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1.74 1.75 1.83 2.09 2.12 2.29 2.4 2.82 3.18 4 4.8 5.28 5.37 5.27 5.33 5.23 5.08 5.11 5.1 4.97 5 5.2 4.9 4.82 5.04 4.82 4.77 4.79 4.58 4.59 4.57 4.35 4.27 4.39 3.97 3.84 3.73 3.58 3.45 3.44 3.25 3.25 3.02 2.87 2.92 2.95 2.75 2.7 2.75 2.72 2.71 2.76 2.68 2.78 2.86 2.75 2.87 2.91 2.79 2.77
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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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