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(20 + ,25 + ,15 + ,15 + ,25 + ,25 + ,25 + ,21 + ,30 + ,25 + ,20 + ,40 + ,13 + ,30 + ,25 + ,20 + ,25 + ,20 + ,25 + ,20 + ,20 + ,15 + ,15 + ,12 + ,20 + ,5 + ,20 + ,15 + ,25 + ,22 + ,20 + ,22 + ,25 + ,20 + ,20 + ,35 + ,30 + ,25 + ,20 + ,20 + ,20 + ,25 + ,25 + ,15 + ,20 + ,35 + ,25 + ,25 + ,30 + ,23 + ,10 + ,22 + ,25 + ,25 + ,22 + ,30 + ,20 + ,25 + ,25 + ,22 + ,25 + ,25 + ,25 + ,22 + ,25 + ,12 + ,18 + ,20 + ,20 + ,22 + ,30 + ,25 + ,22 + ,20 + ,50 + ,30 + ,25 + ,20 + ,30 + ,22 + ,25 + ,30 + ,22 + ,25 + ,22 + ,22 + ,25 + ,25 + ,25 + ,20 + ,22 + ,15 + ,20 + ,30 + ,20 + ,25 + ,30 + ,35 + ,22 + ,12 + ,30 + ,15 + ,10 + ,30 + ,9 + ,25 + ,20 + ,20 + ,35 + ,25 + ,35 + ,30 + ,12 + ,25 + ,15 + ,25 + ,25 + ,20 + ,20 + ,6 + ,15 + ,40 + ,20 + ,40 + ,25 + ,25 + ,20 + ,15 + ,15 + ,22 + ,24 + ,22 + ,20 + ,25 + ,25 + ,25 + ,35 + ,40 + ,20 + ,22 + ,22 + ,20 + ,25 + ,25 + ,18 + ,25 + ,20 + ,25 + ,30 + ,20 + ,22 + ,35 + ,22 + ,25 + ,25 + ,25 + ,25 + ,22 + ,23 + ,35 + ,15 + ,25 + ,18 + ,22 + ,25 + ,25 + ,28 + ,30 + ,20 + ,25 + ,25 + ,30 + ,22 + ,30 + ,10 + ,10 + ,25 + ,20 + ,22 + ,25 + ,25 + ,15 + ,22 + ,25 + ,25 + ,28 + ,22 + ,30 + ,25 + ,20 + ,25 + ,25 + ,20 + ,30 + ,20 + ,30 + ,50 + ,19 + ,20 + ,28 + ,20 + ,25 + ,35 + ,25 + ,25 + ,15 + ,16 + ,20 + ,20 + ,25 + ,30 + ,20 + ,25 + ,25 + ,25 + ,20 + ,20 + ,25 + ,25 + ,30 + ,22 + ,20 + ,25 + ,25 + ,18 + ,18 + ,20 + ,25 + ,25 + ,30 + ,25 + ,20 + ,25 + ,20 + ,20 + ,20 + ,22 + ,18 + ,22 + ,20 + ,15 + ,25 + ,25 + ,20 + ,25 + ,15 + ,22 + ,25 + ,25 + ,15 + ,12 + ,25 + ,30 + ,22 + ,15 + ,22 + ,25 + ,12 + ,18 + ,30 + ,25 + ,25 + ,40 + ,24 + ,25 + ,15 + ,25 + ,20 + ,25 + ,25 + ,25 + ,20 + ,30 + ,20 + ,25 + ,30 + ,22 + ,25 + ,25 + ,25 + ,50 + ,19 + ,50 + ,25 + ,35 + ,20 + ,20 + ,20 + ,20 + ,20 + ,25 + ,25 + ,25 + ,20 + ,20 + ,20 + ,20 + ,25 + ,18 + ,25 + ,22 + ,22 + ,30 + ,30 + ,8 + ,20 + ,25 + ,30 + ,50 + ,22 + ,20 + ,10 + ,25 + ,25 + ,25 + ,25 + ,18 + ,25 + ,20 + ,25 + ,30 + ,18 + ,20 + ,25 + ,22 + ,22 + ,20 + ,20 + ,25 + ,20 + ,20 + ,20 + ,20 + ,25 + ,20 + ,10 + ,20 + ,25 + ,30 + ,25 + ,50 + ,30 + ,30 + ,50 + ,15 + ,25 + ,25 + ,22 + ,20 + ,22 + ,30 + ,25 + ,18 + ,22 + ,22 + ,30 + ,40 + ,25 + ,20 + ,10 + ,20 + ,9 + ,15 + ,20 + ,15 + ,20 + ,30 + ,12 + ,15 + ,12 + ,20 + ,15 + ,12 + ,25 + ,20 + ,25 + ,25 + ,25 + ,30 + ,20 + ,25 + ,15 + ,15 + ,22 + ,10 + ,15 + ,10 + ,20 + ,25 + ,20 + ,20 + ,38 + ,20 + ,20 + ,20 + ,40 + ,25 + ,25 + ,30 + ,25 + ,10 + ,20 + ,25 + ,12 + ,15 + ,25 + ,20 + ,22 + ,22 + ,20 + ,25 + ,25 + ,25 + ,15 + ,40 + ,20 + ,20 + ,16 + ,25 + ,15 + ,20 + ,25 + ,20 + ,30 + ,50 + ,20 + ,25 + ,20 + ,30 + ,30 + ,25 + ,25 + ,12 + ,25 + ,25 + ,25 + ,20 + ,20 + ,20 + ,15 + ,20 + ,25 + ,15 + ,25 + ,50 + ,30 + ,20 + ,20 + ,25 + ,12 + ,15 + ,20 + ,20 + ,35 + ,22 + ,15 + ,18 + ,30 + ,22 + ,12 + ,12 + ,20 + ,20 + ,15 + ,25 + ,15 + ,20 + ,20 + ,25 + ,18 + ,30 + ,20 + ,25 + ,25 + ,25 + ,20 + ,20 + ,25 + ,20 + ,22 + ,15 + ,15 + ,22 + ,20 + ,10 + ,25 + ,20 + ,20 + ,15 + ,12 + ,20 + ,5 + ,20 + ,15 + ,15 + ,25 + ,25 + ,25 + ,15 + ,25 + ,22 + ,25 + ,20 + ,18 + ,22 + ,25 + ,35 + ,25 + ,25 + ,25 + ,35 + ,30 + ,22 + ,30 + ,50 + ,15 + ,25 + ,24 + ,20 + ,25 + ,25 + ,25 + ,12 + ,15 + ,22 + ,25 + ,25 + ,25 + ,25 + ,15 + ,20 + ,20 + ,15 + ,35 + ,30 + ,20 + ,22 + ,65 + ,20 + ,25 + ,22 + ,20 + ,25 + ,25 + ,20 + ,25 + ,15 + ,20 + ,12 + ,15 + ,10 + ,25 + ,15 + ,30 + ,35 + ,25 + ,25 + ,25 + ,25 + ,25 + ,40 + ,40 + ,25 + ,25 + ,20 + ,25 + ,25 + ,22 + ,25 + ,30 + ,25 + ,25 + ,30 + ,25 + ,25 + ,30 + ,25 + ,25 + ,20 + ,22 + ,22 + ,20 + ,25 + ,22 + ,25 + ,22 + ,40 + ,25 + ,25 + ,25 + ,22 + ,20 + ,35 + ,20 + ,35 + ,25 + ,22 + ,25 + ,25 + ,25 + ,25 + ,25 + ,40 + ,25 + ,30 + ,25 + ,20 + ,25 + ,25 + ,30 + ,22 + ,22 + ,20 + ,15 + ,15 + ,25 + ,25 + ,20 + ,20 + ,15 + ,25 + ,15 + ,20 + ,22 + ,25 + ,15 + ,15 + ,18 + ,5 + ,15 + ,25 + ,18 + ,40 + ,25 + ,25 + ,20 + ,30 + ,20 + ,25 + ,25 + ,25 + ,22 + ,22 + ,25 + ,25 + ,30 + ,25 + ,25 + ,25 + ,25 + ,20 + ,20 + ,25 + ,25 + ,25 + ,25 + ,20 + ,30 + ,25 + ,22 + ,30 + ,20 + ,20 + ,30 + ,25 + ,25 + ,30 + ,20 + ,25 + ,25 + ,24 + ,25 + ,30 + ,18 + ,15 + ,22 + ,22 + ,25 + ,22 + ,22 + ,25 + ,15 + ,20 + ,22 + ,18 + ,35 + ,20 + ,20 + ,20 + ,25 + ,25 + ,30 + ,15 + ,25 + ,22 + ,26 + ,25 + ,20 + ,25 + ,25 + ,25 + ,22 + ,25 + ,25 + ,20 + ,22 + ,30 + ,15 + ,30 + ,25 + ,20 + ,25 + ,25 + ,35 + ,22 + ,20 + ,25 + ,20 + ,20 + ,18 + ,20 + ,22 + ,25 + ,10 + ,20 + ,25 + ,20 + ,20 + ,30 + ,25 + ,20 + ,15 + ,20 + ,25 + ,10 + ,20 + ,25 + ,22 + ,22 + ,25 + ,25 + ,15 + ,25 + ,20 + ,10 + ,25 + ,16 + ,25 + ,35 + ,25 + ,15 + ,25 + ,25 + ,30 + ,25 + ,10 + ,22 + ,20 + ,25 + ,20 + ,20 + ,25 + ,22 + ,18 + ,30 + ,19 + ,25 + ,20 + ,25 + ,20 + ,25 + ,20 + ,22 + ,12 + ,30 + ,12 + ,22 + ,25 + ,25 + ,25 + ,25 + ,30 + ,30 + ,10 + ,22 + ,22 + ,25 + ,20 + ,22 + ,20 + ,25 + ,20 + ,15 + ,25 + ,20 + ,25 + ,20 + ,30 + ,15 + ,40 + ,25 + ,20 + ,22 + ,22 + ,30 + ,20 + ,40 + ,20 + ,25 + ,20 + ,25 + ,20 + ,50 + ,50 + ,25 + ,25 + ,40 + ,30 + ,22 + ,30 + ,20 + ,25 + ,25 + ,30 + ,25 + ,25 + ,20 + ,18 + ,18 + ,28 + ,25 + ,22 + ,15 + ,40 + ,40 + ,12 + ,12 + ,18 + ,12 + ,25 + ,26 + ,18 + ,25 + ,22 + ,15 + ,25 + ,15 + ,15 + ,15 + ,25 + ,15 + ,12 + ,22 + ,20 + ,20 + ,25 + ,20 + ,12 + ,9 + ,15 + ,12 + ,15 + ,25 + ,20 + ,20 + ,15 + ,15 + ,30 + ,21 + ,25 + ,22 + ,22 + ,50 + ,15 + ,25 + ,15 + ,25 + ,22 + ,18 + ,50 + ,20 + ,50 + ,20 + ,20 + ,30 + ,25 + ,20 + ,22 + ,25 + ,50 + ,40 + ,25 + ,25 + ,25 + ,25 + ,30 + ,40 + ,25 + ,30 + ,20) > ylimmax = '' > ylimmin = '' > main = 'Robustness of Central Tendency' > #'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!) > 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] + } + } + } + } > 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) + } > (arm <- mean(x)) [1] 