Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
613.20 614.70 618.40 628.20 629.00 629.70 630.40 630.40 639.30 639.40 640.90 640.80 642.10 645.30 647.60 648.40 648.80 648.90 648.90 648.90 650.30 650.30 650.00 650.00 650.50 658.40 666.00 675.50 680.70 690.60 690.60 691.10 692.90 693.80 692.80 697.50 699.00 702.10 704.80 715.50 721.80 726.40 727.70 727.40 731.30 734.40 733.40 733.40 738.10 742.60 747.20 751.10 752.60 758.90 759.10 764.30 765.60 767.60 767.60 765.60 768.20 770.90 775.10 777.60 778.60 778.90 779.40 779.90 781.70 789.10 788.70 788.80 790.80 794.10 795.10 797.30 803.80 805.60 804.60 804.50 805.80 806.80 805.20 814.90 816.60 819.50 823.00 824.00 831.40 831.70 831.10 832.10 833.30 838.80 838.00 837.30 994.20 994.20 994.20 994.20 994.20 1092.60 1100.00 1100.00 1092.60 1000.70 1000.70 1000.50 1000.50 1000.50 1000.50 1000.50 1000.50 1087.70 1113.20 1116.00 1085.20 1031.30 1028.70 1027.50 1027.50 1027.50 1027.50 1027.50 1027.50 1152.20 1155.30 1154.00 1119.90 1079.30 1074.30 1069.80
Sample Range:
(leave blank to include all observations)
From:
To:
# blockwidth
Chart options
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()
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation