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41 39 30 31 34 35 39 34 36 37 38 36 38 39 33 32 36 38 39 32 32 31 39 37 39 41 36 33 33 34 31 27 37 34 34 32 29 36 29 35 37 34 38 35 38 37 38 33 36 38 32 32 32 34 32 37 39 29 37 35 30 38 34 31 34 35 36 30 39 35 38 31 34 38 34 39 37 34 28 37 33 37 35 37 32 33 38 33 29 33 31 36 35 32 29 39 37 35 37 32 38 37 36 32 33 40 38 41 36 43 30 31 32 32 37 37 33 34 33 38 33 31 38 37 33 31 39 44 33 35 32 28 40 27 37 32 28 34 30 35 31 32 30 30 31 40 32 36 32 35 38 42 34 35 35 33 36 32 33 34 32 34
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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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