R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(list(0
+ ,780.8
+ ,93
+ ,1
+ ,699.1
+ ,193
+ ,1
+ ,598.5
+ ,112
+ ,0
+ ,735.3
+ ,71
+ ,0
+ ,700.5
+ ,105
+ ,0
+ ,706.9
+ ,119
+ ,0
+ ,656.3
+ ,162
+ ,1
+ ,1025.1
+ ,277
+ ,0
+ ,639.4
+ ,96
+ ,0
+ ,637.2
+ ,24
+ ,1
+ ,1065.6
+ ,231
+ ,0
+ ,576.1
+ ,99
+ ,0
+ ,525.6
+ ,27
+ ,1
+ ,377.5
+ ,112
+ ,0
+ ,627.8
+ ,96
+ ,0
+ ,646
+ ,95
+ ,1
+ ,999.31
+ ,143
+ ,1
+ ,168.3
+ ,13
+ ,0
+ ,219.5
+ ,22
+ ,0
+ ,507.4
+ ,27
+ ,1
+ ,227.1
+ ,56
+ ,1
+ ,821.6
+ ,278
+ ,0
+ ,144.7
+ ,10
+ ,0
+ ,761.6
+ ,55
+ ,1
+ ,817.7
+ ,61
+ ,0
+ ,547.8
+ ,44
+ ,0
+ ,313.4
+ ,10
+ ,0
+ ,291.8
+ ,28
+ ,0
+ ,650.3
+ ,53
+ ,0
+ ,679.4
+ ,41
+ ,1
+ ,736.5
+ ,135
+ ,0
+ ,842.6
+ ,85
+ ,0
+ ,904.9
+ ,14
+ ,0
+ ,263.7
+ ,12
+ ,1
+ ,446.5
+ ,93
+ ,0
+ ,511.8
+ ,22
+ ,1
+ ,645.6
+ ,101
+ ,1
+ ,873.9
+ ,201
+ ,0
+ ,871.6
+ ,2
+ ,0
+ ,287.3
+ ,9
+ ,0
+ ,505.7
+ ,49
+ ,1
+ ,597.7
+ ,112
+ ,1
+ ,791
+ ,27
+ ,0
+ ,725.8
+ ,93
+ ,0
+ ,919.4
+ ,49
+ ,0
+ ,114.7
+ ,1
+ ,0
+ ,866.8
+ ,69
+ ,0
+ ,870.7
+ ,108
+ ,0
+ ,700.2
+ ,108
+ ,0
+ ,636.5
+ ,70
+ ,1
+ ,890.3
+ ,165
+ ,0
+ ,879.1
+ ,208
+ ,0
+ ,100.5
+ ,4
+ ,0
+ ,782.8
+ ,153
+ ,0
+ ,738.1
+ ,67
+ ,1
+ ,762.3
+ ,163
+ ,1
+ ,857
+ ,75
+ ,1
+ ,712.5
+ ,238
+ ,1
+ ,609.9
+ ,90
+ ,0
+ ,940.1
+ ,137
+ ,0
+ ,586.7
+ ,133
+ ,1
+ ,49.3
+ ,17
+ ,0
+ ,9.7
+ ,0
+ ,0
+ ,786.7
+ ,33
+ ,1
+ ,755.7
+ ,123
+ ,1
+ ,749.2
+ ,153
+ ,1
+ ,630.1
+ ,126
+ ,0
+ ,835.6
+ ,164
+ ,0
+ ,1024.3
+ ,14
+ ,1
+ ,896.2
+ ,102
+ ,1
+ ,410.7
+ ,16
+ ,0
+ ,120.2
+ ,6
+ ,1
+ ,700.7
+ ,140
+ ,0
+ ,704.8
+ ,120
+ ,0
+ ,1042.4
+ ,124
+ ,1
+ ,831.8
+ ,49
+ ,1
+ ,854.1
+ ,99
+ ,1
+ ,547
+ ,23
+ ,0
+ ,999.4
+ ,80
+ ,0
+ ,532.6
+ ,56
+ ,0
+ ,826.4
+ ,152
+ ,0
+ ,670.9
+ ,78
+ ,1
+ ,837.1
+ ,105
+ ,0
+ ,1032.8
+ ,229
+ ,1
+ ,639.9
+ ,80
+ ,1
+ ,850.4
+ ,144
+ ,1
+ ,845
+ ,54
+ ,1
+ ,984.4
+ ,52
+ ,1
+ ,993.2
+ ,187
+ ,1
+ ,958.3
+ ,117
+ ,0
+ ,832.5
+ ,144
+ ,1
+ ,880.9
+ ,147
+ ,1
+ ,1020.9
+ ,182
+ ,1
+ ,764.8
+ ,117
+ ,1
+ ,601.6
+ ,104
+ ,1
+ ,686.2
