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Commit made by the Bioconductor Git-SVN bridge. Consists of 3 commits.

Commit information:

Commit id: 285a731a280125b1ac46a811da37189b02ae629f

fix missing seealso in Rd files

Committed by: Ben Bolstad
Author Name: Ben Bolstad
Commit date: 2014-09-05 19:17:51 -0700
Author date: 2014-09-05 19:17:51 -0700

Commit id: 193c6f8f1cc678d8e2c89260bc49af23d5d2f6b9

Remove Depends: methods (not needed)

Committed by: Ben Bolstad
Author Name: Ben Bolstad
Commit date: 2014-09-05 19:01:16 -0700
Author date: 2014-09-05 19:01:16 -0700

Commit id: 046edd2b6a073a4546ef574657194ff644dd2b93

fix various c compiler warnings

Committed by: Ben Bolstad
Author Name: Ben Bolstad
Commit date: 2014-09-05 18:58:17 -0700
Author date: 2014-09-05 18:58:17 -0700


git-svn-id: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/preprocessCore@93882 bc3139a8-67e5-0310-9ffc-ced21a209358

bolstad authored on 06/09/2014 02:18:32
Showing9 changed files

... ...
@@ -1,9 +1,8 @@
1 1
 Package: preprocessCore
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-Version: 1.27.4
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+Version: 1.27.7
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 Title: A collection of pre-processing functions
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 Author: Benjamin Milo Bolstad <bmb@bmbolstad.com>
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 Maintainer: Benjamin Milo Bolstad <bmb@bmbolstad.com>
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-Depends: methods
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 Imports: stats
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 Description: A library of core preprocessing routines 
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 License: LGPL (>= 2)
... ...
@@ -32,8 +32,7 @@ rcModelPLMd(y,group.labels)
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   Next the residuals for each row are compared to the group variable. In cases
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   where there appears to be a significant relationship, the row-effect is "split" and separate row-effect parameters, one for each group, replace the single row effect.
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 }
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-\seealso{
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-}
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+\seealso{\code{\link{rcModelPLM}},\code{\link{rcModelPLMr}}}
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 \examples{
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 col.effects <- c(10,11,10.5,12,9.5)
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 row.effects <- c(seq(-0.5,-0.1,by=0.1),seq(0.1,0.5,by=0.1))
... ...
@@ -63,4 +62,4 @@ matplot(rcModelPLMd(y,group.labels=c(1,1,1,2,2,2))$Residuals,col=c(rep("red",3),
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 }
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 \author{B. M. Bolstad \email{bmb@bmbolstad.com}}
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-\keyword{models}
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\ No newline at end of file
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+\keyword{models}
... ...
@@ -50,8 +50,7 @@ rcModelWPLMrc(y, w)
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 }
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-\seealso{
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-}
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+\seealso{\code{\link{rcModelPLM}},\code{\link{rcModelPLMd}}}
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 \examples{
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 col.effects <- c(10,11,10.5,12,9.5)
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 row.effects <- c(seq(-0.5,-0.1,by=0.1),seq(0.1,0.5,by=0.1))
... ...
@@ -116,4 +115,4 @@ matplot(y,type="l")
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 }
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 \author{B. M. Bolstad \email{bmb@bmbolstad.com}}
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-\keyword{models}
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\ No newline at end of file
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+\keyword{models}
... ...
@@ -43,8 +43,7 @@ rcModelMedianPolish(y)
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        The function \code{rcModelMedianPolish} uses the median polish algorithm.
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 }
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-\seealso{
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-}
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+\seealso{\code{\link{rcModelPLMr}},\code{\link{rcModelPLMd}}}
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 \examples{
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 col.effects <- c(10,11,10.5,12,9.5)
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 row.effects <- c(seq(-0.5,-0.1,by=0.1),seq(0.1,0.5,by=0.1))
... ...
@@ -78,4 +77,4 @@ rcModelWPLM(y,w,row.effects=row.effects,input.scale=1.0)
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 }
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 \author{B. M. Bolstad \email{bmb@bmbolstad.com}}
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-\keyword{models}
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\ No newline at end of file
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+\keyword{models}
... ...
@@ -47,8 +47,8 @@ subrcModelMedianPolish(y, group.labels)
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        The function \code{rcModelMedianPolish} uses the median polish algorithm.
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 }
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-\seealso{
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-}
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+\seealso{\link{rcModelPLM}}
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+
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 \examples{
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 y <- matrix(c(10+rnorm(50),20+rnorm(50)),20,5,byrow=TRUE)
... ...
@@ -77,7 +77,7 @@ SEXP R_rlm_rma_default_model(SEXP Y, SEXP PsiCode, SEXP PsiK, SEXP Scales){
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   double *weights;
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   double *se;
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-  double scale=-1.0;
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+  /* double scale=-1.0; */
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   double *scaleptr;
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   double residSE;
... ...
@@ -187,7 +187,7 @@ SEXP R_wrlm_rma_default_model(SEXP Y, SEXP PsiCode, SEXP PsiK, SEXP Weights, SEX
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   double *weights;
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   double *se;
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-  double scale=-1.0;
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+  /* double scale=-1.0;*/
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   double *scaleptr;
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   double residSE;
... ...
@@ -303,8 +303,8 @@ SEXP R_medianpolish_rma_default_model(SEXP Y){
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   double *beta;
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   double *residuals;
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-  double *weights;
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-  double *se;
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+  /*double *weights;
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+    double *se; */
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   double intercept;
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... ...
@@ -136,7 +136,7 @@ static double AvgSE(double *x, double mean, size_t length){
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  */
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 void colaverage_no_copy(double *data, size_t rows, size_t cols, double *results, double *resultsSE){
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-  int i,j;
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+  int j;
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   for (j = 0; j < cols; j++){
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     results[j] = Avg(&data[j*rows],rows);
... ...
@@ -140,7 +140,7 @@ void logmedian(double *data, size_t rows, size_t cols, double *results, double *
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 void logmedian_no_copy(double *data, size_t rows, size_t cols, double *results, double *resultsSE){
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-  size_t i,j;
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+  size_t j;
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   for (j=0; j < cols; j++){
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     results[j] = log_median(&data[j*rows],rows); 
... ...
@@ -214,7 +214,7 @@ void colmedian(double *data, size_t rows, size_t cols, double *results, double *
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 void colmedian_no_copy(double *data, size_t rows, size_t cols, double *results, double *resultsSE){
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-  size_t i,j;
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+  size_t j;
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   for (j=0; j < cols; j++){
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     results[j] = colmedian_wrapper(&data[j*rows],rows);