23.16556 > sqrtn <- sqrt(length(x)) > (armse <- sd(x) / sqrtn) [1] 0.2312245 > (armose <- arm / armse) [1] 100.1864 > (geo <- geomean(x)) [1] 22.16958 > (har <- harmean(x)) [1] 21.08367 > (qua <- quamean(x)) [1] 24.18073 > (win <- winmean(x)) [,1] [,2] [1,] 23.14889 0.22845434 [2,] 23.14889 0.22845434 [3,] 23.15222 0.22816769 [4,] 23.16111 0.22746647 [5,] 23.16667 0.22706774 [6,] 23.16667 0.22706774 [7,] 23.16667 0.22706774 [8,] 23.17556 0.22647166 [9,] 23.17556 0.22647166 [10,] 23.17556 0.22647166 [11,] 23.17556 0.22647166 [12,] 23.17556 0.22647166 [13,] 23.17556 0.22647166 [14,] 23.17556 0.22647166 [15,] 23.17556 0.22647166 [16,] 23.17556 0.22647166 [17,] 22.98667 0.20513082 [18,] 22.98667 0.20513082 [19,] 22.98667 0.20513082 [20,] 22.98667 0.20513082 [21,] 22.98667 0.20513082 [22,] 22.98667 0.20513082 [23,] 22.98667 0.20513082 [24,] 22.98667 0.20513082 [25,] 23.04222 0.20147888 [26,] 23.04222 0.20147888 [27,] 23.04222 0.20147888 [28,] 23.04222 0.20147888 [29,] 23.04222 0.20147888 [30,] 23.04222 0.20147888 [31,] 23.04222 0.20147888 [32,] 23.04222 0.20147888 [33,] 23.04222 0.20147888 [34,] 23.04222 0.20147888 [35,] 23.04222 0.20147888 [36,] 23.04222 0.20147888 [37,] 22.96000 0.19408049 [38,] 22.83333 0.18393991 [39,] 22.83333 0.18393991 [40,] 22.83333 0.18393991 [41,] 22.83333 0.18393991 [42,] 22.83333 0.18393991 [43,] 22.83333 0.18393991 [44,] 22.83333 0.18393991 [45,] 22.83333 0.18393991 [46,] 22.83333 0.18393991 [47,] 22.83333 0.18393991 [48,] 22.83333 0.18393991 [49,] 22.83333 0.18393991 [50,] 22.88889 0.18042538 [51,] 23.00222 0.17406279 [52,] 23.00222 0.17406279 [53,] 23.00222 0.17406279 [54,] 23.00222 0.17406279 [55,] 23.00222 0.17406279 [56,] 23.00222 0.17406279 [57,] 23.00222 0.17406279 [58,] 22.68000 0.15288532 [59,] 22.68000 0.15288532 [60,] 22.68000 0.15288532 [61,] 22.68000 0.15288532 [62,] 22.68000 0.15288532 [63,] 22.68000 0.15288532 [64,] 22.68000 0.15288532 [65,] 22.68000 0.15288532 [66,] 22.68000 0.15288532 [67,] 22.68000 0.15288532 [68,] 22.68000 0.15288532 [69,] 22.68000 0.15288532 [70,] 22.68000 0.15288532 [71,] 22.68000 0.15288532 [72,] 22.68000 0.15288532 [73,] 22.68000 0.15288532 [74,] 22.68000 0.15288532 [75,] 22.68000 0.15288532 [76,] 22.68000 0.15288532 [77,] 22.68000 0.15288532 [78,] 22.68000 0.15288532 [79,] 22.68000 0.15288532 [80,] 22.68000 0.15288532 [81,] 22.68000 0.15288532 [82,] 22.68000 0.15288532 [83,] 22.68000 0.15288532 [84,] 22.68000 0.15288532 [85,] 22.68000 0.15288532 [86,] 22.68000 0.15288532 [87,] 22.68000 0.15288532 [88,] 22.68000 0.15288532 [89,] 22.68000 0.15288532 [90,] 22.68000 0.15288532 [91,] 22.68000 0.15288532 [92,] 22.68000 0.15288532 [93,] 22.68000 0.15288532 [94,] 22.68000 0.15288532 [95,] 22.68000 0.15288532 [96,] 22.68000 0.15288532 [97,] 22.68000 0.15288532 [98,] 22.68000 0.15288532 [99,] 22.68000 0.15288532 [100,] 22.68000 0.15288532 [101,] 22.68000 0.15288532 [102,] 22.68000 0.15288532 [103,] 22.68000 0.15288532 [104,] 22.68000 0.15288532 [105,] 22.68000 0.15288532 [106,] 22.68000 0.15288532 [107,] 22.68000 0.15288532 [108,] 22.68000 0.15288532 [109,] 22.68000 0.15288532 [110,] 22.68000 0.15288532 [111,] 22.68000 0.15288532 [112,] 22.68000 0.15288532 [113,] 22.68000 0.15288532 [114,] 22.68000 0.15288532 [115,] 22.68000 0.15288532 [116,] 22.68000 0.15288532 [117,] 22.68000 0.15288532 [118,] 22.68000 0.15288532 [119,] 22.68000 0.15288532 [120,] 22.68000 0.15288532 [121,] 22.68000 0.15288532 [122,] 22.68000 0.15288532 [123,] 22.68000 0.15288532 [124,] 22.68000 0.15288532 [125,] 22.68000 0.15288532 [126,] 22.68000 0.15288532 [127,] 22.68000 0.15288532 [128,] 22.68000 0.15288532 [129,] 22.82333 0.14512602 [130,] 22.82333 0.14512602 [131,] 22.82333 0.14512602 [132,] 23.11667 0.13101785 [133,] 23.11667 0.13101785 [134,] 23.11667 0.13101785 [135,] 23.11667 0.13101785 [136,] 23.11667 0.13101785 [137,] 23.11667 0.13101785 [138,] 22.81000 0.11422445 [139,] 22.81000 0.11422445 [140,] 22.81000 0.11422445 [141,] 22.81000 0.11422445 [142,] 22.49444 0.09997511 [143,] 22.49444 0.09997511 [144,] 22.33444 0.09432240 [145,] 22.33444 0.09432240 [146,] 22.33444 0.09432240 [147,] 22.33444 0.09432240 [148,] 22.33444 0.09432240 [149,] 22.33444 0.09432240 [150,] 22.33444 0.09432240 [151,] 22.33444 0.09432240 [152,] 22.33444 0.09432240 [153,] 22.33444 0.09432240 [154,] 22.33444 0.09432240 [155,] 22.33444 0.09432240 [156,] 22.33444 0.09432240 [157,] 22.50889 0.08587650 [158,] 22.50889 0.08587650 [159,] 22.50889 0.08587650 [160,] 22.68667 0.07841937 [161,] 22.68667 0.07841937 [162,] 22.68667 0.07841937 [163,] 22.68667 0.07841937 [164,] 22.68667 0.07841937 [165,] 22.68667 0.07841937 [166,] 22.68667 0.07841937 [167,] 22.68667 0.07841937 [168,] 22.68667 0.07841937 [169,] 22.68667 0.07841937 [170,] 22.68667 0.07841937 [171,] 22.68667 0.07841937 [172,] 22.68667 0.07841937 [173,] 22.68667 0.07841937 [174,] 22.68667 0.07841937 [175,] 22.68667 0.07841937 [176,] 22.68667 0.07841937 [177,] 22.68667 0.07841937 [178,] 22.68667 0.07841937 [179,] 22.68667 0.07841937 [180,] 22.68667 0.07841937 [181,] 22.68667 0.07841937 [182,] 22.68667 0.07841937 [183,] 22.68667 0.07841937 [184,] 22.68667 0.07841937 [185,] 22.68667 0.07841937 [186,] 22.68667 0.07841937 [187,] 22.68667 0.07841937 [188,] 22.68667 0.07841937 [189,] 22.68667 0.07841937 [190,] 22.68667 0.07841937 [191,] 22.68667 0.07841937 [192,] 22.68667 0.07841937 [193,] 22.68667 0.07841937 [194,] 22.68667 0.07841937 [195,] 22.68667 0.07841937 [196,] 22.68667 0.07841937 [197,] 22.68667 0.07841937 [198,] 22.68667 0.07841937 [199,] 22.68667 0.07841937 [200,] 22.68667 0.07841937 [201,] 22.68667 0.07841937 [202,] 22.68667 0.07841937 [203,] 22.68667 0.07841937 [204,] 22.68667 0.07841937 [205,] 22.68667 0.07841937 [206,] 22.68667 0.07841937 [207,] 22.68667 0.07841937 [208,] 