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124.06 124.58 122.00 124.02 124.16 124.29 123.93 124.62 121.81 124.14 124.31 125.15 125.35 125.48 124.17 125.33 124.46 123.39 123.14 122.24 119.31 120.87 120.43 119.41 118.85 119.08 117.25 118.51 118.42 118.56 117.97 117.98 115.25 117.23 117.08 116.83 117.17 117.73 115.74 116.99 116.90 116.49 115.84 115.92 113.32 114.84 114.75 114.84 115.03 115.03 112.99 114.15 113.77 113.57 113.38 112.71 110.27 111.73 112.12 112.31 111.73 111.83 109.99 111.15 111.25 110.87 110.27 110.18 108.15 109.60 109.60 109.41 109.80 109.60 107.76 109.02 108.62 109.02 109.22 108.92 106.69 107.76 107.66 107.85 107.95 107.85 106.30 107.37 107.66 107.46 107.37 107.18 105.43 106.39 106.50 106.50 106.69 106.50 105.14 106.50 106.20 105.72 104.76 104.55 102.71 104.36 104.65 104.46 104.65 103.88 102.32 103.39 103.00 102.71 102.51 102.04 100.00
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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
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Big Analytics Cloud Computing Center
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