUE)
    > set.seed(1)
    > model <- train(LogSDescsTrain, LogSTrain, algorithm,
    + tuneGrid=tune.grid,
    + trControl=trControl)
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    >
    >
    > # Train an error model
    > error_model <- ErrorModel(PointPredictionModel=model,x.train=LogSDescsTrain,
    + savePredictions=TRUE,algorithm=algorithm,
    + trControl=trControl,
    + tune.grid=tune.grid)
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    >
    > # Instantiate the class and get the confidence intervals
    > example <- ConformalRegression$new()
    Conformal Prediction Class for Regression Instantiated
    > example$CalculateAlphas(model=model,error_model=error_model,ConformityMeasure=StandardMeasure)
    [1] "Calculating alphas.."
    
    > example$GetConfidenceIntervals(new.data=LogSDescsTest)
    [1] "Predicting (i) the value, and (ii) the error for the new data.."
    
    Error in UseMethod("predict") :
     no applicable method for 'predict' applied to an object of class "c('ksvm', 'vm')"
    Calls: <Anonymous> -> as.vector -> predict
    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: 0.2
Check: examples
Result: ERROR
    Running examples in ‘conformal-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: ConformalRegression
    > ### Title: Class ConformalRegression: Conformal Prediction for Regression
    > ### Aliases: ConformalRegression
    >
    > ### ** Examples
    >
    >
    > showClass("ConformalRegression")
    Class "ConformalRegression" [package "conformal"]
    
    Slots:
    
    Name: .xData
    Class: environment
    
    Extends:
    Class "envRefClass", directly
    Class ".environment", by class "envRefClass", distance 2
    Class "refClass", by class "envRefClass", distance 2
    Class "environment", by class "envRefClass", distance 3, with explicit coerce
    Class "refObject", by class "envRefClass", distance 3
    > #############################################
    > ### Example
    > #############################################
    >
    > ## NOTE: the model built in this example has low predictive power as
    > ## only little fraction of the training data set is used in order
    > ## to make the example quick to run.
    > ## Thus, the example merely intends to illustrate the code.
    >
    > # Optional for parallel training
    > #library(doMC)
    > #registerDoMC(cores=4)
    >
    > data(LogS)
    >
    > # Remove part of the data to allow for quick training
    > LogSTrain <- LogSTrain[1:20]
    > LogSTest <- LogSTest[1:20]
    > LogSDescsTrain <- LogSDescsTrain[1:20,]
    > LogSDescsTest <- LogSDescsTest[1:20,]
    >
    > algorithm <- "svmRadial"
    > tune.grid <- expand.grid(.sigma = expGrid(power.from=-10, power.to=-6, power.by=2, base=2),
    + .C = c(1,10,100))
    > trControl <- trainControl(method = "cv", number=5,savePredictions=TRUE)
    > set.seed(1)
    > model <- train(LogSDescsTrain, LogSTrain, algorithm,
    + tuneGrid=tune.grid,
    + trControl=trControl)
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    >
    >
    > # Train an error model
    > error_model <- ErrorModel(PointPredictionModel=model,x.train=LogSDescsTrain,
    + savePredictions=TRUE,algorithm=algorithm,
    + trControl=trControl,
    + tune.grid=tune.grid)
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    Warning in .local(x, ...) : Variable(s) `' constant. Cannot scale data.
    >
    > # Instantiate the class and get the confidence intervals
    > example <- ConformalRegression$new()
    Conformal Prediction Class for Regression Instantiated
    > example$CalculateAlphas(model=model,error_model=error_model,ConformityMeasure=StandardMeasure)
    [1] "Calculating alphas.."
    
    > example$GetConfidenceIntervals(new.data=LogSDescsTest)
    [1] "Predicting (i) the value, and (ii) the error for the new data.."
    
    Error in UseMethod("predict") :
     no applicable method for 'predict' applied to an object of class "c('ksvm', 'vm')"
    Calls: <Anonymous> -> as.vector -> predict
    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-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64