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2.97 3.04 3.12 3.21 3.34 3.45 3.74 4.02 4.24 4.87 5.62 6.02 5.98 5.89 5.76 5.58 5.39 5.19 5.16 5.2 5.25 5.26 5.21 5.18 5.13 5.03 5.01 4.87 4.86 4.82 4.69 4.65 4.61 4.47 4.37 4.29 4.2 4.19 4.09 3.88 3.87 3.74 3.61 3.43 3.29 3.18 3.07 3.02 2.97 2.98 3.01 3.06 3.12 3.16 3.19 3.21 3.27 3.36 3.45 3.52 3.58 3.62 3.5 3.43 3.41 3.48 3.63 3.76 3.8 3.72 3.67 3.58 3.47 3.43 3.55 3.65 3.7 3.7 3.93 4.15 4.24
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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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