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105.5 106.4 117.9 89.7 88.5 106.4 61.4 92.3 95.5 92.5 89.6 84.3 76.3 80.7 96.3 81.0 82.9 90.3 74.8 70.1 86.7 86.4 89.9 88.1 78.8 81.1 85.4 82.6 80.3 81.2 68.0 67.4 91.3 94.9 82.8 88.6 73.1 76.7 93.2 84.9 83.8 93.5 91.9 69.6 87.0 90.2 82.7 91.4 74.6 76.1 87.1 78.4 81.3 99.3 71.0 73.2 95.6 84.0 90.8 93.6 80.9 84.4 97.3 83.5 88.8 100.7 69.4 74.6 96.6 96.6 93.1 91.8 85.7 79.1 91.3 84.2 85.8 90.0 76.6 81.3
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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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