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Data:
1.57374261731945e-11 -7.78930535948257e-10 -9.9175708985985e-11 -6.17827740269557e-10 2.80917788736100e-10 -1.99763641625773e-10 -5.62280802209156e-10 -3.834963850376e-10 -4.17216827233602e-10 -5.67882584539982e-10 2.58637700997753e-10 -1.90527862999576e-10 -1.71577262349281e-09 -3.35381605481246e-10 -8.96626940018993e-10 -4.10744385478952e-10 -1.49797381174457e-10 -1.15741365009681e-09 4.97758749117844e-10 5.61962186332171e-10 -8.28837144782243e-11 3.00919401758308e-10 -3.56842310474036e-10 -2.65445564649461e-10 1.41088100275876e-09 -1.03460467298531e-10 7.3845130614864e-11 -9.69944238759222e-11 5.131852651389e-10 -7.01634738041197e-10 -1.38560835918767e-10 -7.71959620063928e-10 -7.0799159060927e-10 9.21374878678968e-10 -2.34800895738451e-10 -1.51898308298110e-10 4.14446046879670e-10 1.60789644435293e-10 -5.59704597759589e-10 -1.62599611179260e-10 -2.51259688470892e-10 6.02392608325336e-10 1.40768937817837e-09 8.67663665864935e-10 2.48443566634038e-09 -1.58728692714916e-10 -2.38522160490848e-10 1.69115939544137e-09 4.90955643343371e-09 -4.72645086787659e-11 -8.42090559114202e-10 -9.78841734822696e-10 5.33492432359219e-10 9.43414526915943e-10 3.41369607077995e-10 1.95723637461107e-10 3.00517747585271e-10 -9.1302653563983e-10 -8.67566852412382e-10 5.08551441993418e-10 -4.81913846464095e-09 8.72479910544946e-10 4.49296782533904e-10 5.3731256719039e-10 -7.49441166608007e-10 7.73568132392035e-10 1.67536877808481e-10 2.03569599537960e-09 5.86636632995461e-11 -6.17168126334066e-10 -3.4433140227747e-10 -8.6322485209947e-10 -3.25333745267874e-09 3.08292515576174e-10 1.19026377148694e-09 9.77788786184594e-10 -4.57474202748115e-11 -1.02595722322947e-10 -9.7138521570781e-10 1.17167162511307e-09 -1.15353929661592e-09 -8.03674125843833e-10 6.27537221374364e-10 -8.74606140260688e-10 1.5572731935976e-09
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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) 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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