22.68667 0.07841937 [209,] 22.68667 0.07841937 [210,] 22.68667 0.07841937 [211,] 22.68667 0.07841937 [212,] 22.68667 0.07841937 [213,] 22.68667 0.07841937 [214,] 22.68667 0.07841937 [215,] 22.68667 0.07841937 [216,] 22.68667 0.07841937 [217,] 22.68667 0.07841937 [218,] 22.68667 0.07841937 [219,] 22.68667 0.07841937 [220,] 22.68667 0.07841937 [221,] 22.68667 0.07841937 [222,] 22.68667 0.07841937 [223,] 22.68667 0.07841937 [224,] 22.68667 0.07841937 [225,] 22.68667 0.07841937 [226,] 22.68667 0.07841937 [227,] 22.68667 0.07841937 [228,] 22.68667 0.07841937 [229,] 22.68667 0.07841937 [230,] 22.68667 0.07841937 [231,] 22.68667 0.07841937 [232,] 22.68667 0.07841937 [233,] 22.68667 0.07841937 [234,] 22.68667 0.07841937 [235,] 22.68667 0.07841937 [236,] 22.68667 0.07841937 [237,] 22.68667 0.07841937 [238,] 22.68667 0.07841937 [239,] 22.68667 0.07841937 [240,] 22.68667 0.07841937 [241,] 22.68667 0.07841937 [242,] 22.68667 0.07841937 [243,] 22.68667 0.07841937 [244,] 22.68667 0.07841937 [245,] 22.68667 0.07841937 [246,] 22.68667 0.07841937 [247,] 22.68667 0.07841937 [248,] 22.68667 0.07841937 [249,] 22.68667 0.07841937 [250,] 22.68667 0.07841937 [251,] 22.68667 0.07841937 [252,] 22.68667 0.07841937 [253,] 22.68667 0.07841937 [254,] 22.68667 0.07841937 [255,] 22.68667 0.07841937 [256,] 22.68667 0.07841937 [257,] 22.68667 0.07841937 [258,] 22.68667 0.07841937 [259,] 22.68667 0.07841937 [260,] 22.68667 0.07841937 [261,] 22.68667 0.07841937 [262,] 22.68667 0.07841937 [263,] 22.68667 0.07841937 [264,] 22.68667 0.07841937 [265,] 22.68667 0.07841937 [266,] 22.68667 0.07841937 [267,] 22.68667 0.07841937 [268,] 22.68667 0.07841937 [269,] 22.68667 0.07841937 [270,] 22.68667 0.07841937 [271,] 22.68667 0.07841937 [272,] 22.68667 0.07841937 [273,] 22.68667 0.07841937 [274,] 22.68667 0.07841937 [275,] 22.68667 0.07841937 [276,] 22.68667 0.07841937 [277,] 22.68667 0.07841937 [278,] 22.68667 0.07841937 [279,] 22.68667 0.07841937 [280,] 22.68667 0.07841937 [281,] 22.68667 0.07841937 [282,] 22.68667 0.07841937 [283,] 22.68667 0.07841937 [284,] 22.68667 0.07841937 [285,] 22.68667 0.07841937 [286,] 22.68667 0.07841937 [287,] 22.68667 0.07841937 [288,] 22.68667 0.07841937 [289,] 22.68667 0.07841937 [290,] 22.68667 0.07841937 [291,] 22.68667 0.07841937 [292,] 22.68667 0.07841937 [293,] 22.68667 0.07841937 [294,] 22.68667 0.07841937 [295,] 22.68667 0.07841937 [296,] 22.68667 0.07841937 [297,] 22.68667 0.07841937 [298,] 22.68667 0.07841937 [299,] 22.68667 0.07841937 [300,] 22.68667 0.07841937 > (tri <- trimean(x)) [,1] [,2] [1,] 23.13920 0.22609769 [2,] 23.12946 0.22369317 [3,] 23.11969 0.22123897 [4,] 23.10874 0.21883445 [5,] 23.09551 0.21656738 [6,] 23.08108 0.21433987 [7,] 23.06659 0.21206626 [8,] 23.05204 0.20974479 [9,] 23.03628 0.20745759 [10,] 23.02045 0.20512121 [11,] 23.00456 0.20273370 [12,] 22.98858 0.20029296 [13,] 22.97254 0.19779672 [14,] 