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98.50 96.70 113.10 100.00 104.70 108.50 90.50 88.60 105.40 119.90 107.20 84.10 101.40 105.10 118.70 113.80 113.80 118.90 98.50 91.00 120.70 127.90 112.40 93.10 107.50 107.30 114.80 120.80 112.20 123.30 100.60 86.70 123.60 125.30 111.10 98.40 102.30 105.00 128.20 124.70 116.10 131.20 97.70 88.80 132.80 113.90 112.60 104.30 107.50 106.00 117.30 123.10 114.30 132.00 92.30 93.70 121.30 113.60 116.30 98.30 111.90 109.30 133.20 118.00 131.60 134.10 96.70 99.80 128.30 134.90 130.70 107.30 121.60 120.60 140.50 124.80 129.90 145.60 109.70 105.30
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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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Big Analytics Cloud Computing Center
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