make runavg _runavg

diff --git a/R/bayesian_analysis.R b/R/bayesian_analysis.R
index 438ee592e98c5580af4ac80c7da222c4e3a4d7d3..24b99ceb41fee5af84229f0a41132c0f718d24ba 100644 (file)
--- a/R/bayesian_analysis.R
+++ b/R/bayesian_analysis.R
@@ -64,7 +64,7 @@ pierre.pair <-  function (h, cs, ce, end, totalexpresscol,
 
 #   running average standard deviation
      xxx <- S.sd[!is.na(S.sd)][order(index.col[!is.na(S.sd)])]
-     xxx <- runavg(xxx, winsize)
+     xxx <- _runavg(xxx, winsize)
      xxx <- xxx[rank(index.col[!is.na(S.sd)])]
      S.rasd <- rep(NA, nrow(h))
      S.rasd[!is.na(S.sd)] <- xxx
@@ -197,28 +197,28 @@ microarray.bayesian <-
   ## average expression level and the running average calculated on
   ## the estimated st. dev. for each locus. All the wierd code is a
   ## work around of missing values
-  cont.sd.runavg <- runavg(cont.sd[order(cont.mean)])[order(order(cont.mean))]
-   exp.sd.runavg <- runavg( exp.sd[order( exp.mean)])[order(order( exp.mean))]
+  cont.sd.runavg <- _runavg(cont.sd[order(cont.mean)])[order(order(cont.mean))]
+   exp.sd.runavg <- _runavg( exp.sd[order( exp.mean)])[order(order( exp.mean))]
   ## xxx <- temp5[!is.na(temp5)][order(temp3[!is.na(temp5)])]
-  ## xxx <- runavg(xxx, winsize)
+  ## xxx <- _runavg(xxx, winsize)
   ## xxx <- xxx[rank(temp3[!is.na(temp5)])]
   ## temp11 <- rep(NA, nrow(h))
   ## temp11[!is.na(temp5)] <- xxx
   ## xxx <- temp6[!is.na(temp6)][order(temp4[!is.na(temp6)])]
-  ## xxx <- runavg(xxx, winsize)
+  ## xxx <- _runavg(xxx, winsize)
   ## xxx <- xxx[rank(temp4[!is.na(temp6)])]
   ## temp12 <- rep(NA, nrow(h))
   ## temp12[!is.na(temp6)] <- xxx
-  cont.sd.log.runavg <- runavg(cont.sd.log[order(cont.mean.log)])[order(order(cont.mean.log))]
-   exp.sd.log.runavg <- runavg( exp.sd.log[order( exp.mean.log)])[order(order( exp.mean.log))]
+  cont.sd.log.runavg <- _runavg(cont.sd.log[order(cont.mean.log)])[order(order(cont.mean.log))]
+   exp.sd.log.runavg <- _runavg( exp.sd.log[order( exp.mean.log)])[order(order( exp.mean.log))]
   ## xxx <- temp9[!is.na(temp9)][order(temp7[!is.na(temp9)])]
-  ## xxx <- runavg(xxx, winsize)
+  ## xxx <- _runavg(xxx, winsize)
   ## xxx <- xxx[rank(temp7[!is.na(temp9)])]
   ## ##   like 11 and 12 but for the log transofrmed data
   ## temp13 <- rep(NA, nrow(h))
   ## temp13[!is.na(temp9)] <- xxx
   ## xxx <- temp10[!is.na(temp10)][order(temp8[!is.na(temp10)])]
-  ## xxx <- runavg(xxx, winsize)
+  ## xxx <- _runavg(xxx, winsize)
   ## xxx <- xxx[rank(temp8[!is.na(temp10)])]
   ## temp14 <- rep(NA, nrow(h))
   ## temp14[!is.na(temp10)] <- xxx
@@ -428,7 +428,7 @@ microarray.bayesian <-
 }
 
 
-runavg <- function(x,k=1){
+_runavg <- function(x,k=1){
   if (k < 0)
     stop("k must be greater than or equal to 0");
   if (k==0)