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Data:
23.11 18.64 14.94 16.90 15.46 11.15 13.13 12.48 12.95 12.59 10.58 10.58 12.39 15.53 13.06 10.22 16.33 19.72 21.31 18.84 24.84 15.67 15.57 12.73 13.56 15.54 17.22 12.14 11.07 12.02 11.55 6.92 10.33 8.38 12.11 11.46 12.75 13.32 13.00 11.90 11.79 12.55 11.84 11.25 11.15 10.99 11.70 14.01 17.51 17.27 16.90 15.79 15.45 16.24 16.71 16.77 16.64 17.80 16.87 16.13 15.76 15.66 15.54 15.30 15.05 14.69 14.39 14.18 13.70 13.66 13.27 13.56 13.14 14.19 22.57 23.09 23.31 22.91 22.36 43.06 64.67 64.68 56.90 48.79 45.21 41.40 22.17 25.52 20.28 22.87 27.63 22.95 21.35 18.38 17.15 18.27 19.40 20.52
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Seasonal Period
4
12
4
6
12
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R Code
par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) arr <- array(NA,dim=c(par1,np)) j <- 0 k <- 1 for (i in 1:(np*par1)) { j = j + 1 arr[j,k] <- x[i] if (j == par1) { j = 0 k=k+1 } } arr arr.mean <- array(NA,dim=np) arr.sd <- array(NA,dim=np) arr.range <- array(NA,dim=np) for (j in 1:np) { arr.mean[j] <- mean(arr[,j],na.rm=TRUE) arr.sd[j] <- sd(arr[,j],na.rm=TRUE) arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) } arr.mean arr.sd arr.range (lm1 <- lm(arr.sd~arr.mean)) (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) (lm2 <- lm(arr.range~arr.mean)) bitmap(file='test1.png') plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') dev.off() bitmap(file='test2.png') plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Section',header=TRUE) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,'Standard Deviation',header=TRUE) a<-table.element(a,'Range',header=TRUE) a<-table.row.end(a) for (j in 1:np) { a<-table.row.start(a) a<-table.element(a,j,header=TRUE) a<-table.element(a,arr.mean[j]) a<-table.element(a,arr.sd[j] ) a<-table.element(a,arr.range[j] ) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lnlm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Lambda',header=TRUE) a<-table.element(a,1-lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab')
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