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Type 'q()' to quit R. > x <- c(13768040.14,17487530.67,16198106.13,17535166.38,16571771.60,16198892.67,16554237.93,19554176.37,15903762.33,18003781.65,18329610.38,16260733.42,14851949.20,18174068.44,18406552.23,18466459.42,16016524.60,17428458.32,17167191.42,19629987.60,17183629.01,18344657.85,19301440.71,18147463.68,16192909.22,18374420.60,20515191.95,18957217.20,16471529.53,18746813.27,19009453.59,19211178.55,20547653.75,19325754.03,20605542.58,20056915.06,16141449.72,20359793.22,19711553.27,15638580.70,14384486.00,13855616.12,14308336.46,15290621.44,14423755.53,13779681.49,15686348.94,14733828.17,12522497.94,16189383.57,16059123.25,16007123.26,15806842.33,15159951.13,15692144.17,18908869.11,16969881.42,16997477.78,19858875.65,17681170.13) > #'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/19uwq1291135376.ps",horizontal=F,onefile=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/2cvce1291135376.tab") > try(system("convert tmp/19uwq1291135376.ps tmp/19uwq1291135376.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.544 0.216 1.167