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38 32 35 33 37 29 31 36 35 38 31 34 35 38 37 33 32 38 38 32 33 31 38 39 32 32 35 37 33 33 28 32 31 37 30 33 31 33 31 33 32 33 32 33 28 35 39 34 38 32 38 30 33 38 32 32 34 34 36 34 28 34 35 35 31 37 35 27 40 37 36 38 39 41 27 30 37 31 31 27 36 38 37 33 34 31 39 34 32 33 36 32 41 28 30 36 35 31 34 36 36 35 37 28 39 32 35 39 35 42 34 33 41 33 34 32 40 40 35 36 37 27 39 38 31 33 32 39 36 33 33 32 37 30 38 29 22 35 35 34 35 34 34 35 23 31 27 36 31 32 39 37 38 39 34 31 32 37 36 32 35 36
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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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