22.95642 0.19524258 [15,] 22.94023 0.19262795 [16,] 22.92396 0.18995002 [17,] 22.90762 0.18720577 [18,] 22.90278 0.18599260 [19,] 22.89791 0.18475891 [20,] 22.89302 0.18350413 [21,] 22.88811 0.18222770 [22,] 22.88318 0.18092902 [23,] 22.87822 0.17960744 [24,] 22.87324 0.17826233 [25,] 22.86824 0.17689298 [26,] 22.86085 0.17568679 [27,] 22.85343 0.17445933 [28,] 22.84597 0.17321002 [29,] 22.83848 0.17193821 [30,] 22.83095 0.17064327 [31,] 22.82339 0.16932450 [32,] 22.81579 0.16798118 [33,] 22.80815 0.16661256 [34,] 22.80048 0.16521783 [35,] 22.79277 0.16379617 [36,] 22.78502 0.16234668 [37,] 22.77724 0.16086845 [38,] 22.77184 0.15966055 [39,] 22.77007 0.15881517 [40,] 22.76829 0.15795595 [41,] 22.76650 0.15708255 [42,] 22.76471 0.15619463 [43,] 22.76290 0.15529183 [44,] 22.76108 0.15437378 [45,] 22.75926 0.15344008 [46,] 22.75743 0.15249034 [47,] 22.75558 0.15152412 [48,] 22.75373 0.15054098 [49,] 22.75187 0.14954048 [50,] 22.75000 0.14852213 [51,] 22.74687 0.14759464 [52,] 22.74121 0.14683910 [53,] 22.73552 0.14607074 [54,] 22.72980 0.14528925 [55,] 22.72405 0.14449431 [56,] 22.71827 0.14368557 [57,] 22.71247 0.14286268 [58,] 22.70663 0.14202530 [59,] 22.70716 0.14173997 [60,] 22.70769 0.14145018 [61,] 22.70823 0.14115586 [62,] 22.70876 0.14085692 [63,] 22.70930 0.14055330 [64,] 22.70984 0.14024490 [65,] 22.71039 0.13993164 [66,] 22.71094 0.13961344 [67,] 22.71149 0.13929021 [68,] 22.71204 0.13896186 [69,] 22.71260 0.13862830 [70,] 22.71316 0.13828943 [71,] 22.71372 0.13794515 [72,] 22.71429 0.13759538 [73,] 22.71485 0.13724000 [74,] 22.71543 0.13687891 [75,] 22.71600 0.13651201 [76,] 22.71658 0.13613918 [77,] 22.71716 0.13576031 [78,] 22.71774 0.13537529 [79,] 22.71833 0.13498400 [80,] 22.71892 0.13458631 [81,] 22.71951 0.13418210 [82,] 22.72011 0.13377125 [83,] 22.72071 0.13335361 [84,] 22.72131 0.13292906 [85,] 22.72192 0.13249745 [86,] 22.72253 0.13205863 [87,] 22.72314 0.13161247 [88,] 22.72376 0.13115880 [89,] 22.72438 0.13069747 [90,] 22.72500 0.13022832 [91,] 22.72563 0.12975118 [92,] 22.72626 0.12926587 [93,] 22.72689 0.12877223 [94,] 22.72753 0.12827006 [95,] 22.72817 0.12775918 [96,] 22.72881 0.12723939 [97,] 22.72946 0.12671048 [98,] 22.73011 0.12617226 [99,] 22.73077 0.12562450 [100,] 22.73143 0.12506698 [101,] 22.73209 0.12449948 [102,] 22.73276 0.12392174 [103,] 22.73343 0.12333352 [104,] 22.73410 0.12273457 [105,] 22.73478 0.12212462 [106,] 22.73547 0.12150338 [107,] 22.73615 0.12087059 [108,] 22.73684 0.12022592 [109,] 22.73754 0.11956909 [110,] 22.73824 0.11889976 [111,] 22.73894 0.11821759 [112,] 22.73964 0.11752225 [113,] 22.74036 0.11681335 [114,] 22.74107 0.11609053 [115,] 22.74107 0.11535339 [116,] 22.74251 0.11460151 [117,] 22.74324 0.11383446 [118,] 22.74398 0.11305179 [119,] 22.74398 0.11225301 [120,] 22.74545 0.11143764 [121,] 22.74620 0.11060515 [122,] 22.74695 0.10975500 [123,] 22.74695 