Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
161.88 161.88 162.05 162.16 162.61 162.53 162.53 162.53 162.53 162.83 161.61 161.79 161.79 161.79 161.79 161.85 161.77 161.86 161.89 161.89 161.89 162.18 162.43 162.58 162.57 162.57 162.57 162.44 162.79 163.15 163.23 163.23 163.23 163.38 163.71 163.73 163.73 163.73 163.73 163.93 164.27 164.57 164.73 164.73 164.76 165.75 165.86 165.99 166.13 166.13 166.13 166.15 166.45 166.48 166.51 166.51 166.51 166.58 166.82 167.35 167.5 167.5 167.6 167.72 167.29 166.98 166.98 166.98 166.98 167.63 167.83 167.85 167.87 167.87 167.96 167.7 169.25 168.79 168.77 168.77 169 168.92 169.23 169.28 169.29 163.93 164.28 164.58 165.97 166.3 166.27 166.27 166.44 166.26 166.64 166.07 166.19
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