caTools (version 1.10)

caTools-package: Tools: moving window statistics, GIF, Base64, ROC AUC, etc.

Description

Contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off error free sum and cumsum, etc.

docType

package

Details

ll{ Package: caTools Version: 1.6 Date: Apr 11 2006 Depends: R (>= 2.2.0), bitops Suggests: MASS, rpart License: The caMassClass Software License, Version 1.0 (See COPYING file or http://ncicb.nci.nih.gov/download/camassclasslicense.jsp) URL: http://ncicb.nci.nih.gov/download/index.jsp Built: R 2.2.1; i386-pc-mingw32; 2006-04-14 10:45:20; windows } Index: LogitBoost LogitBoost Classification Algorithm predict.LogitBoost Prediction Based on LogitBoost Algorithm base64encode Convert R vectors to/from the Base64 format colAUC Column-wise Area Under ROC Curve (AUC) combs All Combinations of k Elements from Vector v read.ENVI Read and Write Binary Data in ENVI Format read.gif Read and Write Images in GIF format runmean Mean of a Moving Window runmin Minimum and Maximum of Moving Windows runquantile Quantile of Moving Window runmad Median Absolute Deviation of Moving Windows runsd Standard Deviation of Moving Windows sample.split Split Data into Test and Train Set sum.exact Basic Sum Operations without Round-off Errors trapz Trapezoid Rule Numerical Integration

Examples

# GIF image read & write
  write.gif( volcano, "volcano.gif", col=terrain.colors, flip=TRUE, 
           scale="always", comment="Maunga Whau Volcano")
  y = read.gif("volcano.gif", verbose=TRUE, flip=TRUE)
  image(y$image, col=y$col, main=y$comment, asp=1)

  # test runmin, runmax and runmed
  k=25; n=200;
  x = rnorm(n,sd=30) + abs(seq(n)-n/4)
  col = c("black", "red", "green", "brown", "blue", "magenta", "cyan")
  plot(x, col=col[1], main = "Moving Window Analysis Functions (window size=25)")
  lines(runmin (x,k), col=col[2])
  lines(runmed (x,k), col=col[3])
  lines(runmean(x,k), col=col[4])
  lines(runmax (x,k), col=col[5])
  legend(0,.9*n, c("data", "runmin", "runmed", "runmean", "runmax"), col=col, lty=1 )

  # sum vs. sum.exact
  x = c(1, 1e20, 1e40, -1e40, -1e20, -1)
  a = sum(x);          print(a)
  b = sum.exact(x);    print(b)