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Data:
44.58070218 43.3193912 42.07587125 40.8501513 39.64224047 39.64224047 45.85979536 52.5216938 53.90730164 53.90730164 53.90730164 56.73168085 59.62689273 59.62689273 59.62689273 58.17043656 58.17043656 59.62689273 67.17441874 78.48233794 81.87175216 83.59285653 83.59285653 85.33155061 87.08782811 87.08782811 85.33155061 83.59285653 81.87175216 80.16824383 85.33155061 96.13275234 96.13275234 94.2886494 90.65310867 88.86168284 88.86168284 87.08782811 83.59285653 80.16824383 76.81404097 75.16335947 83.59285653 92.46209953 96.13275234 94.2886494 92.46209953 90.65310867 92.46209953 90.65310867 87.08782811 83.59285653 78.48233794 75.16335947 80.16824383 88.86168284 88.86168284 85.33155061 81.87175216 80.16824383 78.48233794 78.48233794 75.16335947 71.91486948 70.31707448 70.31707448 76.81404097 87.08782811 88.86168284 85.33155061 81.87175216 81.87175216 83.59285653 81.87175216 80.16824383 78.48233794 75.16335947 73.53030008 78.48233794 88.86168284 90.65310867 85.33155061 78.48233794 76.81404097 76.81404097 75.16335947 73.53030008 70.31707448 67.17441874 64.10238876 67.17441874 70.31707448 65.62957198 61.10104179 56.73168085 55.31063329 52.5216938 48.4712936 43.3193912 42.07587125 38.45214802 37.27988334 43.3193912 49.80368162 47.15666202 45.85979536 43.3193912 40.8501513 37.27988334 34.98887574 34.98887574 37.27988334 37.27988334 33.8701524 36.12545601 38.45214802 43.3193912 52.5216938 52.5216938 53.90730164 53.90730164 51.15381776 49.80368162 47.15666202 44.58070218 43.3193912 52.5216938 53.90730164 56.73168085 59.62689273 61.10104179 62.59287626 64.10238876 62.59287626 59.62689273 58.17043656 53.90730164 53.90730164 64.10238876 65.62957198 65.62957198 65.62957198 65.62957198 68.73692191 73.53030008 71.91486948 64.10238876 52.5216938 48.4712936 51.15381776 71.91486948 80.16824383 80.16824383 70.31707448 62.59287626 64.10238876 67.17441874 68.73692191 67.17441874 62.59287626 61.10104179 58.17043656 68.73692191 70.31707448 70.31707448 67.17441874 65.62957198 67.17441874 70.31707448 70.31707448 68.73692191 67.17441874 64.10238876 59.62689273 62.59287626 61.10104179 61.10104179 59.62689273 58.17043656 58.17043656
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Seasonal Period
1
12
4
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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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Big Analytics Cloud Computing Center
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