R version 2.10.0 (2009-10-26)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> library(MASS)
> 
> firms <- c("MYLAN","NOVOPHARM","LEMMON","GENEVA","COPLEY_PHARM","ROXANE_LABS",
+            "PUREPAC_PHARM","WATSON_LABS","MUTUAL_PHARM","OTHER")
> 
> ps.options(horizontal=FALSE,onefile=FALSE)
> ps.options(pagecentre=TRUE)
> ps.options(paper="letter")
> ps.options(width=7.0,height=9.0)
>   
> filename <- "an.usrvar.flt.Xave.dat"  
> 
> tmp <- scan(filename)
Read 125 items
> rows <- tmp[1]
> cols <- tmp[2]
> Xave <- matrix(tmp[3:(2+rows*cols)],nrow=rows,ncol=cols)
> 
> nfirm <- rows
> 
> filename <- "an.usrvar.flt.Yave.dat"  
> 
> tmp <- scan(filename)
Read 289 items
> rows <- tmp[1]
> cols <- tmp[2]
> Yave <- matrix(tmp[3:(2+rows*cols)],nrow=rows,ncol=cols)
> 
> filename <- "an.usrvar.flt.Acer.dat"  
> 
> tmp <- scan(filename)
Read 131 items
> rows <- tmp[1]
> cols <- tmp[2]
> Acer <- matrix(tmp[3:(2+rows*cols)],nrow=rows,ncol=cols)
> 
> filename <- "an.usrvar.flt.Aave.dat"  
> 
> tmp <- scan(filename)
Read 125 items
> rows <- tmp[1]
> cols <- tmp[2]
> Aave <- matrix(tmp[3:(2+rows*cols)],nrow=rows,ncol=cols)
> 
> logCu <- Xave
> A <- Yave[1:nfirm,]
> logCk <- Yave[(nfirm+1):(nfirm+nfirm),]
> logPi <- Yave[nfirm+nfirm+1,]
> 
> logC <- logCu + logCk
> 
> maxlogC <- max(logC)
> minlogC <- min(logC)
> 
> maxlogPi <- max(logPi)
> minlogPi <- min(logPi)
> 
> n <- ncol(logC)
> 
> idx <- seq(1,n)
> 
> maxidx <- max(idx)
> minidx <- min(idx)
> 
> N <- mat.or.vec(1,n)
> for (i in 1:nfirm) N <- N + A[i,]
> 
> offset <- 0.5
> 
> loline <- mat.or.vec(1,n)
> for (i in 1:n) loline[i] <- min(logPi-offset)
> 
> filename <- paste("an.usrvar.flt.logCR.",nfirm,"f.eps",sep="")
> postscript(file=filename)
> par(mfrow=c((nfirm+1),1),mar=c(2.5,4,1.6,2)+0.1) # mar=c(bottom,left,top,right)
> 
> for (i in 1:nfirm) {
+   plot(c(minidx,maxidx),c(minlogC-maxlogPi,maxlogC-minlogPi),
+     type="n",xlab="",ylab="")
+     title(paste(firms[i],"'s log cost - log total revenue ",sep=""))
+     lines(idx,logC[i,]-logPi,lty="solid")
+     for (j in 1:n) {
+       if (A[i,j] == 1) { points(idx[j],logC[i,j]-logPi[j],pch="o") }
+     }
+ }
> 
> plot(c(idx,idx),c(logPi,logPi-offset),type="n",xlab="",ylab="")
>   title("log total revenue")
>   lines(idx,logPi,lty="solid")
>   points(idx,loline+0.1,pch=as.character(N))
> 
> dev.off()
null device 
          1 
> 
> filename <- paste("an.usrvar.flt.logC.",nfirm,"f.eps",sep="")
> postscript(file=filename)
> par(mfrow=c((nfirm+1),1),mar=c(2.5,4,1.6,2)+0.1) # mar=c(bottom,left,top,right)
> 
> for (i in 1:nfirm) {
+   plot(c(minidx,maxidx),c(minlogC,maxlogC),type="n",xlab="",ylab="")
+     title(paste(firms[i],"'s log cost",sep=""))
+     lines(idx,logC[i,],lty="solid")
+     for (j in 1:n) {
+       if (A[i,j] == 1) { points(idx[j],logC[i,j],pch="o") }
+     }
+ }
> 
> plot(c(idx,idx),c(logPi,logPi-offset),type="n",xlab="",ylab="")
>   title("log total revenue")
>   lines(idx,logPi,lty="solid")
>   points(idx,loline+0.1,pch=as.character(N))
> 
> dev.off()
null device 
          1 
> 
> ps.options(horizontal=FALSE,onefile=FALSE)
> ps.options(pagecentre=TRUE)
> ps.options(paper="letter")
> ps.options(width=7.0,height=5.0)
> 
> offset <- 0.15
> for (i in 1:n) loline[i] <- -offset 
> 
> filename <- paste("an.usrvar.flt.Acer.",nfirm,"f.eps",sep="")
> postscript(file=filename)
> par(mfrow=c((nfirm),1),mar=c(2.5,4,1.6,2)+0.01) # mar=c(bottom,left,top,right)
> 
> for (i in 1:nfirm) {
+   plot(c(minidx,maxidx),c(-offset,1),
+     type="n",xlab="",ylab="")
+     title(paste(firms[i],"'s classification error rate ",sep=""))
+     lines(idx,Acer[i,1:n],lty="solid")
+     points(idx,loline,pch=as.character(A[i,]))
+ }
> 
> print(" ")
[1] " "
> print("cer per firm")
[1] "cer per firm"
> print(" ")
[1] " "
> print(Acer[,n+1])
[1] 0.10956555 0.09627477 0.11837843
> print("overall cer")
[1] "overall cer"
> print(Acer[1,n+2])
[1] 0.1080729
> 
> dev.off()
null device 
          1 
> 
> filename <- paste("an.usrvar.flt.Aave.",nfirm,"f.eps",sep="")
> postscript(file=filename)
> par(mfrow=c((nfirm),1),mar=c(2.5,4,1.6,2)+0.01) # mar=c(bottom,left,top,right)
> 
> for (i in 1:nfirm) {
+   plot(c(minidx,maxidx),c(0,1),
+   #plot(c(minidx,maxidx),c(-offset,1),
+     type="n",xlab="",ylab="")
+     title(paste(firms[i],"'s entry decisions",sep=""))
+     #lines(idx,Aave[i,1:n],lty="solid")
+     points(idx,Aave[i,],pch="x")
+     #points(idx,loline,pch=as.character(A[i,]))
+     points(idx,A[i,],pch="o")
+ }
> 
> print(" ")
[1] " "
> print("cer per firm")
[1] "cer per firm"
> print(" ")
[1] " "
> print(Acer[,n+1])
[1] 0.10956555 0.09627477 0.11837843
> print("overall cer")
[1] "overall cer"
> print(Acer[1,n+2])
[1] 0.1080729
> 
> dev.off()
null device 
          1 
> 
> 
> proc.time()
   user  system elapsed 
  0.243   0.023   0.262