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Data:
1213.8 1245.6 1306.3 1255.8 1257.6 1287.8 1300.4 1320.9 1370.8 1327.3 1320 1345.3 1346.7 1395.4 1462 1491.6 1461.8 1477.9 1490.3 1521.1 1561.9 1552.6 1523.6 1548.3 1552.4 1587 1621.3 1648.7 1641.8 1650.6 1688.6 1670.7 1682.2 1678.9 1650.6 1662.4 1664.5 1683.2 1736.2 1747.6 1749 1759.7 1793.6 1817.4 1858.4 1839.9 1809.1 1877.7 1880.3 1930.9 2039.3 1992.7 1987.8 1984.4 2016.5 2016.7 2064.1 2031.5 2000.3 2057.8 2041.2 2093.2 2158.3 2128.8 2131.9 2170.3 2190.8 2217.7 2254.4 2223.3 2210.5 2250.8 2249.1 2288.6 2329.2 2313.8 2309.8 2345.9 2361.3 2372 2410.4 2398.5 2362.3 2419.1 2421.6 2465 2480.5 2506.1 2506.6 2525.8 2550 2578.3 2807.8 2815.3 2767.7 2815.4 2838.8 2864 2948.6 2922.8 2917.2 2936.8 2993.4 3007.8 3046.3 3011.5 2958.6 3019.8 2998.5 3040.4 3166 3110 3099.2 3150.3 3163.6 3182.6 3244.4 3223.2 3143.6 3217 3182.3 3217.2 3262.5 3227.9 3171.6 3219 3195.4 3221.6 3262.1 3179.5 3133.6 3219.2 3245 3265.3 3312.5 3383.6 3386.3 3411.1 3467.2 3487.7 3575.5 3571.5 3582.3 3637.1 3685
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R Code
par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) arr <- array(NA,dim=c(par1,np+1)) darr <- array(NA,dim=c(par1,np+1)) ari <- array(0,dim=par1) dx <- diff(x) j <- 0 for (i in 1:n) { j = j + 1 ari[j] = ari[j] + 1 arr[j,ari[j]] <- x[i] darr[j,ari[j]] <- dx[i] if (j == par1) j = 0 } ari arr darr arr.mean <- array(NA,dim=par1) arr.median <- array(NA,dim=par1) arr.midrange <- array(NA,dim=par1) for (j in 1:par1) { arr.mean[j] <- mean(arr[j,],na.rm=TRUE) arr.median[j] <- median(arr[j,],na.rm=TRUE) arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2 } overall.mean <- mean(x) overall.median <- median(x) overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2 bitmap(file='plot1.png') plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index') mtext(paste('#blocks = ',np)) abline(overall.mean,0) dev.off() bitmap(file='plot2.png') plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index') mtext(paste('#blocks = ',np)) abline(overall.median,0) dev.off() bitmap(file='plot3.png') plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index') mtext(paste('#blocks = ',np)) abline(overall.midrange,0) dev.off() bitmap(file='plot4.png') z <- data.frame(t(arr)) names(z) <- c(1:par1) (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries')) dev.off() bitmap(file='plot4b.png') z <- data.frame(t(darr)) names(z) <- c(1:par1) (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Differenced Periodic Subseries')) dev.off() bitmap(file='plot5.png') z <- data.frame(arr) names(z) <- c(1:np) (boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks')) dev.off() bitmap(file='plot6.png') z <- data.frame(cbind(arr.mean,arr.median,arr.midrange)) names(z) <- list('mean','median','midrange') (boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots')) dev.off()
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Big Analytics Cloud Computing Center
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