R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- c(255
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> ylimmax = ''
> ylimmin = ''
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> x <-sort(x[!is.na(x)])
> num <- 50
> res <- array(NA,dim=c(num,3))
> geomean <- function(x) {
+ return(exp(mean(log(x))))
+ }
> harmean <- function(x) {
+ return(1/mean(1/x))
+ }
> quamean <- function(x) {
+ return(sqrt(mean(x*x)))
+ }
> winmean <- function(x) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ denom <- 3
+ nodenom <- n/denom
+ if (nodenom>40) denom <- n/40
+ sqrtn = sqrt(n)
+ roundnodenom = floor(nodenom)
+ win <- array(NA,dim=c(roundnodenom,2))
+ for (j in 1:roundnodenom) {
+ win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
+ win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
+ }
+ return(win)
+ }
> trimean <- function(x) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ denom <- 3
+ nodenom <- n/denom
+ if (nodenom>40) denom <- n/40
+ sqrtn = sqrt(n)
+ roundnodenom = floor(nodenom)
+ tri <- array(NA,dim=c(roundnodenom,2))
+ for (j in 1:roundnodenom) {
+ tri[j,1] <- mean(x,trim=j/n)
+ tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
+ }
+ return(tri)
+ }
> midrange <- function(x) {
+ return((max(x)+min(x))/2)
+ }
> q1 <- function(data,n,p,i,f) {
+ np <- n*p;
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- (1-f)*data[i] + f*data[i+1]
+ }
> q2 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- (1-f)*data[i] + f*data[i+1]
+ }
> q3 <- function(data,n,p,i,f) {
+ np <- n*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
> q4 <- function(data,n,p,i,f) {
+ np <- n*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- (data[i]+data[i+1])/2
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
> q5 <- function(data,n,p,i,f) {
+ np <- (n-1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i+1]
+ } else {
+ qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
+ }
+ }
> q6 <- function(data,n,p,i,f) {
+ np <- n*p+0.5
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- data[i]
+ }
> q7 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- f*data[i] + (1-f)*data[i+1]
+ }
+ }
> q8 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ if (f == 0.5) {
+ qvalue <- (data[i]+data[i+1])/2
+ } else {
+ if (f < 0.5) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
+ }
+ }
> iqd <- function(x,def) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ if (def==1) {
+ qvalue1 <- q1(x,n,0.25,i,f)
+ qvalue3 <- q1(x,n,0.75,i,f)
+ }
+ if (def==2) {
+ qvalue1 <- q2(x,n,0.25,i,f)
+ qvalue3 <- q2(x,n,0.75,i,f)
+ }
+ if (def==3) {
+ qvalue1 <- q3(x,n,0.25,i,f)
+ qvalue3 <- q3(x,n,0.75,i,f)
+ }
+ if (def==4) {
+ qvalue1 <- q4(x,n,0.25,i,f)
+ qvalue3 <- q4(x,n,0.75,i,f)
+ }
+ if (def==5) {
+ qvalue1 <- q5(x,n,0.25,i,f)
+ qvalue3 <- q5(x,n,0.75,i,f)
+ }
+ if (def==6) {
+ qvalue1 <- q6(x,n,0.25,i,f)
+ qvalue3 <- q6(x,n,0.75,i,f)
+ }
+ if (def==7) {
+ qvalue1 <- q7(x,n,0.25,i,f)
+ qvalue3 <- q7(x,n,0.75,i,f)
+ }
+ if (def==8) {
+ qvalue1 <- q8(x,n,0.25,i,f)
+ qvalue3 <- q8(x,n,0.75,i,f)
+ }
+ iqdiff <- qvalue3 - qvalue1
+ return(c(iqdiff,iqdiff/2,iqdiff/(qvalue3 + qvalue1)))
+ }
> midmean <- function(x,def) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ if (def==1) {
+ qvalue1 <- q1(x,n,0.25,i,f)
+ qvalue3 <- q1(x,n,0.75,i,f)
+ }
+ if (def==2) {
+ qvalue1 <- q2(x,n,0.25,i,f)
+ qvalue3 <- q2(x,n,0.75,i,f)
+ }
+ if (def==3) {
+ qvalue1 <- q3(x,n,0.25,i,f)
+ qvalue3 <- q3(x,n,0.75,i,f)
+ }
+ if (def==4) {
+ qvalue1 <- q4(x,n,0.25,i,f)
+ qvalue3 <- q4(x,n,0.75,i,f)
+ }
+ if (def==5) {
+ qvalue1 <- q5(x,n,0.25,i,f)
+ qvalue3 <- q5(x,n,0.75,i,f)
+ }
+ if (def==6) {
+ qvalue1 <- q6(x,n,0.25,i,f)
+ qvalue3 <- q6(x,n,0.75,i,f)
+ }
+ if (def==7) {
+ qvalue1 <- q7(x,n,0.25,i,f)
+ qvalue3 <- q7(x,n,0.75,i,f)
+ }
+ if (def==8) {
+ qvalue1 <- q8(x,n,0.25,i,f)
