R version 2.8.1 (2008-12-22) Copyright (C) 2008 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(0.148646309,0.193804029,0.131910607,0.048982359,0.035920892,0.052430242,0.062010996,0.076835147,0.038935146,0.028633045,0.030047843,0.028588494,0.070373946,0.125599266,0.093117457,0.082838021,0.069228352,0.089461571,0.090135825,0.119156645,0.084594868,0.077924504,0.050993737,-0.012468929,0.014611083,0.064006082,0.060022728,0.027923409,0.015205745,0.021403349,0.021403349,0.047156409,0.036829054,0.005311826,-0.046777916,-0.085262281,-0.076011397,-0.078430257,-0.067808537,-0.084313313,-0.08589517,-0.055971412,-0.075210786,-0.11300426,-0.169796642,-0.220749887,-0.146468921,-0.052085939,0.003958635,-0.012954959,-0.100487052,-0.175181637,-0.163935918,-0.060773277,-0.019995189,0.019465346,-0.05531767,-0.094184475,-0.065037375,-0.049343114) > 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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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,] "0.414553916" [2,] "4.7321903430951" [3,] "4.7721251468185" [4,] "0.00767427988407688" [5,] "0.00754637521934227" [6,] "0.0876029673246111" [7,] "0.0868698752119644" [8,] "1752059329.82742" [9,] "1737397487.71395" [10,] "0.00754637521934227" [11,] "0.00754637521934227" [12,] "0.0722488771416667" [13,] "0.07029712265" [14,] "0.0645217285" [15,] "0.065686392" [16,] "0.00754637521934227" [17,] "0.00796393777504959" [18,] "0.129819533" [19,] "0.130623057" [20,] "0.129819533" [21,] "0.129431495" [22,] "0.128239933" [23,] "0.129819533" [24,] "0.128239933" [25,] "0.131814619" [26,] "0.0649097665" [27,] "0.0653115285" [28,] "0.0649097665" [29,] "0.0647157475" [30,] "0.0641199665" [31,] "0.0649097665" [32,] "0.0641199665" [33,] "0.0659073095" [34,] "-22.3921716120679" [35,] "-36.1993553439772" [36,] "-22.3921716120679" [37,] "-37.9073484580237" [38,] "-39.8211441567162" [39,] "-22.3921716120679" [40,] "-39.8211441567162" [41,] "-34.6656617895544" [42,] "1770" [43,] "0.0153485597681537" [44,] "0.0994008712661017" [45,] "0.0994008712661018" [46,] "-994008702.413015" [47,] "-50309167192821240" [48,] "-51161864941852104" [49,] "3.53565863268532" [50,] "60" > (arm <- mean(x)) [1] 5e-11 > sqrtn <- sqrt(length(x)) > (armse <- sd(x) / sqrtn) [1] 0.01130949 > (armose <- arm / armse) [1] 4.421064e-09 > (geo <- geomean(x)) [1] NaN Warning message: In log(x) : NaNs produced > (har <- harmean(x)) [1] 0.08198552 > (qua <- quamean(x)) [1] 0.08686988 > (win <- winmean(x)) [,1] [,2] [1,] 6.842217e-06 0.010882998 [2,] -3.715147e-04 0.010711444 [3,] -3.940455e-04 0.010568816 [4,] 3.409129e-04 0.010187855 [5,] 9.597023e-04 0.009149166 [6,] 1.913260e-03 0.008843380 [7,] 2.569898e-03 0.008688491 [8,] 3.026245e-03 0.008376089 [9,] 2.857651e-03 0.008315794 [10,] 2.196893e-03 0.008156168 [11,] 3.075737e-03 0.007933827 [12,] 2.267269e-03 0.007650376 [13,] 2.192523e-03 0.007583007 [14,] 2.701185e-03 0.007107833 [15,] 2.895204e-03 0.006919369 [16,] 3.502092e-03 0.006655110 [17,] 2.711416e-03 0.006130374 [18,] 2.476587e-03 0.006039600 [19,] 2.863032e-03 0.005787878 [20,] 3.168657e-03 0.005559204 > (tri <- trimean(x)) [,1] [,2] [1,] 0.0004645838 0.010528667 [2,] 0.0009550212 