Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
-7.34658641160771 -3.83393270509369 0.601079165691683 10.1708123315412 -19.3839869794366 76.9922425740188 5.53070349660019 -40.6642925799496 7.8923727519013 17.2902637570394 12.6760697817719 19.6464948843585 -22.8607017650403 24.2145566602915 -102.787405880591 -22.146815361688 19.5158080760987 -27.5133483228973 32.8225102202477 -23.6235769736771 9.83643314161895 4.60698806707138 70.5427891086114 50.22081902765 -0.610172080927745 109.512600045334 38.3844237614283 -17.1329178076636 9.8914651620462 8.93506884166259 -50.6089193933982 6.24830624992741 -15.4577854355838 17.4048085530475 -39.2380533193169 -41.6349321334386 5.69033922999012 31.4039155628394 20.6034212187875 4.54632743294802 -32.8317960857245 5.29772239563854 18.8811727936388 21.0417879652906 -34.8082213857578 32.3312855186524 -31.5422133188891 -6.96524384146907 -51.1887131351437 -19.6210349753855 16.3293278006868 -54.3249050913562 11.0791037716048 51.4231162089253 -17.4375959401962 -28.8303943807569 23.0112582539784 -6.31347225533266 -53.84077421835 -12.249523516243 13.1904099411244 8.39642203599641 -42.7811420681512 59.8084957547755 36.2483062499274 -29.8633361331903 38.3824605416578 76.0113792797905 45.9664338814935 -1.17612597762016 21.4146723322159 -26.7205970597838 -36.2752826830959 -1.78601535890883 -12.2530318706035 2.56265100567706 1.16142391932059 9.31058249798772 -27.9481685557842 -35.9069347340566 -16.4696314381812 7.28921972470831 -19.3587966655329 1.19328162042654 22.2468389243388 0.588096592448664 -19.1512627690298 -32.8384189427771 -19.9199397354674 28.5582080595397 -27.2895444904127 20.3171435437495 39.2813121694082 -9.73130430948931 -0.942375677488173 9.60548926754502 18.1714456892322 -4.93840200425281 -7.56232751201247 12.8399739909504 -30.4867554511851 -3.63900096482928 -17.8985321242085 30.4073651037041 -5.7272065943191 -9.33170040228832 -5.54115129593736 -14.7961174338129 -55.8251391362126 -7.45031070418756 7.46339499060845 3.41546646113856 -77.9853494545382 -70.9245602064598 25.0086309727327 29.2440128930041 10.2707157618025 -13.3739967262292 60.4465269458381 27.8033040934051 28.783673988851 -65.8301244767567 18.4628713819454 -89.4987213214184 -19.623252462839 -11.2502101051705 9.82813335318713 -20.7816766235179 40.6664595968392 -28.5945915143623 -10.6826220633439 26.0439497578208 -9.82613598785401 -7.37666572389216 -50.7149932897269 -40.8176172241267 -1.70087235956341 -99.8017389500321 14.1375276385751 -11.3700983552581 -11.5851921361629 43.8639647275284 32.0648275157806 1.17526571711362 15.5921920420822 5.30726906493567 0.309518089321935 -25.6242515771811 0.855347084597148 45.82596028482 34.6050928277554 -22.2974114549406 25.724966525478 38.2553520465631 -20.4191182276973 5.13598732690237 36.9150764336932 -22.4415575475537 17.9049156953637 -14.7084067380213 20.6994781446868 4.38462512248504 35.8516667812385 -124.97712092823 64.3234036524464 -31.3808056049636 22.9818734549562 9.22512141838141 7.16267812199563 -6.14015849546619 10.5281938816587 19.0310230212635 40.8664924012808 38.6731382905774 38.6731382905774 28.9974598982497 -6.40376507741122 23.1365593461027 56.3239790494825 -81.4622605682183 -6.58429493929693 26.0776190049686 19.861114006955 5.20928321135139 57.0212696008941 9.45682352090344 7.45682352090344 12.4568235209034 16.306500717659 -34.7239638045267 -27.969678691805 33.4925597898478 -10.2838683863397 22.2460928279007 -13.1050628287336 -18.4535558221218 9.35706193361561 3.31777871462932 -9.6207490651828 18.7281864038017 89.783673988851 -23.6846828893207 13.0052033197453 21.7361067500842 -3.67581318460958 -28.9608756213021 -76.9932529907464 -32.6912391121651 49.37539265306 17.3415441214018 -49.6868480326369 25.4616632245656 -21.8286948794475 -12.784343749941 14.6582683760197 -21.787055413815 9.07381431646217 48.8846677481931 -33.938148589021 10.7993040682602 13.2288911666416 -33.8784514839943 -23.4321103218372 7.38081929087432 39.5195070781681 -41.8079987923958 9.44010451918122 1.73576760864494 -11.368712656493 14.4103106601748 36.7926918156455 11.4415062241488 3.58294561440226 42.2508217717385 -29.784849680975 -79.348398518174 -47.2453527162769 22.0010904512135 -55.9351724842194 -1.49485326878918 -25.0235049393696 -28.1146659080171 15.240449060843 64.3234036524464 -1.8963136481531 29.7923853622617 31.3960625611379 -13.8095321274412 -7.75535772813713 10.663145044613 12.0411114253833 -54.9164187819607 5.60624912728185 -11.4532615656104 36.1205139843701 14.201605571223 -21.5211895057792 -47.5902501757404 11.8037424584266 25.0071469888737 -31.3808056049636 -9.64807162553253 7.74461357566997 15.240449060843 8.14127045873426 -17.663610396475 -23.8619452129315 22.111100502846 24.4276514774178 -35.2637422077927 25.4358785498882 -11.1428696590303 9.01713310814046 12.6078628048154 19.1899681873745 -22.1745442232816 21.1920012076042 -67.4087619189757
Chart options
Title:
Y-axis minimum
Y-axis maximum
R Code
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,'Arithmetic Mean',header=TRUE) a<-table.element(a,signif(arm,6)) a<-table.element(a, signif(armse,6)) a<-table.element(a,signif(armose,6)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Geometric Mean',header=TRUE) a<-table.element(a,signif(geo,6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Harmonic Mean',header=TRUE) a<-table.element(a,signif(har,6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Quadratic Mean',header=TRUE) a<-table.element(a,signif(qua,6)) 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, mylabel,header=TRUE) a<-table.element(a,signif(win[j,1],6)) a<-table.element(a,signif(win[j,2],6)) a<-table.element(a,signif(win[j,1]/win[j,2],6)) 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, mylabel,header=TRUE) a<-table.element(a,signif(tri[j,1],6)) a<-table.element(a,signif(tri[j,2],6)) a<-table.element(a,signif(tri[j,1]/tri[j,2],6)) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a, 'Median',header=TRUE) a<-table.element(a,signif(median(x),6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Midrange',header=TRUE) a<-table.element(a,signif(midr,6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[1],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[2],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[3],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[4],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[5],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'Closest Observation',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[6],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[7],6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- 'Midmean' mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,signif(midm[8],6)) 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,signif(length(x),6)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation