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Hierarchical Clustering tijdsreeksen q2

*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: Tue, 11 Nov 2008 09:30:28 -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/11/t1226421101mvzxf2bqf3167b4.htm/, Retrieved Tue, 11 Nov 2008 16:31:44 +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/11/t1226421101mvzxf2bqf3167b4.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)
 
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Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
Hierarchical Clustering
 
Dataseries X:
» Textbox « » Textfile « » CSV «
8,4 9,5 308.347 577.992 8,4 9,1 298.427 565.464 8,4 9 289.231 547.344 8,6 9,3 291.975 554.788 8,9 9,9 294.912 562.325 8,8 9,8 293.488 560.854 8,3 9,4 290.555 555.332 7,5 8,3 284.736 543.599 7,2 8 281.818 536.662 7,5 8,5 287.854 542.722 8,8 10,4 316.263 593.530 9,3 11,1 325.412 610.763 9,3 10,9 326.011 612.613 8,7 9,9 328.282 611.324 8,2 9,2 317.480 594.167 8,3 9,2 317.539 595.454 8,5 9,5 313.737 590.865 8,6 9,6 312.276 589.379 8,6 9,5 309.391 584.428 8,2 9,1 302.950 573.100 8,1 8,9 300.316 567.456 8 9 304.035 569.028 8,6 10,1 333.476 620.735 8,7 10,3 337.698 628.884 8,8 10,2 335.932 628.232 8,5 9,6 323.931 612.117 8,4 9,2 313.927 595.404 8,5 9,3 314.485 597.141 8,7 9,4 313.218 593.408 8,7 9,4 309.664 590.072 8,6 9,2 302.963 579.799 8,5 9 298.989 574.205 8,3 9 298.423 572.775 8,1 9 301.631 572.942 8,2 9,8 329.765 619.567 8,1 10 335.083 625.809 8,1 9,9 327.616 619.916 7,9 9,3 309.119 587.625 7,9 9 295.916 565.742 7,9 9 291.413 557.274 8 9,1 291.542 560.576 8 9,1 284.678 548.854 7,9 9,1 276.475 531.673 8 9,2 272.566 525.919 7,7 8,8 264.981 511.038 7,2 8,3 263.290 498.662 7,5 8,4 296.806 555.362 7,3 8,1 303.598 564.591 7 7,8 286.994 541.657 7 7,9 276.427 527.070 7 7,9 266.424 509.846 7,2 8 267.153 514.258 7,3 7,9 268.381 516.922 7,1 7,5 262.522 507.561 6,8 7,2 255.542 492.622 6,6 6,9 253.158 490.243 6,2 6,6 243.803 469.357 6,2 6,7 250.741 477.580 6,8 7,3 280.445 528.379 6,9 7,5 285.257 533.590
 
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
11.29222676028621
21.33593600146117
31.55088877744349
41.55316966233571
51.61673281651601
61.82989972402858
71.88781884724142
81.95481482498986
92.05222245382901
102.08871180395956
112.18174288127635
122.19160055667085
132.5772863636003
142.61568339243502
152.63340729853928
162.72044100029725
172.85319675768697
182.93681460088985
193.38719603802321
203.45479385131652
213.46124120648219
223.66521719846921
233.87778167789672
244.04006744993204
254.05531167938672
264.2729152811634
274.64800010757317
284.72199915764921
294.8145517963773
305.08384650399694
315.29178813184784
325.51886035045593
335.69058037461906
345.84867063255192
355.97626845483139
367.04281336963637
377.48312842426753
387.53979886076419
397.55313507758917
409.4313920357062
419.91879335635114
4210.7593481679886
4312.0043454160770
4413.4173434017129
4514.3073993344678
4615.2541527779190
4718.9258946342214
4822.5521823534554
4927.8395741863787
5028.6914816467646
5141.4771040401003
5249.5203132157515
5361.7851059414658
5487.958556496179
55100.181866062849
56256.515768468808
57303.209194116262
58665.369439378979
591247.20771985409
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226421101mvzxf2bqf3167b4/1rxuf1226421026.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226421101mvzxf2bqf3167b4/1rxuf1226421026.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226421101mvzxf2bqf3167b4/29z981226421027.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/11/t1226421101mvzxf2bqf3167b4/29z981226421027.ps (open in new window)


 
Parameters (Session):
par1 = ward ; par2 = ALL ; par3 = FALSE ; par4 = FALSE ;
 
Parameters (R input):
par1 = ward ; 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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