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-12.7 -2.4 7.1 -3.9 9.5 5 -16.1 -10.8 7 13.6 8.1 -8.1 4.9 -0.8 4.3 4 1.5 5.4 -11.3 -16.4 -2 8.9 -7.2 -18 1.3 6.3 -6 2.8 2 5.1 -7.6 -18.6 5.8 20.3 0.7 -11.2 -5.7 -0.1 3.4 3.3 -1.2 4.2 -8.8 -25.3 8.5 14.5 -3.1 -10.4 -2.9 0.3 22.6 15.4 9 29.1 2.8 -3.8 27.7 28.9 26.5 19.8 13.2 14.1 34.1 30 21.8 32.1 5.3 3 17.1 26.3 38.1 19.5 38 35.5 78.6 62.2 76.9 104.9 32.2 42.5 64.3 74.9 75.4 43 58.7 55.4 76.6 63.3 78.9 82.7
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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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