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Data:
3202.1 3650.2 2805.1 3957.5 3941.3 3905.4 3546.9 3208.7 3402 3661.1 3073.9 3419.2 3532.8 3693.1 2622.9 3130.8 3487.5 3349.7 3044.2 3266 3351.5 3606.8 3419.5 3829.5 3505.1 3845.3 2566.6 3658.5 3954 3460.1 3454.1 3412.8 3418 3349.5 3423.4 3242.8 3277.2 3833 2606.3 3643.8 3686.4 3281.6 3669.3 3191.5 3512.7 3970.7 3601.2 3610 4172.1 3956.2 3142.7 3884.3 3892.2 3613 3730.5 3481.3 3649.5 4215.2 4066.6 4196.8 4536.6 4441.6 3548.3 4735.9 4130.6 4356.2 4159.6 3988 4167.8 4902.2 3909.4 4697.6 4308.9 4420.4 3544.2 4433 4479.7 4533.2 4237.5 4207.4 4394 5148.4 4202.2 4682.5 4884.3 5288.9 4505.2 4611.5 5081.1 4523.1 4412.8 4647.4 4778.6 4495.3 4633.5 4360.5 4517.9
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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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