+ qvalue3 <- q8(x,n,0.75,i,f)
+ }
+ midm <- 0
+ myn <- 0
+ roundno4 <- round(n/4)
+ round3no4 <- round(3*n/4)
+ for (i in 1:n) {
+ if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
+ midm = midm + x[i]
+ myn = myn + 1
+ }
+ }
+ midm = midm / myn
+ return(midm)
+ }
> range <- max(x) - min(x)
> lx <- length(x)
> biasf <- (lx-1)/lx
> varx <- var(x)
> bvarx <- varx*biasf
> sdx <- sqrt(varx)
> mx <- mean(x)
> bsdx <- sqrt(bvarx)
> x2 <- x*x
> mse0 <- sum(x2)/lx
> xmm <- x-mx
> xmm2 <- xmm*xmm
> msem <- sum(xmm2)/lx
> axmm <- abs(x - mx)
> medx <- median(x)
> axmmed <- abs(x - medx)
> xmmed <- x - medx
> xmmed2 <- xmmed*xmmed
> msemed <- sum(xmmed2)/lx
> qarr <- array(NA,dim=c(8,3))
> for (j in 1:8) {
+ qarr[j,] <- iqd(x,j)
+ }
> sdpo <- 0
> adpo <- 0
> for (i in 1:(lx-1)) {
+ for (j in (i+1):lx) {
+ ldi <- x[i]-x[j]
+ aldi <- abs(ldi)
+ sdpo = sdpo + ldi * ldi
+ adpo = adpo + aldi
+ }
+ }
> denom <- (lx*(lx-1)/2)
> sdpo = sdpo / denom
> adpo = adpo / denom
> gmd <- 0
> for (i in 1:lx) {
+ for (j in 1:lx) {
+ ldi <- abs(x[i]-x[j])
+ gmd = gmd + ldi
+ }
+ }
> gmd <- gmd / (lx*(lx-1))
> sumx <- sum(x)
> pk <- x / sumx
> ck <- cumsum(pk)
> dk <- array(NA,dim=lx)
> for (i in 1:lx) {
+ if (ck[i] <= 0.5) dk[i] <- ck[i] else dk[i] <- 1 - ck[i]
+ }
> bigd <- sum(dk) * 2 / (lx-1)
> iod <- 1 - sum(pk*pk)
> res[1,] <- c('Absolute range','http://www.xycoon.com/absolute.htm', range)
> res[2,] <- c('Relative range (unbiased)','http://www.xycoon.com/relative.htm', range/sd(x))
> res[3,] <- c('Relative range (biased)','http://www.xycoon.com/relative.htm', range/sqrt(varx*biasf))
> res[4,] <- c('Variance (unbiased)','http://www.xycoon.com/unbiased.htm', varx)
> res[5,] <- c('Variance (biased)','http://www.xycoon.com/biased.htm', bvarx)
> res[6,] <- c('Standard Deviation (unbiased)','http://www.xycoon.com/unbiased1.htm', sdx)
> res[7,] <- c('Standard Deviation (biased)','http://www.xycoon.com/biased1.htm', bsdx)
> res[8,] <- c('Coefficient of Variation (unbiased)','http://www.xycoon.com/variation.htm', sdx/mx)
> res[9,] <- c('Coefficient of Variation (biased)','http://www.xycoon.com/variation.htm', bsdx/mx)
> res[10,] <- c('Mean Squared Error (MSE versus 0)','http://www.xycoon.com/mse.htm', mse0)
> res[11,] <- c('Mean Squared Error (MSE versus Mean)','http://www.xycoon.com/mse.htm', msem)
> res[12,] <- c('Mean Absolute Deviation from Mean (MAD Mean)', 'http://www.xycoon.com/mean2.htm', sum(axmm)/lx)
> res[13,] <- c('Mean Absolute Deviation from Median (MAD Median)', 'http://www.xycoon.com/median1.htm', sum(axmmed)/lx)
> res[14,] <- c('Median Absolute Deviation from Mean', 'http://www.xycoon.com/mean3.htm', median(axmm))
> res[15,] <- c('Median Absolute Deviation from Median', 'http://www.xycoon.com/median2.htm', median(axmmed))
> res[16,] <- c('Mean Squared Deviation from Mean', 'http://www.xycoon.com/mean1.htm', msem)
> res[17,] <- c('Mean Squared Deviation from Median', 'http://www.xycoon.com/median.htm', msemed)
> mylink1 <- hyperlink('http://www.xycoon.com/difference.htm','Interquartile Difference','')
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
> res[18,] <- c('', mylink2, qarr[1,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
> res[19,] <- c('', mylink2, qarr[2,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_3.htm','(Empirical Distribution Function)',''),sep=' ')
> res[20,] <- c('', mylink2, qarr[3,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
> res[21,] <- c('', mylink2, qarr[4,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
> res[22,] <- c('', mylink2, qarr[5,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_6.htm','(Closest Observation)',''),sep=' ')
> res[23,] <- c('', mylink2, qarr[6,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
> res[24,] <- c('', mylink2, qarr[7,1])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_8.htm','(MS Excel (old versions))',''),sep=' ')
> res[25,] <- c('', mylink2, qarr[8,1])
> mylink1 <- hyperlink('http://www.xycoon.com/deviation.htm','Semi Interquartile Difference','')
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
> res[26,] <- c('', mylink2, qarr[1,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
> res[27,] <- c('', mylink2, qarr[2,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_3.htm','(Empirical Distribution Function)',''),sep=' ')
> res[28,] <- c('', mylink2, qarr[3,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
> res[29,] <- c('', mylink2, qarr[4,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
> res[30,] <- c('', mylink2, qarr[5,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_6.htm','(Closest Observation)',''),sep=' ')
> res[31,] <- c('', mylink2, qarr[6,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
> res[32,] <- c('', mylink2, qarr[7,2])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_8.htm','(MS Excel (old versions))',''),sep=' ')
> res[33,] <- c('', mylink2, qarr[8,2])
> mylink1 <- hyperlink('http://www.xycoon.com/variation1.htm','Coefficient of Quartile Variation','')
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_1.htm','(Weighted Average at Xnp)',''),sep=' ')
> res[34,] <- c('', mylink2, qarr[1,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_2.htm','(Weighted Average at X(n+1)p)',''),sep=' ')
> res[35,] <- c('', mylink2, qarr[2,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_3.htm','(Empirical Distribution Function)',''),sep=' ')
> res[36,] <- c('', mylink2, qarr[3,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_4.htm','(Empirical Distribution Function - Averaging)',''),sep=' ')
> res[37,] <- c('', mylink2, qarr[4,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_5.htm','(Empirical Distribution Function - Interpolation)',''),sep=' ')
> res[38,] <- c('', mylink2, qarr[5,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_6.htm','(Closest Observation)',''),sep=' ')
> res[39,] <- c('', mylink2, qarr[6,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_7.htm','(True Basic - Statistics Graphics Toolkit)',''),sep=' ')
> res[40,] <- c('', mylink2, qarr[7,3])
> mylink2 <- paste(mylink1,hyperlink('http://www.xycoon.com/method_8.htm','(MS Excel (old versions))',''),sep=' ')
> res[41,] <- c('', mylink2, qarr[8,3])
> res[42,] <- c('Number of all Pairs of Observations', 'http://www.xycoon.com/pair_numbers.htm', lx*(lx-1)/2)
> res[43,] <- c('Squared Differences between all Pairs of Observations', 'http://www.xycoon.com/squared_differences.htm', sdpo)
> res[44,] <- c('Mean Absolute Differences between all Pairs of Observations', 'http://www.xycoon.com/mean_abs_differences.htm', adpo)
> res[45,] <- c('Gini Mean Difference', 'http://www.xycoon.com/gini_mean_difference.htm', gmd)
> res[46,] <- c('Leik Measure of Dispersion', 'http://www.xycoon.com/leiks_d.htm', bigd)
> res[47,] <- c('Index of Diversity', 'http://www.xycoon.com/diversity.htm', iod)
> res[48,] <- c('Index of Qualitative Variation', 'http://www.xycoon.com/qualitative_variation.htm', iod*lx/(lx-1))
> res[49,] <- c('Coefficient of Dispersion', 'http://www.xycoon.com/dispersion.htm', sum(axmm)/lx/medx)
> res[50,] <- c('Observations', '', lx)
> res
[,1]
[1,] "Absolute range"
[2,] "Relative range (unbiased)"
[3,] "Relative range (biased)"
[4,] "Variance (unbiased)"
[5,] "Variance (biased)"
[6,] "Standard Deviation (unbiased)"
[7,] "Standard Deviation (biased)"
[8,] "Coefficient of Variation (unbiased)"
[9,] "Coefficient of Variation (biased)"
[10,] "Mean Squared Error (MSE versus 0)"
[11,] "Mean Squared Error (MSE versus Mean)"
[12,] "Mean Absolute Deviation from Mean (MAD Mean)"
[13,] "Mean Absolute Deviation from Median (MAD Median)"
[14,] "Median Absolute Deviation from Mean"
[15,] "Median Absolute Deviation from Median"
[16,] "Mean Squared Deviation from Mean"
[17,] "Mean Squared Deviation from Median"
[18,] ""
[19,] ""
[20,] ""
[21,] ""
[22,] ""
[23,] ""
[24,] ""
[25,] ""
[26,] ""
[27,] ""
[28,] ""
[29,] ""
[30,] ""
[31,] ""
[32,] ""
[33,] ""
[34,] ""
[35,] ""
[36,] ""
[37,] ""
[38,] ""
[39,] ""
[40,] ""
[41,] ""
[42,] "Number of all Pairs of Observations"
[43,] "Squared Differences between all Pairs of Observations"
[44,] "Mean Absolute Differences between all Pairs of Observations"
[45,] "Gini Mean Difference"
[46,] "Leik Measure of Dispersion"
[47,] "Index of Diversity"
[48,] "Index of Qualitative Variation"
[49,] "Coefficient of Dispersion"
[50,] "Observations"
[,2]
[1,] "http://www.xycoon.com/absolute.htm"
[2,] "http://www.xycoon.com/relative.htm"
[3,] "http://www.xycoon.com/relative.htm"
[4,] "http://www.xycoon.com/unbiased.htm"
[5,] "http://www.xycoon.com/biased.htm"
[6,] "http://www.xycoon.com/unbiased1.htm"
[7,] "http://www.xycoon.com/biased1.htm"
[8,] "http://www.xycoon.com/variation.htm"
[9,] "http://www.xycoon.com/variation.htm"
[10,] "http://www.xycoon.com/mse.htm"
[11,] "http://www.xycoon.com/mse.htm"
[12,] "http://www.xycoon.com/mean2.htm"
[13,] "http://www.xycoon.com/median1.htm"
[14,] "http://www.xycoon.com/mean3.htm"
[15,] "http://www.xycoon.com/median2.htm"
[16,] "http://www.xycoon.com/mean1.htm"
[17,] "http://www.xycoon.com/median.htm"
[18,] "Interquartile Difference (Weighted Average at Xnp)"
[19,] "Interquartile Difference (Weighted Average at X(n+1)p)"
[20,] "Interquartile Difference (Empirical Distribution Function)"
[21,] "Interquartile Difference (Empirical Distribution Function - Averaging)"
[22,] "Interquartile Difference (Empirical Distribution Function - Interpolation)"
[23,] "Interquartile Difference (Closest Observation)"
[24,] "Interquartile Difference (True Basic - Statistics Graphics Toolkit)"
[25,] "Interquartile Difference (MS Excel (old versions))"
[26,] "Semi Interquartile Difference (Weighted Average at Xnp)"
[27,] "Semi Interquartile Difference (Weighted Average at X(n+1)p)"
[28,] "Semi Interquartile Difference (Empirical Distribution Function)"
[29,] "Semi Interquartile Difference (Empirical Distribution Function - Averaging)"
[30,] "Semi Interquartile Difference (Empirical Distribution Function - Interpolation)"
[31,] "Semi Interquartile Difference (Closest Observation)"
[32,] "Semi Interquartile Difference (True Basic - Statistics Graphics Toolkit)"
[33,] "Semi Interquartile Difference (MS Excel (old versions))"
[34,] "Coefficient of Quartile Variation (Weighted Average at Xnp)"
[35,] "Coefficient of Quartile Variation (Weighted Average at X(n+1)p)"
[36,] "Coefficient of Quartile Variation (Empirical Distribution Function)"
[37,] "Coefficient of Quartile Variation (Empirical Distribution Function - Averaging)"
[38,] "Coefficient of Quartile Variation (Empirical Distribution Function - Interpolation)"
[39,] "Coefficient of Quartile Variation (Closest Observation)"
[40,] "Coefficient of Quartile Variation (True Basic - Statistics Graphics Toolkit)"
[41,] "Coefficient of Quartile Variation (MS Excel (old versions))"
[42,] "http://www.xycoon.com/pair_numbers.htm"
[43,] "http://www.xycoon.com/squared_differences.htm"
[44,] "http://www.xycoon.com/mean_abs_differences.htm"
[45,] "http://www.xycoon.com/gini_mean_difference.htm"
[46,] "http://www.xycoon.com/leiks_d.htm"
[47,] "http://www.xycoon.com/diversity.htm"
[48,] "http://www.xycoon.com/qualitative_variation.htm"
[49,] "http://www.xycoon.com/dispersion.htm"
[50,] ""
[,3]
[1,] "231.7"
[2,] "4.72690116241179"
[3,] "4.73348001202893"
[4,] "2402.69710236769"
[5,] "2396.02294375"
[6,] "49.0173143120641"
[7,] "48.9491873655733"
[8,] "0.158966051047040"
[9,] "0.158745111327973"
[10,] "97476.2593611111"
[11,] "2396.02294375"
[12,] "39.0595601851852"
[13,] "38.1108333333333"
[14,] "34.4491666666667"
[15,] "32.75"
[16,] "2396.02294375"
[17,] "2537.65277777778"
[18,] "65.6"
