version 2.1

DESCRIPTION

@@ -1,14 +1,14 @@
 Package: npmv
 Type: Package
 Title: Nonparametric Comparison of Multivariate Samples
-Version: 2.0
-Date: 2013-07-03
+Version: 2.1
+Date: 2013-11-24
 Author: Woodrow Burchett and Amanda Ellis
-Maintainer: Woodrow Burchett <woodrow.burchett@uky.edu>
+Maintainer: Amanda Ellis <arelli4@uky.edu>
 Description: Performs analysis of one-way multivariate data, for small samples using Nonparametric techniques. Using approximations for ANOVA Type, Wilks' Lambda, Lawley Hotelling, and Bartlett Nanda Pillai Test statics, the package compares the multivariate distributions for a single explanatory variable.  The comparison is also performed using a permutation test for each of the four test statistics. The package also performs an all-subsets algorithm regarding variables and regarding factor levels. 
-Depends: Formula
+Depends: Formula, ggplot2
 License: GPL-2
-Packaged: 2013-07-23 14:05:48 UTC; Amanda
+Packaged: 2013-11-25 00:00:58 UTC; Amanda
 NeedsCompilation: no
 Repository: CRAN
-Date/Publication: 2013-07-26 01:27:46
+Date/Publication: 2013-12-04 19:18:17

MD5

@@ -1,10 +1,10 @@
-47057f18068dcf79da7bfac26401f948 *DESCRIPTION
+48ffe5fa480a41724408cfc6285f0fbf *DESCRIPTION
 4bef8f90e730c1780e1f17836fd42624 *NAMESPACE
 44ac709629c95c6dc4f3f38e41b8b1ea *R/basenonpartest.R
-f6fe9ab0fbf5907bcddc170046abbe66 *R/nonpartest.R
-04dd7cdd8ff2c49dbe1eaea5744fe1e2 *R/ssnonpartest.R
+4522d6ad75222398fc705585e0fdae0c *R/nonpartest.R
+426ae858d144748d6bb5105ecb1686e6 *R/ssnonpartest.R
 2b528a89b41c1e33024220baecc5af7a *data/sberry.rda
-5f8634d85ba4801dc44f2eb8d5f2bd16 *man/nonpartest.Rd
-546c72fa3a16f6f9f6c968edd8882563 *man/npmv-package.Rd
+92716c198052cd08ce32c646ed4f74e5 *man/nonpartest.Rd
+f75f65fa0c722d28a7b8aaa72658fb4b *man/npmv-package.Rd
 fba438f751e7c535a814474f5dc7d395 *man/sberry.Rd
-b1d4f47ad1d6d73c0ec024aa371897e2 *man/ssnonpartest.Rd
+fcda1e6a4074fa2e69d62a73cd78c405 *man/ssnonpartest.Rd

R/nonpartest.R

@@ -9,7 +9,7 @@ nonpartest <- function(formula,data,permtest=TRUE,permreps=10000,plots=TRUE,test
   formula=Formula(formula)
   frame=model.frame(formula,data=data)
 
-  #Assigns group variable and response variables
+#Assigns group variable and response variables
   groupvar.location=length(frame[1,])
   groupvar=names(frame)[groupvar.location]
   vars=names(frame)[1:(groupvar.location-1)]
@@ -19,17 +19,6 @@ nonpartest <- function(formula,data,permtest=TRUE,permreps=10000,plots=TRUE,test
       return('Error: Missing Data')
    }
 
-   if(plots){
-      if (length(vars) > 1)
-      {
-         oask <- devAskNewPage(TRUE)
-         on.exit(devAskNewPage(oask))
-      }
-
-      for(i in 1:length(vars)){
-         boxplot(frame[,vars[i]]~frame[,groupvar],data=frame,main=vars[i],ylab=vars[i],xlab=names(frame)[1])
-      }
-   }
 
    if(!is.factor(frame[,groupvar]))
    {
@@ -53,8 +42,35 @@ nonpartest <- function(formula,data,permtest=TRUE,permreps=10000,plots=TRUE,test
    }
 
    if(sum(ssize<2)>0){return('Error: Each group must have sample size of at least 2')}
-
-   # Sets up R matrix
+
+#Plot
+  if(plots==TRUE && max(ssize)>10){
+    if (length(vars) > 1)
+    {
+      oask <- devAskNewPage(TRUE)
+      on.exit(devAskNewPage(oask))
+    }
+
+    for(i in 1:length(vars)){
+    boxplot(frame[,vars[i]]~frame[,groupvar],data=frame,main=vars[i],ylab=vars[i],xlab=names(frame)[groupvar.location])
+    }
+
+  }
+
+  if(plots==TRUE && max(ssize)<=10){
+    if (length(vars) > 1)
+    {
+      oask <- devAskNewPage(TRUE)
+      on.exit(devAskNewPage(oask))
+    }
+    for(i in 1:length(vars)){
+    plot=qplot(frame[,groupvar],frame[,vars[i]],data=frame,main=vars[i],ylab=vars[i],xlab=names(frame)[groupvar.location])
+    print(plot)
+    }
+  }
+
+
+# Sets up R matrix
    Rmat <- matrix(NA,N,p)
 
    for(j in 1:p){
@@ -106,15 +122,15 @@ nonpartest <- function(formula,data,permtest=TRUE,permreps=10000,plots=TRUE,test
 
       for(i in 1:a){
          for(j in 1:p){
-            rel[i,j] <- (1/N)*(mean(Rmat[which(frame[,groupvar]==levels(frame[,groupvar])[i]),j])-.5)
+            rel[i,j] <- signif((1/N)*(mean(Rmat[which(frame[,groupvar]==levels(frame[,groupvar])[i]),j])-.5),digits=5)
          }
       }
 
       if(a == 2){
          origrel <- rel
          for(j in 1:p){
-            rel[1,j] <- origrel[1,j] - origrel[2,j] + .5
-            rel[2,j] <- origrel[2,j] - origrel[1,j] + .5
+            rel[1,j] <- signif(origrel[1,j] - origrel[2,j] + .5,digits=5)
+            rel[2,j] <- signif(origrel[2,j] - origrel[1,j] + .5,digits=5)
          }
       }
    }