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99.2 93.6 104.2 95.3 102.7 103.1 100 107.2 107 119 110.4 101.7 102.4 98.8 105.6 104.4 106.3 107.2 108.5 106.9 114.2 125.9 110.6 110.5 106.7 104.7 107.4 109.8 103.4 114.8 114.3 109.6 118.3 127.3 112.3 114.9 108.2 105.4 122.1 113.5 110 125.3 114.3 115.6 127.1 123 122.2 126.4 112.7 105.8 120.9 116.3 115.7 127.9 108.3 121.1 128.6 123.1 127.7 126.6
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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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