[19,] "65.725"
[20,] "65.6"
[21,] "65.55"
[22,] "65.375"
[23,] "65.6"
[24,] "65.375"
[25,] "65.9"
[26,] "32.8"
[27,] "32.8625"
[28,] "32.8"
[29,] "32.775"
[30,] "32.6875"
[31,] "32.8"
[32,] "32.6875"
[33,] "32.95"
[34,] "0.108753315649867"
[35,] "0.108901868191044"
[36,] "0.108753315649867"
[37,] "0.108607406180101"
[38,] "0.108312968562316"
[39,] "0.108753315649867"
[40,] "0.108312968562316"
[41,] "0.109196354598177"
[42,] "64620"
[43,] "4805.3942047354"
[44,] "53.8016264314451"
[45,] "53.8016264314454"
[46,] "0.503300672159145"
[47,] "0.997152222193415"
[48,] "0.99992980498504"
[49,] "0.131757666335588"
[50,] "360"
> (arm <- mean(x))
[1] 308.3508
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 2.583439
> (armose <- arm / armse)
[1] 119.3567
> (geo <- geomean(x))
[1] 304.7407
> (har <- harmean(x))
[1] 301.3851
> (qua <- quamean(x))
[1] 312.2119
> (win <- winmean(x))
[,1] [,2]
[1,] 308.3428 2.5812558
[2,] 308.3517 2.5790972
[3,] 308.2533 2.5601636
[4,] 308.2589 2.5592575
[5,] 308.2533 2.5528466
[6,] 308.2450 2.5504967
[7,] 308.2100 2.5436015
[8,] 308.1544 2.5330833
[9,] 308.1569 2.5296963
[10,] 308.1542 2.5239762
[11,] 307.9158 2.4899138
[12,] 307.7358 2.4556472
[13,] 307.4831 2.4211379
[14,] 307.2808 2.3963217
[15,] 307.2933 2.3946748
[16,] 307.2222 2.3795108
[17,] 307.1467 2.3697386
[18,] 307.1167 2.3643913
[19,] 307.0903 2.3584176
[20,] 307.0014 2.3461609
[21,] 306.9664 2.3421677
[22,] 306.9969 2.3378927
[23,] 306.8308 2.3157266
[24,] 306.6775 2.2987520
[25,] 306.5942 2.2871897
[26,] 306.4353 2.2675180
[27,] 306.1353 2.2346033
[28,] 306.1275 2.2324604
[29,] 306.0469 2.2186381
[30,] 305.9553 2.2064394
[31,] 305.5936 2.1616384
[32,] 305.5758 2.1584216
[33,] 305.5025 2.1497532
[34,] 305.3419 2.1311565
[35,] 305.2058 2.1166120
[36,] 305.0158 2.0987738
[37,] 305.0158 2.0987738
[38,] 304.9208 2.0882553
[39,] 304.8775 2.0825148
[40,] 304.5331 2.0476756
[41,] 304.4761 2.0407802
[42,] 304.4294 2.0292602
[43,] 304.3458 2.0106337
[44,] 304.2358 1.9972082
[45,] 303.8858 1.9575287
[46,] 303.7325 1.9426867
[47,] 303.5236 1.9194353
[48,] 303.4969 1.9051919
[49,] 303.4697 1.9009297
[50,] 303.4558 1.8894064
[51,] 303.3850 1.8794627
[52,] 303.4283 1.8700783
[53,] 303.0897 1.8409959
[54,] 303.0597 1.8211057
[55,] 302.9375 1.8094047
[56,] 302.9531 1.7993477
[57,] 302.8739 1.7909851
[58,] 302.7772 1.7766715
[59,] 302.6461 1.7644189
[60,] 302.5128 1.7544298
[61,] 302.3942 1.7312295
[62,] 302.4458 1.7277536
[63,] 302.4983 1.7242355
[64,] 302.4094 1.7151943
[65,] 302.2289 1.7020127
[66,] 302.2289 1.6994514
[67,] 302.0986 1.6900327
[68,] 302.1175 1.6599696
[69,] 302.1175 1.6599696
[70,] 302.1369 1.6559979
[71,] 302.2158 1.6507778
[72,] 302.2358 1.6439643
[73,] 302.2967 1.6399688
[74,] 302.1733 1.6311752
[75,] 302.3192 1.6131207
[76,] 302.2558 1.6057552
[77,] 302.2344 1.6013373
[78,] 302.2778 1.5955903
[79,] 302.4533 1.5842824
[80,] 302.3867 1.5675855
[81,] 302.4542 1.5602553
[82,] 302.4314 1.5494863
[83,] 302.1778 1.5255692
[84,] 301.9911 1.5064253
[85,] 302.0147 1.5017880
[86,] 302.1581 1.4863817
[87,] 301.9164 1.4697753
[88,] 301.1831 1.4171840
[89,] 301.1831 1.4107455
[90,] 301.2081 1.3994035
[91,] 301.1575 1.3927898
[92,] 301.2342 1.3813021
[93,] 301.2600 1.3729941
[94,] 301.1817 1.3678467
[95,] 301.2344 1.3611118
[96,] 301.2611 1.3594301
[97,] 301.1803 1.3506683
[98,] 300.9353 1.3242579
[99,] 301.3203 1.2966269
[100,] 301.3758 1.2825994
[101,] 301.6283 1.2458330
[102,] 301.4867 1.2330876
[103,] 301.6011 1.2225414
[104,] 301.6878 1.1920486
[105,] 301.7169 1.1866690
[106,] 301.6286 1.1590657
[107,] 301.8664 1.1449524
[108,] 301.8364 1.1393261
[109,] 301.6547 1.1276945
[110,] 301.5325 1.1161538
[111,] 301.5633 1.1143287
[112,] 301.5944 1.0820354
[113,] 301.5003 1.0227735
[114,] 301.5003 1.0189543
[115,] 301.5322 1.0132564
[116,] 301.6611 0.9942198
[117,] 301.4986 0.9840745
[118,] 301.5314 0.9704373