0.010091410 [3,] 0.0016919856 0.009664566 [4,] 0.0024943053 0.009200766 [5,] 0.0031403230 0.008775701 [6,] 0.0036854782 0.008605879 [7,] 0.0040707431 0.008477009 [8,] 0.0043631156 0.008346364 [9,] 0.0046018426 0.008250366 [10,] 0.0048925412 0.008126176 [11,] 0.0053181699 0.007988075 [12,] 0.0056579324 0.007846914 [13,] 0.0061565594 0.007711187 [14,] 0.0067282954 0.007520647 [15,] 0.0073035969 0.007370432 [16,] 0.0079333674 0.007184642 [17,] 0.0085724937 0.006970211 [18,] 0.0094344169 0.006793039 [19,] 0.0104886335 0.006501380 [20,] 0.0116926759 0.006091723 > (midr <- midrange(x)) [1] -0.01347293 > midm <- array(NA,dim=8) > for (j in 1:8) midm[j] <- midmean(x,j) > midm [1] 0.004880625 0.007303597 0.004880625 0.007303597 0.007303597 0.004880625 [7] 0.007303597 0.006728295 > postscript(file="/var/www/rcomp/tmp/1oswd1256471250.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/rcomp/tmp/2grbd1256471250.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/rcomp/tmp/39jmo1256471251.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/rcomp/tmp/4l5dz1256471251.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/rcomp/tmp/5pj9f1256471251.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/rcomp/tmp/62e4u1256471251.tab") > postscript(file="/var/www/rcomp/tmp/7fz7c1256471251.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > myhist<-hist(x) > dev.off() null device 1 > myhist $breaks [1] -0.25 -0.20 -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0.20 $counts [1] 1 3 3 13 5 16 14 4 1 $intensities [1] 0.3333333 1.0000000 1.0000000 4.3333333 1.6666667 5.3333333 4.6666667 [8] 1.3333333 0.3333333 $density [1] 0.3333333 1.0000000 1.0000000 4.3333333 1.6666667 5.3333333 4.6666667 [8] 1.3333333 0.3333333 $mids [1] -0.225 -0.175 -0.125 -0.075 -0.025 0.025 0.075 0.125 0.175 $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$density[i],6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/8vu701256471251.tab") > postscript(file="/var/www/rcomp/tmp/9tjuq1256471251.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > mydensity1<-density(x,kernel='gaussian',na.rm=TRUE) > plot(mydensity1,main='Gaussian Kernel') > grid() > dev.off() null device 1 > mydensity1 Call: density.default(x = x, kernel = "gaussian", na.rm = TRUE) Data: x (60 obs.); Bandwidth 'bw' = 0.03476 x y Min. :-0.32504 Min. :0.002169 1st Qu.:-0.16926 1st Qu.:0.187924 Median :-0.01347 Median :1.018037 Mean :-0.01347 Mean :1.603143 3rd Qu.: 0.14231 3rd Qu.:3.091165 Max. : 0.29810 Max. :4.611183 > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Properties of Density Trace',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Bandwidth',header=TRUE) > a<-table.element(a,mydensity1$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/rcomp/tmp/10iymh1256471251.tab") > > system("convert tmp/1oswd1256471250.ps tmp/1oswd1256471250.png") > system("convert tmp/2grbd1256471250.ps tmp/2grbd1256471250.png") > system("convert tmp/5pj9f1256471251.ps tmp/5pj9f1256471251.png") > system("convert tmp/7fz7c1256471251.ps tmp/7fz7c1256471251.png") > system("convert tmp/9tjuq1256471251.ps tmp/9tjuq1256471251.png") > > > proc.time() user system elapsed 1.330 1.010 2.416