+ ,46
+ ,1
+ ,821.2
+ ,138
+ ,0
+ ,836.9
+ ,89
+ ,0
+ ,985.5
+ ,120
+ ,1
+ ,973.2
+ ,314
+ ,1
+ ,702.9
+ ,111
+ ,1
+ ,929.2
+ ,80
+ ,0
+ ,747.2
+ ,187
+ ,1
+ ,654.3
+ ,166
+ ,1
+ ,628.8
+ ,70
+ ,0
+ ,564.6
+ ,91
+ ,0
+ ,981
+ ,202
+ ,1
+ ,705.3
+ ,112
+ ,0
+ ,397.9
+ ,40
+ ,0
+ ,56.3
+ ,2
+ ,1
+ ,929.7
+ ,69
+ ,0
+ ,559.7
+ ,75
+ ,1
+ ,669.2
+ ,78
+ ,0
+ ,923.5
+ ,128
+ ,1
+ ,539.8
+ ,38
+ ,1
+ ,401.7
+ ,19
+ ,0
+ ,923.5
+ ,171
+ ,1
+ ,688.3
+ ,124
+ ,0
+ ,324.5
+ ,4
+ ,1
+ ,613
+ ,27
+ ,0
+ ,930.5
+ ,255
+ ,0
+ ,348.6
+ ,6
+ ,1
+ ,582.9
+ ,143
+ ,1
+ ,919.7
+ ,113
+ ,0
+ ,786.5
+ ,87
+ ,1
+ ,637
+ ,85
+ ,1
+ ,917.1
+ ,110)
+ ,dim=c(3
+ ,127)
+ ,dimnames=list(c('pass'
+ ,'ws'
+ ,'pe')
+ ,1:127))
>  y <- array(NA,dim=c(3,127),dimnames=list(c('pass','ws','pe'),1:127))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(brlr)
> roc.plot <- function (sd, sdc, newplot = TRUE, ...)
+ {
+ sall <- sort(c(sd, sdc))
+ sens <- 0
+ specc <- 0
+ for (i in length(sall):1) {
+ sens <- c(sens, mean(sd >= sall[i], na.rm = T))
+ specc <- c(specc, mean(sdc >= sall[i], na.rm = T))
+ }
+ if (newplot) {
+ plot(specc, sens, xlim = c(0, 1), ylim = c(0, 1), type = 'l',
+ xlab = '1-specificity', ylab = 'sensitivity', main = 'ROC plot', ...)
+ abline(0, 1)
+ }
+ else lines(specc, sens, ...)
+ npoints <- length(sens)
+ area <- sum(0.5 * (sens[-1] + sens[-npoints]) * (specc[-1] -
+ specc[-npoints]))
+ lift <- (sens - specc)[-1]
+ cutoff <- sall[lift == max(lift)][1]
+ sensopt <- sens[-1][lift == max(lift)][1]
+ specopt <- 1 - specc[-1][lift == max(lift)][1]
+ list(area = area, cutoff = cutoff, sensopt = sensopt, specopt = specopt)
+ }
> roc.analysis <- function (object, newdata = NULL, newplot = TRUE, ...)
+ {
+ if (is.null(newdata)) {
+ sd <- object$fitted[object$y == 1]
+ sdc <- object$fitted[object$y == 0]
+ }
+ else {
+ sd <- predict(object, newdata, type = 'response')[newdata$y ==
+ 1]
+ sdc <- predict(object, newdata, type = 'response')[newdata$y ==
+ 0]
+ }
+ roc.plot(sd, sdc, newplot, ...)
