datareeks - evolutie graan - marie-laure van thielen

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sat, 08 Nov 2008 10:55:47 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Nov/08/t12261669852oq078wwt05p7q2.htm/, Retrieved Sat, 08 Nov 2008 17:56:27 +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/Nov/08/t12261669852oq078wwt05p7q2.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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Original text written by user:

IsPrivate?

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User-defined keywords:

Dataseries X:

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93,4 96,3 97 97,4 97,8 98,1 98,4 98,5 98,5 98,6 99 99,5 99,7 100,3 100,7 100,8 101,1 101,2 101,4 102,3 103,7 103,8 104,7 108,2 108,8 109,5 109,5 110,2 110,8 110,8 110,8 111,1 111,2 111,2 111,4 111,4 112,1 112,5 113 114 114,1 114,4 114,9 115,1 115,3 115,4 115,5 116 116 117,2 117,6 119,1 119,2 119,9 121,7 124,5 125,6 126,5 127,3 127,8 129,8 130,7 131,3 131,8 134,2 134,5 137,1 137,3 137,4 139,9 140,3 141,4 143 159,3 169,6 170,4 172,3 175 175,8 177,7 180,3 180,9 184,6 184,8 211,4 215,3 215,9 244,7 259,3 273,9 284,7 289 310,9 314,1 315,1 321 333,2

