Q6 Error Component

*The author of this computation has been verified*

R Software Module: rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Sat, 25 Oct 2008 06:52:51 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0.htm/, Retrieved Sat, 25 Oct 2008 13:04:01 +0000

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0.htm/}, year = {2008}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2008}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

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0.989130435 0.919087137 0.925417076 0.925612053 1.066666667 0.851108765 1.030693069 0.989031079 0.913000978 0.792723264 0.978170478 0.987513007 0.909433962 0.883608147 0.82745098 0.8252149 1.023255814 0.815418024 1.026192703 0.914742451 0.807276303 0.739130435 0.98973306 0.972164948 0.853889943 0.856864654 0.775739042 0.789473684 0.931350114 0.73971079 0.885245902 0.842435094 0.818458418 0.72755418 0.923238696 0.922680412 0.883762201 0.818270165 0.771047228 0.825852783 0.924485126 0.755165289 0.874671341 0.815956482 0.799807507 0.712598425 0.832980973 0.910323253 0.869149952 0.779182879 0.750254842 0.75856014 0.920889988 0.743991641 0.816254417 0.769593957 0.784007353 0.683284457 0.850505051 0.900695134 0.868398268 0.788480636 0.771610555 0.810645724 0.955503513 0.756218905 0.859756098 0.764806867 0.785651019 0.657843137 0.883018868 0.921177588 0.848484848 0.754948162 0.738334858 0.762798635 0.881081081 0.706333973 0.808 0.794934641 0.744042365 0.656 0.788617886 0.802304965 0.750455373

