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Data:
35 36.1 40.1 35.4 37.4 39.9 32 32.6 44.9 36.3 43.7 39.8 42.6 48.6 49.1 46.9 45.7 56.1 38.3 40.6 46.5 51.4 47 44.6 51 51.1 54.9 52.1 48.7 50.5 47.5 44.6 50.3 54.3 50 44.8 57.6 47.2 59.1 53.9 45.7 54.5 52.8 52.9 66 63.7 54.4 74.4 50.1 62.5 77.2 65.6 58.2 72.6 68.6 63.1 76.9 70.6 71.4 90.6 71.9 60.9 72.9 69.2 64.8 70.2 63 62.2 82.8 77.6 71.2 70.6 71.1 74 87.9 68.3 68.1 75.7 62.7 66.2 81.3 84 80 80.8 67.3 61.9 77.2 65.6 68.7 82 81.4 70.9 71.2 71.9 71.6 76.4 75.6 73.2 80.2 74 69.5 82 82.8 64.5 92.6 82 78.4 103.8 66.6 73.3 92.3 73.6 74.9 83.6 83.3 70.9 82.5 81.7 83.1 92.4 86.9 110.1 112.1 81.5 84.3 113.5 100.3 93.2 100.4 94.4 110.2 113 94.6 111 160.1 110.1 102.8 112.4 105.4 130.4 117.2 103.9 92.2 95.8 93.1 93.9 147.6 89.6 83 99.2 118.3 110.9 124.4 115.8 112.7 111.9 108.6 102.5 141.9 137.7 121.3 142.8 143 121.1 130.2 146.3 143.7 139.3 109.3 141.3 152.7 152.2 151.8 180.5 129 126.1 187.9 170 168.4 157.1 133.9 103.1 166.3 148 131.4 136.3 135.8 151.8 172.2 154.4 158 146.2 128 124.7 160.3 148.1 139.7 194 188.7 172.2 184.8 160.5 139.7 219.8 143.9 166.2 182.7 152.7 146.8 177.1 186 189.2
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Seasonal Period
12
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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