[119,] 301.7297 0.9473450
[120,] 301.6631 0.9352907
> (tri <- trimean(x))
[,1] [,2]
[1,] 308.1123 2.551534
[2,] 307.8792 2.520636
[3,] 307.6390 2.489646
[4,] 307.4295 2.464322
[5,] 307.2163 2.438257
[6,] 307.0017 2.412617
[7,] 306.7861 2.386412
[8,] 306.5733 2.360327
[9,] 306.3652 2.334786
[10,] 306.1544 2.308672
[11,] 305.9414 2.282203
[12,] 305.7491 2.258655
[13,] 305.7491 2.237867
[14,] 305.4111 2.219742
[15,] 305.2655 2.203255
[16,] 305.1171 2.186263
[17,] 304.9718 2.169885
[18,] 304.8296 2.153657
[19,] 304.6876 2.137198
[20,] 304.5453 2.120526
[21,] 304.4063 2.104077
[22,] 304.2674 2.087243
[23,] 304.1252 2.070001
[24,] 303.9894 2.053537
[25,] 303.8594 2.037505
[26,] 303.8594 2.021543
[27,] 303.6092 2.006136
[28,] 303.4984 1.992078
[29,] 303.3864 1.977556
[30,] 303.2763 1.963216
[31,] 303.1685 1.948959
[32,] 303.0733 1.936574
[33,] 302.9776 1.923832
[34,] 302.8832 1.911005
[35,] 302.7934 1.898602
[36,] 302.7073 1.886413
[37,] 302.6266 1.874604
[38,] 302.5447 1.862275
[39,] 302.4649 1.849927
[40,] 302.3854 1.837310
[41,] 302.3158 1.825835
[42,] 302.2471 1.814172
[43,] 302.1788 1.802521
[44,] 302.1121 1.791206
[45,] 302.0478 1.779995
[46,] 301.9929 1.770089
[47,] 301.9417 1.760389
[48,] 301.8958 1.751267
[49,] 301.8958 1.742325
[50,] 301.8042 1.733134
[51,] 301.7581 1.723989
[52,] 301.7581 1.714826
[53,] 301.6665 1.705601
[54,] 301.6282 1.697176
[55,] 301.5900 1.689153
[56,] 301.5544 1.681209
[57,] 301.5179 1.673264
[58,] 301.4828 1.665251
[59,] 301.4496 1.657409
[60,] 301.4192 1.649658
[61,] 301.3916 1.641904
[62,] 301.3665 1.634679
[63,] 301.3665 1.627185
[64,] 301.3112 1.619410
[65,] 301.2843 1.611572
[66,] 301.2614 1.603841
[67,] 301.2381 1.595770
[68,] 301.2174 1.587632
[69,] 301.1959 1.580255
[70,] 301.1741 1.572437
[71,] 301.1514 1.564315
[72,] 301.1264 1.555919
[73,] 301.1005 1.547301
[74,] 301.0726 1.538326
[75,] 301.0471 1.529191
[76,] 301.0178 1.520255
[77,] 300.9893 1.511086
[78,] 300.9608 1.501537
[79,] 300.9307 1.491635
[80,] 300.8960 1.481587
[81,] 300.8621 1.471647
[82,] 300.8260 1.461384
[83,] 300.7897 1.450941
[84,] 300.7583 1.440929
[85,] 300.7305 1.431140
[86,] 300.7016 1.420900
[87,] 300.6688 1.410659
[88,] 300.6408 1.400518
[89,] 300.6286 1.392164
[90,] 300.6161 1.383503
[91,] 300.6028 1.374737
[92,] 300.5903 1.365642
[93,] 300.5759 1.356417
[94,] 300.5605 1.346903
[95,] 300.5465 1.336929
[96,] 300.5310 1.326531
[97,] 300.5145 1.315424
[98,] 300.5145 1.303925
[99,] 300.4895 1.292933
[100,] 300.4706 1.282498
[101,] 300.4500 1.271958
[102,] 300.4231 1.262478
[103,] 300.3987 1.252897
[104,] 300.3987 1.243054
[105,] 300.3407 1.234008
[106,] 300.3088 1.224450
[107,] 300.2781 1.215589
[108,] 300.2410 1.206654
[109,] 300.2410 1.197211
[110,] 300.1693 1.187598
[111,] 300.1370 1.177780
[112,] 300.1029 1.167121
[113,] 300.0672 1.157413
[114,] 300.0326 1.150350
[115,] 300.0326 1.142743
[116,] 299.9594 1.134647
[117,] 299.9175 1.126823
[118,] 299.8782 1.118813
[119,] 299.8369 1.110766
[120,] 299.7892 1.103237
> (midr <- midrange(x))
[1] 351.05
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 300.4403 300.6161 300.4403 300.6161 300.6161 300.4403 300.6161 300.6286
> postscript(file="/var/www/html/rcomp/tmp/11drk1289497395.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> lb <- win[,1] - 2*win[,2]
> ub <- win[,1] + 2*win[,2]
> if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main='Robustness of Central Tendency', xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main='Robustness of Central Tendency', xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
> lines(ub,lty=3)
> lines(lb,lty=3)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2u4q51289497395.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> lb <- tri[,1] - 2*tri[,2]
> ub <- tri[,1] + 2*tri[,2]
