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Data:
4930.63 6284.63 13339.63 8935.63 -419.37 1220.63 -5094.37 -5561.37 -2732.37 -316.37 -3929.37 -9291.37 6644.63 2492.63 5997.63 3383.63 -693.37 3945.63 -5128.37 -4368.37 -3414.37 -3313.37 -4619.37 -12400.37 8857.63 6407.63 11407.63 4066.63 3637.63 592.63 -4941.37 -5770.37 -4893.37 -2103.37 -5716.37 -13731.37 8025.63 3452.63 7552.63 2760.63 2001.63 2679.63 -2680.37 -4410.37 -2674.37 1677.63 -3284.37 -10360.37 8467.63 7012.63 6920.63 8835.63 2727.63 3736.63 -2893.37 -5309.37 -2578.37 -580.37 -7526.37 -11589.37 2348.63 991.63 4687.63 3096.63 -2582.37 -339.37 -4070.37 -6127.37 -3062.37 -613.37
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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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