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Data:
50 68 62 54 71 54 65 73 52 84 42 66 65 78 73 75 72 66 70 61 81 71 69 71 72 68 70 68 61 67 76 70 60 77 72 69 71 62 70 64 58 76 52 59 68 76 65 67 59 69 76 63 75 63 60 73 63 70 75 66 63 63 64 70 75 61 60 62 73 61 66 64 59 64 60 56 66 78 53 67 59 66 68 71 66 73 72 71 59 64 66 78 68 73 62 65 68 65 60 71 65 68 64 74 69 76 68 72 67 63 59 73 66 62 69 66 51 56 67 69 57 56 55 63 67 65 47 76 64 68 64 65 71 63 60 68 72 70 61 61 62 71 71 51 56 70 73 76 59 68 48 52 59 60 59 57 79 60 60 59 62 59 61 71 57 66 63 69 58 59 48 66 73 67 61 68 75 62 69 58 60 74 55 62 63 69 58 58 68 72 62 62 65 69 66 72 62 75 58 66 55 47 72 62 64 64 19 50 68 70 79 69 71 48 66 73 74 66 71 74 78 75 53 60 50 70 69 65 78 78 59 72 70 63 63 71 74 67 66 62 80 73 67 61 73 74 32 69 69 84 64 58 60 59 78 57 60 68 68 73 69 67 60 65 66 74 81 72 55 49 74 53 64 65 57 51 80 67 70 74 75 70 69 65 55 71 65 69 48 69 68 74 67 65 63 74 39 68 69 68 63 67 70 68 66 70 78 59 62 75 74 73 62 69 65 67 73 52 61 53 63 78 65 77 69 68 76 63 41 76 67 69 59 73 72 52 65 63 78 56 68 56 64 68 75 67 55 73 66 75 77 65 75 57 61 71 72 62 66 66 63 60 64 74 59 71 69 63 73 55 77 70 64 78 60 66 77 68 78 68 60 65 64 69 72 50 72 71 80 74 64 69 76 75 79 73 60 76 55 53 62 69 78 68 67 75 59 73 70 59 64 63 67 58 71 79 53 76 66 64 57 67 72 58 74 57 62 74 54 62 66 64 74 71 66 66 63 65 70 66 66 78 77 72 65 67 72 58 84 67 84 58 63 75 55 72 58 69 54 58 67 77 80 67 75 71 72 75 79 76 72 81 52 76 60 72 77 64 67 72 79 40 71 73 75 70 66 66 73 74 58 51 75 70 50 64 77 71
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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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1 seconds
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Big Analytics Cloud Computing Center
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