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94.70 90.20 104.30 96.00 96.60 103.50 79.90 88.50 103.30 113.50 100.80 95.30 92.60 89.00 98.70 94.50 96.90 98.10 82.10 86.50 104.10 110.90 114.50 112.20 96.40 92.00 102.00 99.70 102.00 98.90 87.40 94.40 109.30 116.40 101.00 105.50 97.80 95.50 113.70 103.70 100.80 113.80 84.60 95.30 110.00 107.50 107.60 116.00 96.90 97.00 108.10 101.90 107.20 110.20 78.70 96.50 115.20 104.70 109.10 108.40 95.50 97.80 115.10 96.20 112.00 111.80 82.50 100.80 116.00 116.30 116.60 112.90 100.90 104.10 117.40 103.30 111.60 115.20 92.60 106.90
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R Code
library(MASS) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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