========================================================================= Reverse dependency check for hash 3.0.2 ========================================================================= setting value version R version 3.1.0 (2014-04-10) system x86_64, linux-gnu ui RStudio (0.98.1060) language en collate en_US.UTF-8 tz
package * version date source chron 2.3.45 2014-02-11 CRAN (R 3.1.0) data.table * 1.9.4 2014-10-02 CRAN (R 3.1.0) devtools * 1.6.0.9000 2014-10-30 Github (hadley/devtools@5f0e3ed) digest 0.6.4 2013-12-03 CRAN (R 3.1.0) hash * 3.0.2 local magrittr * 1.0.1 2014-05-15 CRAN (R 3.1.0) memoise 0.2.1 2014-04-22 CRAN (R 3.1.0) plyr 1.8.1 2014-02-26 CRAN (R 3.1.0) Rcpp 0.11.1 2014-03-14 CRAN (R 3.1.0) RCurl 1.95.4.1 2013-03-06 CRAN (R 3.1.0) reshape2 1.4 2014-04-23 CRAN (R 3.1.0) roxygen2 4.0.2 2014-09-02 CRAN (R 3.1.0) rstudioapi 0.1 2014-03-27 CRAN (R 3.1.0) stringr 0.6.2 2012-12-06 CRAN (R 3.1.0)
CITAN =================================================================== * checking package dependencies ... ERROR Package required but not available: ‘RGtk2’
See the information on DESCRIPTION files in the chapter ‘Creating R packages’ of the ‘Writing R Extensions’ manual.
GABi ====================================================================
HAP.ROR =================================================================
KoNLP =================================================================== * checking package dependencies ... ERROR Package required but not available: ‘rJava’
See the information on DESCRIPTION files in the chapter ‘Creating R packages’ of the ‘Writing R Extensions’ manual.
MXM ===================================================================== * checking examples ... ERROR Running examples in ‘MXM-Ex.R’ failed The error most likely occurred in:
base::assign(".ptime", proc.time(), pos = "CheckExEnv")
Name: SES
Title: Feature selection algorithm for identifying multiple minimal,
statistically-equivalent and equally-predictive feature signatures.
Aliases: SES
Keywords: SES Multiple Feature Signatures Feature Selection Variable
Selection
** Examples
set.seed(123)
require(gRbase) #for faster computations in the internal functions
require(hash) Loading required package: hash hash-3.0.2 provided by Decision Patterns
simulate a dataset with continuous data
dataset <- matrix(nrow = 1000 , ncol = 300) dataset <- apply(dataset, 1:2, function(i) runif(1, 1, 100))
define a simulated class variable
target = 3dataset[,10] + 2dataset[,200] + 3*dataset[,20] + runif(1, 0, 1);
define some simulated equivalences
dataset[,15] = dataset[,10] dataset[,250] = dataset[,200] dataset[,230] = dataset[,200]
run the SES algorithm
sesObject <- SES(target , dataset , max_k=5 , threshold=0.2 , test="testIndFisher", + hash = TRUE, hashObject=NULL);
Conditional independence test used: testIndFisher error in try catch of the testIndFisher test Here's the original error message: could not find function ".set"Error in value[3L] : Calls: SES ... tryCatch -> tryCatchList -> tryCatchOne -> Execution halted
neuroim =================================================================
orderbook =============================================================== * checking whether package ‘orderbook’ can be installed ... ERROR Installation failed. See ‘/tmp/RtmpH4OO6G/check_cran6a467fa2b45c/orderbook.Rcheck/00install.out’ for details.
rpartitions =============================================================
stream ==================================================================
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