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 0.842107708388235 0.00981646798961035 85.7852039327703 Geometric Mean 0.837357416906186 Harmonic Mean 0.83266295570438 Quadratic Mean 0.846900164249206 Winsorized Mean ( 1 / 28 ) 0.84170617355294 0.00970484222889624 86.7305365404865 Winsorized Mean ( 2 / 28 ) 0.842198901882353 0.00955358594232475 88.155265150356 Winsorized Mean ( 3 / 28 ) 0.842908759305882 0.0093786830962828 89.8749590590139 Winsorized Mean ( 4 / 28 ) 0.841626015682353 0.00899216961460449 93.5954337777881 Winsorized Mean ( 5 / 28 ) 0.842470317447059 0.00884193672139936 95.2811973205035 Winsorized Mean ( 6 / 28 ) 0.843224293117647 0.00872720580050225 96.6201912035946 Winsorized Mean ( 7 / 28 ) 0.843164793529412 0.0086930619371986 96.9928432145887 Winsorized Mean ( 8 / 28 ) 0.842340118329412 0.00851481546646897 98.9264091096884 Winsorized Mean ( 9 / 28 ) 0.842157505258824 0.0083310380123174 101.08674381436 Winsorized Mean ( 10 / 28 ) 0.840203303964706 0.00797922620097078 105.298845126421 Winsorized Mean ( 11 / 28 ) 0.837881537588235 0.00735802224202543 113.873199893671 Winsorized Mean ( 12 / 28 ) 0.837099768647059 0.0072337245071312 115.721820456644 Winsorized Mean ( 13 / 28 ) 0.837757081070588 0.00713288692333792 117.449931573926 Winsorized Mean ( 14 / 28 ) 0.837639345517647 0.00710554887216891 117.885241603013 Winsorized Mean ( 15 / 28 ) 0.837605319517647 0.00704801232232542 118.842771722239 Winsorized Mean ( 16 / 28 ) 0.83794093382353 0.00697265172548221 120.175360367017 Winsorized Mean ( 17 / 28 ) 0.83848806802353 0.00681570762454625 123.022892737326 Winsorized Mean ( 18 / 28 ) 0.838852437152941 0.00675102677608095 124.255534006326 Winsorized Mean ( 19 / 28 ) 0.839519502341177 0.00655492551220944 128.074606000855 Winsorized Mean ( 20 / 28 ) 0.8388391694 0.00636508841974723 131.787512455846 Winsorized Mean ( 21 / 28 ) 0.838548098035294 0.00628657328546115 133.387150671510 Winsorized Mean ( 22 / 28 ) 0.83892358937647 0.0060549449463704 138.551811256246 Winsorized Mean ( 23 / 28 ) 0.839614819470588 0.00590647636742293 142.151558262634 Winsorized Mean ( 24 / 28 ) 0.838509590105882 0.00539861780153642 155.319309669828 Winsorized Mean ( 25 / 28 ) 0.834449129517647 0.00473697236603372 176.156638679388 Winsorized Mean ( 26 / 28 ) 0.834860821470588 0.00457378885571785 182.531561426781 Winsorized Mean ( 27 / 28 ) 0.834855483729412 0.00456230047668881 182.990026192954 Winsorized Mean ( 28 / 28 ) 0.83494327822353 0.00450367068177114 185.391725377037 Trimmed Mean ( 1 / 28 ) 0.841644440313253 0.00941228833358613 89.4197468760057 Trimmed Mean ( 2 / 28 ) 0.841579658518519 0.00907299676371432 92.7565258134173 Trimmed Mean ( 3 / 28 ) 0.841246521265823 0.00877317727793451 95.888467155639 Trimmed Mean ( 4 / 28 ) 0.840634875233766 0.00850116766586172 98.8846365905142 Trimmed Mean ( 5 / 28 ) 0.840354052106667 0.00832118382233509 100.989723343336 Trimmed Mean ( 6 / 28 ) 0.839861223191781 0.00815351310742999 103.006055442095 Trimmed Mean ( 7 / 28 ) 0.839190188112676 0.00798422090071067 105.106083429879 Trimmed Mean ( 8 / 28 ) 0.838490723391304 0.00779070194091644 107.627108539166 Trimmed Mean ( 9 / 28 ) 0.837880278298507 0.00760109367746637 110.231542176940 Trimmed Mean ( 10 / 28 ) 0.837258800876923 0.0074132106970771 112.941454801364 Trimmed Mean ( 11 / 28 ) 0.836861526650794 0.00726103558752261 115.253742605099 Trimmed Mean ( 12 / 28 ) 0.836732315131148 0.00719564215913882 116.283202614301 Trimmed Mean ( 13 / 28 ) 0.836688199949153 0.00713404594056157 117.281022146500 Trimmed Mean ( 14 / 28 ) 0.836565588754386 0.0070712064037152 118.305921365109 Trimmed Mean ( 15 / 28 ) 0.836447057163636 0.00699325383839924 119.607707154971 Trimmed Mean ( 16 / 28 ) 0.836323217792453 0.00690174332686127 121.175647685639 Trimmed Mean ( 17 / 28 ) 0.836154705705882 0.00679600120330889 123.036279819781 Trimmed Mean ( 18 / 28 ) 0.835916607510204 0.00668663827293157 125.012984610534 Trimmed Mean ( 19 / 28 ) 0.835621636446809 0.0065543843528166 127.490484455297 Trimmed Mean ( 20 / 28 ) 0.835234129311111 0.00641756269071227 130.148183907871 Trimmed Mean ( 21 / 28 ) 0.834877817209302 0.00627443303220839 133.060280175698 Trimmed Mean ( 22 / 28 ) 0.834515478219512 0.00609818901770015 136.846443394475 Trimmed Mean ( 23 / 28 ) 0.83407877723077 0.00591090197227817 141.108545048210 Trimmed Mean ( 24 / 28 ) 0.83352582354054 0.00568676674436393 146.572887725109 Trimmed Mean ( 25 / 28 ) 0.833021513828571 0.00550807445774304 151.236429394585 Trimmed Mean ( 26 / 28 ) 0.832874426151515 0.00542957736894405 153.395811415336 Trimmed Mean ( 27 / 28 ) 0.832664942774194 0.00534502815639359 155.783078855849 Trimmed Mean ( 28 / 28 ) 0.832427144586207 0.00520899184842927 159.805806729611 Median 0.825852783 Midrange 0.8613333335 Midmean - Weighted Average at Xnp 0.833017741952381 Midmean - Weighted Average at X(n+1)p 0.834877817209302 Midmean - Empirical Distribution Function 0.834877817209302 Midmean - Empirical Distribution Function - Averaging 0.834877817209302 Midmean - Empirical Distribution Function - Interpolation 0.834877817209302 Midmean - Closest Observation 0.833427122 Midmean - True Basic - Statistics Graphics Toolkit 0.834877817209302 Midmean - MS Excel (old versions) 0.834877817209302 Number of observations 85

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0/1juim1224939169.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0/1juim1224939169.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0/2tbxy1224939169.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Oct/25/t1224939839mzu3hb0odsr96t0/2tbxy1224939169.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

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)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') 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() bitmap(file='test2.png') 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() load(file='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='mytable.tab')

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This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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