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Data:
0.913425 -4.08657 3.95844 1.91343 6.91343 7.91343 -0.0865746 4.95844 -1.08657 -12.0416 -0.041565 6.91343 -1.61389 4.91343 1.38611 -0.041565 -1.08657 1.91343 2.91343 -3.04156 -0.041565 4.95844 -0.0865746 -3.04156 -5.08657 -0.0865746 6.91343 -3.04156 1.91343 6.95844 7.91343 -1.04156 -0.041565 -0.041565 -3.04156 -3.04156 -3.04156 -3.08657 0.913425 -7.08657 0.958435 -4.04156 2.95844 4.38611 -3.04156 -2.6589 2.3411 -2.6589 -6.08657 -8.04156 -6.08657 -2.61389 -1.08657 -0.0865746 -3.04156 -4.08657 0.38611 -4.04156 1.38611 -3.04156 -1.04156 5.95844 -0.658899 1.38611 -3.61389 -1.08657 2.91343 6.91343 5.3411 2.95844 -1.08657 5.91343 -2.04156 2.95844 3.95844 -4.61389 0.913425 -6.04156 1.38611 -1.61389 2.38611 -0.041565 -4.04156 -1.6589 -4.6589 -0.658899 3.38611 0.958435 -3.6589 2.38611 2.91343 2.3411 -3.08657 5.3411 -2.08657 0.38611 -4.04156 0.958435 7.38611 0.38611 -1.6589 -6.04156 1.38611 1.91343 6.38611 4.95844 3.3411 -1.61389 -0.658899 1.91343 -3.61389 -2.08657 0.958435 3.3411 2.95844 -1.6589 3.91343 5.3411 0.38611 -3.6589 4.3411 6.95844 2.91343 5.91343 -5.08657 -6.08657 5.95844 5.91343 -1.61389 -3.61389 -3.6589 3.95844 -0.0865746 -0.658899 -5.04156 4.95844 -3.6589 -5.08657 3.3411 0.913425 -6.04156 -1.6589 -4.08657 1.3411 0.341101 3.95844 2.95844 1.91343 -9.61389 -3.6589 3.3411 6.95844 -7.08657 3.38611 0.341101 3.38611 -0.61389 -7.6589 4.3411 2.91343 -0.0865746 -2.61389 -3.04156 -6.6589 -8.04156 -0.041565 -0.658899 -1.6589 -5.08657 -2.08657 -5.08657 -10.0866 0.341101 -1.6589 6.38611 4.3411 0.38611 4.38611 -1.6589 -6.6589 1.91343 3.3411 5.91343 1.91343 -1.6589 5.95844 2.91343 0.913425 5.3411 0.38611 -4.6589 0.341101 4.91343 -2.08657 -0.041565 2.3411 0.341101 -3.61389 2.38611 1.3411 -2.08657 -1.08657 -5.08657 -0.61389 -1.6589 -4.61389 0.341101
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R Code
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) } bitmap(file='test1.png') myqqnorm <- qqnorm(x,col=2) qqline(x) grid() dev.off() load(file='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='mytable.tab')
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