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 142.780412371134 6.02673679163251 23.6911644406587 Geometric Mean 134.004891051931 Harmonic Mean 127.811378859765 Quadratic Mean 154.509273401341 Winsorized Mean ( 1 / 32 ) 142.684536082474 5.98403200583307 23.844213390468 Winsorized Mean ( 2 / 32 ) 142.577319587629 5.94560655772392 23.9802816085109 Winsorized Mean ( 3 / 32 ) 142.558762886598 5.93529268114572 24.0188261211542 Winsorized Mean ( 4 / 32 ) 142.443298969072 5.89448201164466 24.1655328980007 Winsorized Mean ( 5 / 32 ) 141.329896907216 5.56896954076994 25.378105567386 Winsorized Mean ( 6 / 32 ) 141.082474226804 5.49452164099652 25.6769348534619 Winsorized Mean ( 7 / 32 ) 140.310309278351 5.28515790510628 26.5479881202393 Winsorized Mean ( 8 / 32 ) 139.106185567010 4.97490692517561 27.9615654441817 Winsorized Mean ( 9 / 32 ) 137.760824742268 4.64079256841088 29.6847624002812 Winsorized Mean ( 10 / 32 ) 134.832989690722 3.9610752996271 34.0394916762666 Winsorized Mean ( 11 / 32 ) 134.821649484536 3.94126803201466 34.207683514389 Winsorized Mean ( 12 / 32 ) 134.363917525773 3.83717661407795 35.0163495297075 Winsorized Mean ( 13 / 32 ) 130.879381443299 3.13148740299574 41.7946376913709 Winsorized Mean ( 14 / 32 ) 130.908247422680 3.12046463674731 41.9515241035181 Winsorized Mean ( 15 / 32 ) 130.351546391753 3.01768061458980 43.1959385501343 Winsorized Mean ( 16 / 32 ) 130.30206185567 2.99540562405551 43.5006400499619 Winsorized Mean ( 17 / 32 ) 129.863917525773 2.91504981654154 44.5494676587881 Winsorized Mean ( 18 / 32 ) 129.548453608247 2.85131515195967 45.4346316362856 Winsorized Mean ( 19 / 32 ) 129.568041237113 2.80688071570845 46.160864803409 Winsorized Mean ( 20 / 32 ) 129.3 2.68454794712487 48.1645336744606 Winsorized Mean ( 21 / 32 ) 128.910309278350 2.61406595504065 49.3140997570376 Winsorized Mean ( 22 / 32 ) 128.932989690722 2.56381429359949 50.289519803599 Winsorized Mean ( 23 / 32 ) 127.320618556701 2.08571733260936 61.0440430091335 Winsorized Mean ( 24 / 32 ) 123.436082474227 1.46036494636151 84.5241340404446 Winsorized Mean ( 25 / 32 ) 123.204123711340 1.38463270459884 88.9796429783414 Winsorized Mean ( 26 / 32 ) 122.909278350515 1.34458558690143 91.41052793356 Winsorized Mean ( 27 / 32 ) 122.992783505155 1.30956142764693 93.9190639771305 Winsorized Mean ( 28 / 32 ) 122.444329896907 1.19638807888262 102.344993282836 Winsorized Mean ( 29 / 32 ) 122.414432989691 1.19249783844524 102.653798642766 Winsorized Mean ( 30 / 32 ) 122.352577319588 1.18446514237612 103.297744224148 Winsorized Mean ( 31 / 32 ) 121.617525773196 1.06853426995087 113.817150458625 Winsorized Mean ( 32 / 32 ) 121.551546391753 1.05274566702381 115.461454935633 Trimmed Mean ( 1 / 32 ) 141.295789473684 5.78950375030369 24.4055096201073 Trimmed Mean ( 2 / 32 ) 139.847311827957 5.56324460090297 25.1377248099532 Trimmed Mean ( 3 / 32 ) 138.392307692308 5.32306136058196 25.9986309226346 Trimmed Mean ( 4 / 32 ) 136.878651685393 5.04456682210187 27.1338762102791 Trimmed Mean ( 5 / 32 ) 135.327586206897 4.72847553232653 28.619707405002 Trimmed Mean ( 6 / 32 ) 133.957647058824 4.46156206597477 30.0248310071545 Trimmed Mean ( 7 / 32 ) 133.957647058824 4.16346271622797 32.1745758732738 Trimmed Mean ( 8 / 32 ) 131.245679012346 3.86303071761736 33.9747955960587 Trimmed Mean ( 9 / 32 ) 130.039240506329 3.58320010669427 36.2913699023911 Trimmed Mean ( 10 / 32 ) 128.958441558442 3.329953923521 38.7267945804141 Trimmed Mean ( 11 / 32 ) 128.198666666667 3.18755490655177 40.2184967553545 Trimmed Mean ( 12 / 32 ) 127.398630136986 3.01990573423211 42.1862936623685 Trimmed Mean ( 13 / 32 ) 126.605633802817 2.83928100919774 44.5907373707227 Trimmed Mean ( 14 / 32 ) 126.605633802817 2.76889115339621 45.7243086813028 Trimmed Mean ( 15 / 32 ) 125.650746268657 2.68552359248279 46.7881744254168 Trimmed Mean ( 16 / 32 ) 125.183076923077 2.60396200458105 48.0740796919644 Trimmed Mean ( 17 / 32 ) 124.690476190476 2.50826663392058 49.7118107398243 Trimmed Mean ( 18 / 32 ) 124.206557377049 2.40662322537628 51.6103044578692 Trimmed Mean ( 19 / 32 ) 123.718644067797 2.29361739175903 53.9404019660462 Trimmed Mean ( 20 / 32 ) 123.194736842105 2.16038237624916 57.0245055673871 Trimmed Mean ( 21 / 32 ) 122.656363636364 2.01764566542822 60.7918257095609 Trimmed Mean ( 22 / 32 ) 122.111320754717 1.85072390100353 65.9803013774794 Trimmed Mean ( 23 / 32 ) 121.521568627451 1.64062712477664 74.0701935206608 Trimmed Mean ( 24 / 32 ) 121.022448979592 1.49358681559939 81.0280645996625 Trimmed Mean ( 25 / 32 ) 121.022448979592 1.4606176975841 82.8570331441048 Trimmed Mean ( 26 / 32 ) 120.608888888889 1.43173562194057 84.2396368719357 Trimmed Mean ( 27 / 32 ) 120.409302325581 1.40120899369195 85.9324361088516 Trimmed Mean ( 28 / 32 ) 120.409302325581 1.36588621476879 88.1547093920729 Trimmed Mean ( 29 / 32 ) 119.982051282051 1.34315313650713 89.3286461691665 Trimmed Mean ( 30 / 32 ) 119.762162162162 1.31050474740202 91.386286390478 Trimmed Mean ( 31 / 32 ) 119.762162162162 1.26513749021506 94.6633572148778 Trimmed Mean ( 32 / 32 ) 119.324242424242 1.23403463606656 96.6944030068586 Median 116 Midrange 213.3 Midmean - Weighted Average at Xnp 120.564583333333 Midmean - Weighted Average at X(n+1)p 121.022448979592 Midmean - Empirical Distribution Function 121.022448979592 Midmean - Empirical Distribution Function - Averaging 121.022448979592 Midmean - Empirical Distribution Function - Interpolation 121.022448979592 Midmean - Closest Observation 120.766 Midmean - True Basic - Statistics Graphics Toolkit 121.022448979592 Midmean - MS Excel (old versions) 121.022448979592 Number of observations 97

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/08/t12261669852oq078wwt05p7q2/1oxl41226166945.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/08/t12261669852oq078wwt05p7q2/1oxl41226166945.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/08/t12261669852oq078wwt05p7q2/2t5rq1226166945.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/08/t12261669852oq078wwt05p7q2/2t5rq1226166945.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')

Copyright

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 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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