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beste investering 2

*The author of this computation has been verified*
R Software Module: rwasp_hierarchicalclustering.wasp (opens new window with default values)
Title produced by software: Hierarchical Clustering
Date of computation: Wed, 05 Nov 2008 04:33:32 -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/05/t1225885149k4zzxsy23tue1yu.htm/, Retrieved Wed, 05 Nov 2008 11:39:12 +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/05/t1225885149k4zzxsy23tue1yu.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},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:

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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
hierarchical
 
Dataseries X:
» Textbox « » Textfile « » CSV «
100.00 100.00 100.00 100.00 100.00 100.39 100.37 100.35 100.33 100.31 100.15 100.26 100.38 100.50 100.61 100.21 100.37 100.52 100.68 100.84 100.03 100.18 100.34 100.49 100.64 99.58 99.78 99.97 100.17 100.36 99.40 99.64 99.88 100.13 100.37 99.77 100.01 100.26 100.50 100.75 100.41 100.67 100.93 101.19 101.45 100.12 100.50 100.88 101.25 101.63 99.83 100.28 100.73 101.18 101.63 99.73 100.24 100.74 101.25 101.75 98.74 99.49 100.25 101.00 101.76 98.44 99.36 100.29 101.22 102.14 98.79 99.68 100.57 101.46 102.35 99.60 100.42 101.24 102.05 102.87 99.82 100.75 101.69 102.62 103.55 99.85 100.87 101.89 102.90 103.92 100.01 101.04 102.07 103.10 104.13 100.28 101.36 102.43 103.51 104.58 100.63 101.57 102.51 103.45 104.39 101.14 101.93 102.71 103.50 104.29 101.51 102.37 103.22 104.08 104.93 102.41 103.10 103.79 104.48 105.17 102.46 103.22 103.99 104.75 105.52 102.09 102.96 103.83 104.70 105.57 101.99 102.77 103.55 104.33 105.11 101.52 102.38 103.24 104.11 104.97 102.44 103.10 103.77 104.43 105.09 103.42 103.90 104.37 104.85 105.33 103.63 104.12 104.61 105.11 105.60 103.28 103.75 104.21 104.68 105.14 103.98 104.37 104.77 105.16 105.56 103.56 103.94 104.33 104.71 105.09 103.42 103.78 104.14 104.51 104.87 103.92 104.15 104.37 104.59 104.81 103.81 104.01 104.20 104.40 104.60 103.09 103.33 103.58 103.83 104.07 102.60 103.05 103.51 103.96 104.41 102.77 103.08 103.39 103.71 104.02 102.60 102.86 103.11 103.37 103.62 102.88 103.08 103.28 103.48 103.68 102.17 102.50 102.83 103.15 103.48 101.85 102.20 102.56 102.91 103.27 101.66 102.14 102.62 103.10 103.58 101.91 102.28 102.66 103.03 103.41 102.13 102.43 102.72 103.02 103.31 102.71 102.82 102.92 103.02 103.13 103.17 103.22 103.26 103.31 103.36 102.89 102.95 103.02 103.08 103.14 102.94 103.14 103.33 103.53 103.73 103.33 103.45 103.57 103.68 103.80 103.75 103.68 103.61 103.54 103.46 104.11 103.98 103.85 103.72 103.60 104.77 104.49 104.22 103.94 103.67 104.62 104.39 104.15 103.92 103.68 105.00 104.76 104.52 104.28 104.04 105.74 105.51 105.27 105.03 104.79 105.94 105.77 105.60 105.43 105.26 106.37 106.18 105.99 105.80 105.62 106.65 106.44 106.23 106.03 105.82 107.08 106.74 106.40 106.05 105.71 106.77 106.51 106.25 106.00 105.74 107.21 106.97 106.74 106.50 106.26 107.34 107.15 106.96 106.78 106.59 107.12 106.93 106.74 106.55 106.36 106.86 106.73 106.59 106.46 106.33 106.92 106.78 106.65 106.51 106.37 106.95 106.75 106.56 106.36 106.17 107.23 106.96 106.69 106.42 106.16 106.94 106.80 106.66 106.51 106.37 106.62 106.51 106.40 106.29 106.18 105.94 105.97 105.99 106.01 106.03 105.91 105.95 105.99 106.03 106.08 106.52 106.45 106.38 106.31 106.24 106.85 106.63 106.41 106.19 105.97 107.22 106.99 106.75 106.52 106.28 107.28 107.09 106.90 106.71 106.52 107.86 107.57 107.29 107.00 106.72 107.68 107.46 107.24 107.02 106.80 108.07 107.82 107.56 107.31 107.06 107.87 107.66 107.45 107.23 107.02 107.65 107.50 107.35 107.19 107.04 108.16 107.89 107.63 107.36 107.09 108.60 108.24 107.88 107.51 107.15 108.92 108.57 108.21 107.86 107.50 109.66 109.22 108.78 108.34 107.90 109.87 109.40 108.94 108.48 108.02 109.54 109.10 108.66 108.22 107.78 109.06 108.72 108.38 108.04 107.70
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Summary of Dendrogram
LabelHeight
10.0299999999999917
20.0374165738677358
30.0556776436282904
40.0648074069840745
50.100995049383620
60.121243556529820
70.129975734866232
80.134164078649990
90.143527000944077
100.145945195193266
110.146955205859693
120.152970585407785
130.164316767251545
140.176068168616588
150.194679223339306
160.211930677078514
170.231948270094860
180.232379000772445
190.241845085443575
200.248596057893118
210.250998007960231
220.253771550808995
230.268328157299979
240.293257565972305
250.316227766016834
260.356651090002537
270.375233260785878
280.378681924575238
290.38085496566656
300.381847284303828
310.383994393221481
320.389230009120564
330.40332032516851
340.409165803810819
350.409267638593615
360.4135214625627
370.414808290522715
380.4402821682489
390.442012432492449
400.461194102304
410.463357313528128
420.48487111689602
430.501673105968209
440.535887061723603
450.538362445444262
460.548908006864532
470.564179566483495
480.573759531511236
490.585148543291279
500.628108600071935
510.633509189531422
520.644138787495886
530.644923299212842
540.673509650614968
550.695776369027681
560.715443696266066
570.716001828074995
580.721051337547454
590.724787350710935
600.730063562629699
610.73673717754249
620.75368380908956
630.772916554357583
640.775071392633332
650.873092265907511
660.886363330434203
670.940566966659705
680.995905875796707
691.008391265311
701.09015950845540
711.09453155489816
721.09928186535188
731.35320601012463
741.42748572135745
751.45524622907264
761.47493802397988
771.72013257992850
781.76694564256923
792.01948477008426
802.09570234424673
812.14879248267555
822.20072244086909
832.29188455772522
842.4166566454479
853.21006186247776
863.28522092522229
874.8757868374048
886.02906225853992
8911.5094528787633
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/05/t1225885149k4zzxsy23tue1yu/1ako31225884811.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/05/t1225885149k4zzxsy23tue1yu/1ako31225884811.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/05/t1225885149k4zzxsy23tue1yu/2mvz11225884811.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/05/t1225885149k4zzxsy23tue1yu/2mvz11225884811.ps (open in new window)


 
Parameters (Session):
par1 = mcquitty ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
Parameters (R input):
par1 = mcquitty ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
R code (references can be found in the software module):
par3 <- as.logical(par3)
par4 <- as.logical(par4)
if (par3 == 'TRUE'){
dum = xlab
xlab = ylab
ylab = dum
}
x <- t(y)
hc <- hclust(dist(x),method=par1)
d <- as.dendrogram(hc)
str(d)
mysub <- paste('Method: ',par1)
bitmap(file='test1.png')
if (par4 == 'TRUE'){
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
if (par2 != 'ALL'){
if (par3 == 'TRUE'){
ylab = 'cluster'
} else {
xlab = 'cluster'
}
par2 <- as.numeric(par2)
memb <- cutree(hc, k = par2)
cent <- NULL
for(k in 1:par2){
cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE]))
}
hc1 <- hclust(dist(cent),method=par1, members = table(memb))
de <- as.dendrogram(hc1)
bitmap(file='test2.png')
if (par4 == 'TRUE'){
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub)
} else {
plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub)
}
dev.off()
str(de)
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- length(x[,1])-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,hc$labels[i])
a<-table.element(a,hc$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
if (par2 != 'ALL'){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Label',header=TRUE)
a<-table.element(a,'Height',header=TRUE)
a<-table.row.end(a)
num <- par2-1
for (i in 1:num)
{
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,hc1$height[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
 




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