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Type 'q()' to quit R. > x <- c(11178.4,9516.4,12102.8,12989.0,11610.2,10205.5,11356.2,11307.1,12648.6,11947.2,11714.1,12192.5,11268.8,9097.4,12639.8,13040.1,11687.3,11191.7,11391.9,11793.1,13933.2,12778.1,11810.3,13698.4,11956.6,10723.8,13938.9,13979.8,13807.4,12973.9,12509.8,12934.1,14908.3,13772.1,13012.6,14049.9,11816.5,11593.2,14466.2,13615.9,14733.9,13880.7,13527.5,13584.0,16170.2,13260.6,14741.9,15486.5,13154.5,12621.2,15031.6,15452.4,15428,13105.9,14716.8,14180.0,16202.2,14392.4,15140.6,15960.1,14351.3,13230.2,15202.1,17157.3,16159.1,13405.7,17224.7,17338.4,17370.6,18817.8,16593.2,17979.5,17015.2) > #'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!) > x <-sort(x[!is.na(x)]) > q1 <- function(data,n,p,i,f) { + np <- n*p; + i <<- floor(np) + f <<- np - i + qvalue <- (1-f)*data[i] + f*data[i+1] + } > q2 <- function(data,n,p,i,f) { + np <- (n+1)*p + i <<- floor(np) + f <<- np - i + qvalue <- (1-f)*data[i] + f*data[i+1] + } > q3 <- function(data,n,p,i,f) { + np <- n*p + i <<- floor(np) + f <<- np - i + if (f==0) { + qvalue <- data[i] + } else { + qvalue <- data[i+1] + } + } > q4 <- function(data,n,p,i,f) { + np <- n*p + i <<- floor(np) + f <<- np - i + if (f==0) { + qvalue <- (data[i]+data[i+1])/2 + } else { + qvalue <- data[i+1] + } + } > q5 <- function(data,n,p,i,f) { + np <- (n-1)*p + i <<- floor(np) + f <<- np - i + if (f==0) { + qvalue <- data[i+1] + } else { + qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) + } + } > q6 <- function(data,n,p,i,f) { + np <- n*p+0.5 + i <<- floor(np) + f <<- np - i + qvalue <- data[i] + } > q7 <- function(data,n,p,i,f) { + np <- (n+1)*p + i <<- floor(np) + f <<- np - i + if (f==0) { + qvalue <- data[i] + } else { + qvalue <- f*data[i] + (1-f)*data[i+1] + } + } > q8 <- function(data,n,p,i,f) { + np <- (n+1)*p + i <<- floor(np) + f <<- np - i + if (f==0) { + qvalue <- data[i] + } else { + if (f == 0.5) { + qvalue <- (data[i]+data[i+1])/2 + } else { + if (f < 0.5) { + qvalue <- data[i] + } else { + qvalue <- data[i+1] + } + } + } + } > lx <- length(x) > qval <- array(NA,dim=c(99,8)) > mystep <- 25 > mystart <- 25 > if (lx>10){ + mystep=10 + mystart=10 + } > if (lx>20){ + mystep=5 + mystart=5 + } > if (lx>50){ + mystep=2 + mystart=2 + } > if (lx>=100){ + mystep=1 + mystart=1 + } > for (perc in seq(mystart,99,mystep)) { + qval[perc,1] <- q1(x,lx,perc/100,i,f) + qval[perc,2] <- q2(x,lx,perc/100,i,f) + qval[perc,3] <- q3(x,lx,perc/100,i,f) + qval[perc,4] <- q4(x,lx,perc/100,i,f) + qval[perc,5] <- q5(x,lx,perc/100,i,f) + qval[perc,6] <- q6(x,lx,perc/100,i,f) + qval[perc,7] <- q7(x,lx,perc/100,i,f) + qval[perc,8] <- q8(x,lx,perc/100,i,f) + } > postscript(file="/var/www/html/rcomp/tmp/1ffrq1224514757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > myqqnorm <- qqnorm(x,col=2) > qqline(x) > grid() > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'p',1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_1.htm', 'Weighted Average at Xnp',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE) > a<-table.element(a,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),1,TRUE) > a<-table.row.end(a) > for (perc in seq(mystart,99,mystep)) { + a<-table.row.start(a) + a<-table.element(a,round(perc/100,2),1,TRUE) + for (j in 1:8) { + a<-table.element(a,round(qval[perc,j],6)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2njg31224514757.tab") > > system("convert tmp/1ffrq1224514757.ps tmp/1ffrq1224514757.png") > > > proc.time() user system elapsed 0.778 0.189 0.850