> if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main='Robustness of Central Tendency', xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main='Robustness of Central Tendency', xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
> lines(ub,lty=3)
> lines(lb,lty=3)
> grid()
> dev.off()
null device
1
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Measure',header=TRUE)
> a<-table.element(a,'Value',header=TRUE)
> a<-table.element(a,'S.E.',header=TRUE)
> a<-table.element(a,'Value/S.E.',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
> a<-table.element(a,arm)
> a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
> a<-table.element(a,armose)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
> a<-table.element(a,geo)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
> a<-table.element(a,har)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
> a<-table.element(a,qua)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> for (j in 1:length(win[,1])) {
+ a<-table.row.start(a)
+ mylabel <- paste('Winsorized Mean (',j)
+ mylabel <- paste(mylabel,'/')
+ mylabel <- paste(mylabel,length(win[,1]))
+ mylabel <- paste(mylabel,')')
+ a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
+ a<-table.element(a,win[j,1])
+ a<-table.element(a,win[j,2])
+ a<-table.element(a,win[j,1]/win[j,2])
+ a<-table.row.end(a)
+ }
> for (j in 1:length(tri[,1])) {
+ a<-table.row.start(a)
+ mylabel <- paste('Trimmed Mean (',j)
+ mylabel <- paste(mylabel,'/')
+ mylabel <- paste(mylabel,length(tri[,1]))
+ mylabel <- paste(mylabel,')')
+ a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
+ a<-table.element(a,tri[j,1])
+ a<-table.element(a,tri[j,2])
+ a<-table.element(a,tri[j,1]/tri[j,2])
+ a<-table.row.end(a)
+ }
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
> a<-table.element(a,median(x))
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
> a<-table.element(a,midr)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[1])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[2])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[3])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[4])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[5])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[6])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[7])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[8])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Number of observations',header=TRUE)
> a<-table.element(a,length(x))
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/33gij1289497395.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Variability - Ungrouped Data',2,TRUE)
> a<-table.row.end(a)
> for (i in 1:num) {
+ a<-table.row.start(a)
+ if (res[i,1] != '') {
+ a<-table.element(a,hyperlink(res[i,2],res[i,1],''),header=TRUE)
+ } else {
+ a<-table.element(a,res[i,2],header=TRUE)
+ }
+ a<-table.element(a,res[i,3])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/47hhp1289497395.tab")
> lx <- length(x)
> qval <- array(NA,dim=c(99,8))
> mystep <- 25
> mystart <- 25
> if (lx>10){
+ mystep=10
+ mystart=10
+ }
> if (lx>20){
+ mystep=5
+ mystart=5
+ }
> if (lx>50){
+ mystep=2
+ mystart=2
+ }
> if (lx>=100){
+ mystep=1
+ mystart=1
+ }
> for (perc in seq(mystart,99,mystep)) {
+ qval[perc,1] <- q1(x,lx,perc/100,i,f)
+ qval[perc,2] <- q2(x,lx,perc/100,i,f)
+ qval[perc,3] <- q3(x,lx,perc/100,i,f)
+ qval[perc,4] <- q4(x,lx,perc/100,i,f)
+ qval[perc,5] <- q5(x,lx,perc/100,i,f)
+ qval[perc,6] <- q6(x,lx,perc/100,i,f)
+ qval[perc,7] <- q7(x,lx,perc/100,i,f)
+ qval[perc,8] <- q8(x,lx,perc/100,i,f)
+ }
> postscript(file="/var/www/html/rcomp/tmp/5szfd1289497395.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> myqqnorm <- qqnorm(x,col=2)
> qqline(x)
> grid()
> dev.off()
null device
1
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Percentiles - Ungrouped Data',9,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p',1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_1.htm', 'Weighted Average at Xnp',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),1,TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),1,TRUE)
