• using R Under development (unstable) (2017-06-21 r72824)
• using platform: x86_64-pc-linux-gnu (64-bit)
• using session charset: UTF-8
• checking for file ‘BigTSP/DESCRIPTION’ ... OK
• checking extension type ... Package
• this is package ‘BigTSP’ version ‘1.0’
• checking package namespace information ... OK
• checking package dependencies ... OK
• checking if this is a source package ... OK
• checking if there is a namespace ... OK
• checking for executable files ... OK
• checking for hidden files and directories ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking whether package ‘BigTSP’ can be installed ... OK
• checking package directory ... OK
• checking DESCRIPTION meta-information ... OK
• checking top-level files ... OK
• checking for left-over files ... OK
• checking index information ... OK
• checking package subdirectories ... OK
• checking R files for non-ASCII characters ... OK
• checking R files for syntax errors ... OK
• checking whether the package can be loaded ... OK
• checking whether the package can be loaded with stated dependencies ... OK
• checking whether the package can be unloaded cleanly ... OK
• checking whether the namespace can be loaded with stated dependencies ... OK
• checking whether the namespace can be unloaded cleanly ... OK
• checking loading without being on the library search path ... OK
• checking use of S3 registration ... OK
• checking dependencies in R code ... NOTE
  Packages in Depends field not imported from:
    ‘gbm’ ‘glmnet’ ‘randomForest’ ‘tree’
    These packages need to be imported from (in the NAMESPACE file)
    for when this namespace is loaded but not attached.
• checking S3 generic/method consistency ... OK
• checking replacement functions ... OK
• checking foreign function calls ... OK
• checking R code for possible problems ... NOTE
  LDCAEst: no visible global function definition for ‘glmnet’
  cv.LDCA: no visible global function definition for ‘cv.glmnet’
  predict.LDCA: no visible global function definition for ‘predict’
  predict.cv.LDCA: no visible global function definition for ‘predict’
  predict.tsp.gbm: no visible global function definition for ‘predict’
  predict.tsp.randomForest: no visible global function definition for
    ‘predict’
  predict.tsp.tree: no visible global function definition for ‘predict’
  tsp.gbm: no visible global function definition for ‘gbm.fit’
  tsp.randomForest: no visible global function definition for
    ‘randomForest’
  tsp.tree: no visible global function definition for ‘tree.control’
  tsp.tree: no visible global function definition for ‘tree’
  Undefined global functions or variables:
    cv.glmnet gbm.fit glmnet predict randomForest tree tree.control
  Consider adding
    importFrom("stats", "predict")
  to your NAMESPACE file.
• checking Rd files ... OK
• checking Rd metadata ... OK
• checking Rd line widths ... NOTE
  Rd file 'predict.LDCA.Rd':
    \usage lines wider than 90 characters:
       predict(object, newx, s = NULL, type = c("link", "response", "coefficients", "nonzero", "class"), exact = FALSE, offset, ...)
  
  Rd file 'predict.tsp.randomForest.Rd':
    \usage lines wider than 90 characters:
       predict(object, newdata, type = "response", norm.votes = TRUE, predict.all = FALSE, proximity = FALSE, nodes = FALSE, cutoff, ...)
  
  Rd file 'predict.tsp.tree.Rd':
    \usage lines wider than 90 characters:
       predict(object, newdata, type = c("vector", "tree", "class", "where"), split = FALSE, nwts, eps = 0.001, ...)
  
  Rd file 'tsp.gbm.Rd':
    \usage lines wider than 90 characters:
       tsp.gbm(x, y, offset = NULL, misc = NULL, distribution = "bernoulli", w = NULL, var.monotone = NULL, n.trees = 100, interaction.depth = ... [TRUNCATED]
  
  Rd file 'tsp.randomForest.Rd':
    \usage lines wider than 90 characters:
       tsp.randomForest(x, y = NULL, xtest = NULL, ytest = NULL, ntree = 500, type = "classification", mtry = if (!is.null(y) && !is.factor(y) ... [TRUNCATED]
  
  Rd file 'tsp.tree.Rd':
    \usage lines wider than 90 characters:
       tsp.tree(X, response, control = tree.control(dim(X)[1], ...), method = "recursive.partition", split = c("deviance", "gini"), x = FALSE, ... [TRUNCATED]
  
  These lines will be truncated in the PDF manual.
• checking Rd cross-references ... OK
• checking for missing documentation entries ... OK
• checking for code/documentation mismatches ... OK
• checking Rd \usage sections ... OK
• checking Rd contents ... OK
• checking for unstated dependencies in examples ... OK
• checking examples ... [5s/5s] OK
• checking PDF version of manual ... OK
• DONE

Status: 3 NOTEs