0.10888660 [124,] 22.74847 0.10799935 [125,] 22.74923 0.10709261 [126,] 22.75000 0.10616570 [127,] 22.75077 0.10521792 [128,] 22.75155 0.10424850 [129,] 22.75234 0.10325665 [130,] 22.75156 0.10241483 [131,] 22.75078 0.10155427 [132,] 22.75000 0.10067432 [133,] 22.74606 0.10006097 [134,] 22.74209 0.09943471 [135,] 22.73810 0.09879515 [136,] 22.73408 0.09814189 [137,] 22.73003 0.09747450 [138,] 22.72596 0.09679256 [139,] 22.72508 0.09643318 [140,] 22.72419 0.09606676 [141,] 22.72330 0.09569311 [142,] 22.72240 0.09531207 [143,] 22.72476 0.09516258 [144,] 22.72712 0.09500976 [145,] 22.73115 0.09493213 [146,] 22.73520 0.09485209 [147,] 22.73927 0.09476960 [148,] 22.74338 0.09468460 [149,] 22.74751 0.09459704 [150,] 22.75167 0.09450687 [151,] 22.75585 0.09441403 [152,] 22.76007 0.09431846 [153,] 22.76431 0.09422011 [154,] 22.76858 0.09411891 [155,] 22.77288 0.09401481 [156,] 22.77721 0.09390774 [157,] 22.78157 0.09379763 [158,] 22.78425 0.09381867 [159,] 22.78694 0.09383875 [160,] 22.78966 0.09385785 [161,] 22.79066 0.09398103 [162,] 22.79167 0.09410460 [163,] 22.79268 0.09422858 [164,] 22.79371 0.09435296 [165,] 22.79474 0.09447775 [166,] 22.79577 0.09460294 [167,] 22.79682 0.09472854 [168,] 22.79787 0.09485454 [169,] 22.79893 0.09498096 [170,] 22.80000 0.09510778 [171,] 22.80108 0.09523501 [172,] 22.80216 0.09536265 [173,] 22.80325 0.09549070 [174,] 22.80435 0.09561917 [175,] 22.80545 0.09574805 [176,] 22.80657 0.09587734 [177,] 22.80769 0.09600705 [178,] 22.80882 0.09613717 [179,] 22.80996 0.09626770 [180,] 22.81111 0.09639865 [181,] 22.81227 0.09653002 [182,] 22.81343 0.09666180 [183,] 22.81461 0.09679400 [184,] 22.81579 0.09692662 [185,] 22.81698 0.09705966 [186,] 22.81818 0.09719311 [187,] 22.81939 0.09732698 [188,] 22.82061 0.09746127 [189,] 22.82184 0.09759597 [190,] 22.82308 0.09773110 [191,] 22.82432 0.09786664 [192,] 22.82558 0.09800260 [193,] 22.82685 0.09813898 [194,] 22.82812 0.09827577 [195,] 22.82941 0.09841298 [196,] 22.83071 0.09855060 [197,] 22.83202 0.09868865 [198,] 22.83333 0.09882710 [199,] 22.83466 0.09896597 [200,] 22.83600 0.09910526 [201,] 22.83735 0.09924495 [202,] 22.83871 0.09938506 [203,] 22.84008 0.09952558 [204,] 22.84146 0.09966650 [205,] 22.84286 0.09980784 [206,] 22.84426 0.09994958 [207,] 22.84568 0.10009172 [208,] 22.84711 0.10023427 [209,] 22.84855 0.10037722 [210,] 22.85000 0.10052057 [211,] 22.85146 0.10066431 [212,] 22.85294 0.10080845 [213,] 22.85443 0.10095298 [214,] 22.85593 0.10109790 [215,] 22.85745 0.10124321 [216,] 22.85897 0.10138890 [217,] 22.86052 0.10153498 [218,] 22.86207 0.10168143 [219,] 22.86364 0.10182826 [220,] 22.86522 0.10197546 [221,] 22.86681 0.10212302 [222,] 22.86842 0.10227095 [223,] 22.87004 0.10241923 [224,] 22.87168 0.10256788 [225,] 22.87333 0.10271687 [226,] 22.87500 0.10286620 [227,] 22.87668 0.10301588 [228,] 22.87838 0.10316589 [229,] 22.87838 