+ }
> hosmerlem <- function (y, yhat, g = 10)
+ {
+ cutyhat <- cut(yhat, breaks = quantile(yhat, probs = seq(0,
+ 1, 1/g)), include.lowest = T)
+ obs <- xtabs(cbind(1 - y, y) ~ cutyhat)
+ expect <- xtabs(cbind(1 - yhat, yhat) ~ cutyhat)
+ chisq <- sum((obs - expect)^2/expect)
+ P <- 1 - pchisq(chisq, g - 2)
+ c('X^2' = chisq, Df = g - 2, 'P(>Chi)' = P)
+ }
> x <- as.data.frame(t(y))
> r <- brlr(x)
Warning message:
In brlr(x) : Not converged: gradient values not all zero
> summary(r)
Call:
brlr(formula = x)

Coefficients:
            Value   Std. Error t value
(Intercept) -0.9294  0.5664    -1.6411
ws           0.0001  0.0010     0.0879
pe           0.0080  0.0037     2.1616

Deviance: 166.6604 
Penalized deviance: 137.7453 
Residual df: 124 
> rc <- summary(r)$coeff
> hm <- hosmerlem(y[1,],r$fitted.values)
> hm
      X^2        Df   P(>Chi) 
6.1936207 8.0000000 0.6255534 
> postscript(file="/var/www/html/rcomp/tmp/1y4kt1201950070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> ra <- roc.analysis(r)
> dev.off()
null device 
          1 
> te <- array(0,dim=c(2,99))
> for (i in 1:99) {
+ threshold <- i / 100
+ numcorr1 <- 0
+ numfaul1 <- 0
+ numcorr0 <- 0
+ numfaul0 <- 0
+ for (j in 1:length(r$fitted.values)) {
+ if (y[1,j] > 0.99) {
+ if (r$fitted.values[j] >= threshold) numcorr1 = numcorr1 + 1 else numfaul1 = numfaul1 + 1
+ } else {
+ if (r$fitted.values[j] < threshold) numcorr0 = numcorr0 + 1 else numfaul0 = numfaul0 + 1
+ }
+ }
+ te[1,i] <- numfaul1 / (numfaul1 + numcorr1)
+ te[2,i] <- numfaul0 / (numfaul0 + numcorr0)
+ }
> postscript(file="/var/www/html/rcomp/tmp/21vjy1201950070.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,2))
> plot((1:99)/100,te[1,],xlab='Threshold',ylab='Type I error', main='1 - Specificity')
> plot((1:99)/100,te[2,],xlab='Threshold',ylab='Type II error', main='1 - Sensitivity')
> plot(te[1,],te[2,],xlab='Type I error',ylab='Type II error', main='(1-Sens.) vs (1-Spec.)')
> plot((1:99)/100,te[1,]+te[2,],xlab='Threshold',ylab='Sum of Type I & II error', main='(1-Sens.) + (1-Spec.)')
> par(op)
> dev.off()
null device 
          1 
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Coefficients of Bias-Reduced Logistic Regression',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.E.',header=TRUE)
> a<-table.element(a,'t-stat',header=TRUE)
> a<-table.element(a,'2-sided p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:length(rc[,1])) {
+ a<-table.row.start(a)
+ a<-table.element(a,labels(rc)[[1]][i],header=TRUE)
+ a<-table.element(a,rc[i,1])
+ a<-table.element(a,rc[i,2])
+ a<-table.element(a,rc[i,3])
+ a<-table.element(a,2*(1-pt(abs(rc[i,3]),r$df.residual)))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3zi2s1201950070.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Summary of Bias-Reduced Logistic Regression',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Deviance',1,TRUE)
> a<-table.element(a,r$deviance)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Penalized deviance',1,TRUE)
> a<-table.element(a,r$penalized.deviance)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Residual Degrees of Freedom',1,TRUE)
> a<-table.element(a,r$df.residual)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'ROC Area',1,TRUE)
> a<-table.element(a,ra$area)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Hosmer–Lemeshow test',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Chi-square',1,TRUE)
> a<-table.element(a,hm[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Degrees of Freedom',1,TRUE)
> a<-table.element(a,hm[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'P(>Chi)',1,TRUE)
> a<-table.element(a,hm[3])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4vi5t1201950070.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Fit of Logistic Regression',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Index',1,TRUE)
> a<-table.element(a,'Actual',1,TRUE)
> a<-table.element(a,'Fitted',1,TRUE)
> a<-table.element(a,'Error',1,TRUE)
> a<-table.row.end(a)
> for (i in 1:length(r$fitted.values)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,1,TRUE)
+ a<-table.element(a,y[1,i])
+ a<-table.element(a,r$fitted.values[i])
+ a<-table.element(a,y[1,i]-r$fitted.values[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5u60u1201950070.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Type I & II errors for various threshold values',3,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Threshold',1,TRUE)
> a<-table.element(a,'Type I',1,TRUE)
> a<-table.element(a,'Type II',1,TRUE)
> a<-table.row.end(a)
> for (i in 1:99) {
+ a<-table.row.start(a)
+ a<-table.element(a,i/100,1,TRUE)
+ a<-table.element(a,te[1,i])
+ a<-table.element(a,te[2,i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6kf3b1201950070.tab") 
> 
> system("convert tmp/1y4kt1201950070.ps tmp/1y4kt1201950070.png")
> system("convert tmp/21vjy1201950070.ps tmp/21vjy1201950070.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.412   0.542   2.515