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111.4 114.1 121.8 127.6 129.9 128.0 123.5 124.0 127.4 127.6 128.4 131.4 135.1 134.0 144.5 147.3 150.9 148.7 141.4 138.9 139.8 145.6 147.9 148.5 151.1 157.5 167.5 172.3 173.5 187.5 205.5 195.1 204.5 204.5 201.7 207.0 206.6 210.6 211.1 215.0 223.9 238.2 238.9 229.6 232.2 222.1 221.6 227.3 221.0 213.6 243.4 253.8 265.3 268.2 268.5 266.9 268.4 250.8 231.2 192.0
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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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1 seconds
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Big Analytics Cloud Computing Center
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