0.10331623 [230,] 22.88009 0.10346689 [231,] 22.88356 0.10361787 [232,] 22.88532 0.10376916 [233,] 22.88710 0.10392075 [234,] 22.88889 0.10407264 [235,] 22.89070 0.10422481 [236,] 22.89252 0.10437727 [237,] 22.89252 0.10453000 [238,] 22.89437 0.10468299 [239,] 22.89810 0.10483624 [240,] 22.90000 0.10498973 [241,] 22.90191 0.10514346 [242,] 22.90385 0.10529741 [243,] 22.90580 0.10545158 [244,] 22.90777 0.10560596 [245,] 22.90777 0.10576052 [246,] 22.90976 0.10591527 [247,] 22.91379 0.10607018 [248,] 22.91584 0.10622525 [249,] 22.91791 0.10638046 [250,] 22.92000 0.10653579 [251,] 22.92211 0.10669124 [252,] 22.92424 0.10684678 [253,] 22.92424 0.10700240 [254,] 22.92857 0.10715808 [255,] 22.93077 0.10731381 [256,] 22.93299 0.10746956 [257,] 22.93523 0.10762532 [258,] 22.93750 0.10778107 [259,] 22.93979 0.10793679 [260,] 22.94211 0.10809244 [261,] 22.94444 0.10824803 [262,] 22.94681 0.10840351 [263,] 22.94920 0.10855886 [264,] 22.95161 0.10871406 [265,] 22.95405 0.10886909 [266,] 22.95652 0.10902391 [267,] 22.95902 0.10917849 [268,] 22.96154 0.10933281 [269,] 22.96409 0.10948684 [270,] 22.96667 0.10964053 [271,] 22.96927 0.10979386 [272,] 22.97191 0.10994680 [273,] 22.97458 0.11009929 [274,] 22.97727 0.11025132 [275,] 22.98000 0.11040283 [276,] 22.98276 0.11055378 [277,] 22.98555 0.11070413 [278,] 22.98837 0.11085384 [279,] 22.99123 0.11100286 [280,] 22.99412 0.11115113 [281,] 22.99704 0.11129861 [282,] 23.00000 0.11144525 [283,] 23.00299 0.11159097 [284,] 23.00602 0.11173574 [285,] 23.00909 0.11187948 [286,] 23.01220 0.11202214 [287,] 23.01534 0.11216364 [288,] 23.01852 0.11230392 [289,] 23.02174 0.11244291 [290,] 23.02500 0.11258052 [291,] 23.02830 0.11271668 [292,] 23.03165 0.11285131 [293,] 23.03503 0.11298432 [294,] 23.03846 0.11311562 [295,] 23.04194 0.11324512 [296,] 23.04545 0.11337272 [297,] 23.04902 0.11349832 [298,] 23.05263 0.11362180 [299,] 23.05629 0.11374306 [300,] 23.06000 0.11386197 > (midr <- midrange(x)) [1] 35 > midm <- array(NA,dim=8) > for (j in 1:8) midm[j] <- midmean(x,j) > midm [1] 22.84899 22.84899 22.84899 22.84899 22.84899 22.84899 22.84899 22.84899 > postscript(file="/var/www/html/rcomp/tmp/1qfqk1268676840.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=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, 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/25hsc1268676840.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=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, 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 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > 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/35gha1268676840.tab") > > try(system("convert tmp/1qfqk1268676840.ps tmp/1qfqk1268676840.png",intern=TRUE)) character(0) > try(system("convert tmp/25hsc1268676840.ps tmp/25hsc1268676840.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.495 0.493 8.954