> a<-table.row.end(a)
> for (perc in seq(mystart,99,mystep)) {
+ a<-table.row.start(a)
+ a<-table.element(a,round(perc/100,2),1,TRUE)
+ for (j in 1:8) {
+ a<-table.element(a,round(qval[perc,j],6))
+ }
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6d0dj1289497395.tab")
> postscript(file="/var/www/html/rcomp/tmp/7d0dj1289497395.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> myhist<-hist(x)
> dev.off()
null device
1
> myhist
$breaks
[1] 220 240 260 280 300 320 340 360 380 400 420 440 460 480
$counts
[1] 3 58 52 75 44 44 36 14 11 10 5 5 3
$intensities
[1] 0.0004166666 0.0080555556 0.0072222222 0.0104166667 0.0061111111
[6] 0.0061111111 0.0050000000 0.0019444444 0.0015277778 0.0013888889
[11] 0.0006944444 0.0006944444 0.0004166667
$density
[1] 0.0004166666 0.0080555556 0.0072222222 0.0104166667 0.0061111111
[6] 0.0061111111 0.0050000000 0.0019444444 0.0015277778 0.0013888889
[11] 0.0006944444 0.0006944444 0.0004166667
$mids
[1] 230 250 270 290 310 330 350 370 390 410 430 450 470
$xname
[1] "x"
$equidist
[1] TRUE
attr(,"class")
[1] "histogram"
> n <- length(x)
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/histogram.htm','Frequency Table (Histogram)',''),6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Bins',header=TRUE)
> a<-table.element(a,'Midpoint',header=TRUE)
> a<-table.element(a,'Abs. Frequency',header=TRUE)
> a<-table.element(a,'Rel. Frequency',header=TRUE)
> a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE)
> a<-table.element(a,'Density',header=TRUE)
> a<-table.row.end(a)
> crf <- 0
> mybracket <- '['
> mynumrows <- (length(myhist$breaks)-1)
> for (i in 1:mynumrows) {
+ a<-table.row.start(a)
+ if (i == 1)
+ dum <- paste('[',myhist$breaks[i],sep='')
+ else
+ dum <- paste(mybracket,myhist$breaks[i],sep='')
+ dum <- paste(dum,myhist$breaks[i+1],sep=',')
+ if (i==mynumrows)
+ dum <- paste(dum,']',sep='')
+ else
+ dum <- paste(dum,mybracket,sep='')
+ a<-table.element(a,dum,header=TRUE)
+ a<-table.element(a,myhist$mids[i])
+ a<-table.element(a,myhist$counts[i])
+ rf <- myhist$counts[i]/n
+ crf <- crf + rf
+ a<-table.element(a,round(rf,6))
+ a<-table.element(a,round(crf,6))
+ a<-table.element(a,round(myhist$density[i],6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/821sv1289497395.tab")
> postscript(file="/var/www/html/rcomp/tmp/921sv1289497395.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> mydensity1<-density(x,kernel='gaussian',na.rm=TRUE)
> plot(mydensity1,main='Gaussian Kernel')
> grid()
> dev.off()
null device
1
> mydensity1
Call:
density.default(x = x, kernel = "gaussian", na.rm = TRUE)
Data: x (360 obs.); Bandwidth 'bw' = 13.53
x y
Min. :194.6 Min. :1.567e-06
1st Qu.:272.8 1st Qu.:6.308e-04
Median :351.1 Median :1.726e-03
Mean :351.1 Mean :3.193e-03
3rd Qu.:429.3 3rd Qu.:6.227e-03
Max. :507.5 Max. :8.706e-03
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Properties of Density Trace',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Bandwidth',header=TRUE)
> a<-table.element(a,mydensity1$bw)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'#Observations',header=TRUE)
> a<-table.element(a,mydensity1$n)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/10vasy1289497395.tab")
>
> try(system("convert tmp/11drk1289497395.ps tmp/11drk1289497395.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u4q51289497395.ps tmp/2u4q51289497395.png",intern=TRUE))
character(0)
> try(system("convert tmp/5szfd1289497395.ps tmp/5szfd1289497395.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d0dj1289497395.ps tmp/7d0dj1289497395.png",intern=TRUE))
character(0)
> try(system("convert tmp/921sv1289497395.ps tmp/921sv1289497395.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.567 0.815 4.870