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Various EDA methods 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: Sun, 09 Nov 2008 01:56:48 -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/09/t12262210920d6lpoik4k83rcy.htm/, Retrieved Sun, 09 Nov 2008 08:58:15 +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/09/t12262210920d6lpoik4k83rcy.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:
reeks 1; reeks 2;reeks 3;reeks 4
 
Dataseries X:
» Textbox « » Textfile « » CSV «
569 117,8 77,9 85,7 580 113,5 60 61,9 578 121,2 99,5 104,9 565 130,4 95 107,9 547 115,2 105,6 95,6 555 117,9 102,5 79,8 562 110,7 93,3 94,8 561 107,6 97,3 93,7 555 124,3 127 108,1 544 115,1 111,7 96,9 537 112,5 96,4 88,8 543 127,9 133 106,7 594 117,4 72,2 86,8 611 119,3 95,8 69,8 613 130,4 124,1 110,9 611 126 127,6 105,4 594 125,4 110,7 99,2 595 130,5 104,6 84,4 591 115,9 112,7 87,2 589 108,7 115,3 91,9 584 124 139,4 97,9 573 119,4 119 94,5 567 118,6 97,4 85 569 131,3 154 100,3 621 111,1 81,5 78,7 629 124,8 88,8 65,8 628 132,3 127,7 104,8 612 126,7 105,1 96 595 131,7 114,9 103,3 597 130,9 106,4 82,9 593 122,1 104,5 91,4 590 113,2 121,6 94,5 580 133,6 141,4 109,3 574 119,2 99 92,1 573 129,4 126,7 99,3 573 131,4 134,1 109,6 620 117,1 81,3 87,5 626 130,5 88,6 73,1 620 132,3 132,7 110,7 588 140,8 132,9 111,6 566 137,5 134,4 110,7 557 128,6 103,7 84 561 126,7 119,7 101,6 549 120,8 115 102,1 532 139,3 132,9 113,9 526 128,6 108,5 99 511 131,3 113,9 100,4 499 136,3 142 109,5 555 128,8 97,7 93,1 565 133,2 92,2 77 542 136,3 128,8 108 527 151,1 134,9 119,9 510 145 128,2 105,9 514 134,4 114,8 78,2 517 135,7 117,9 100,3 508 128,7 119,1 102,2 493 129,2 120,7 97 490 138,6 129,1 101,3 469 132,7 117,6 89,2 478 132,5 129,2 93,3 528 135,2 99,1 86,4
 
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 time5 seconds
R Server'George Udny Yule' @ 72.249.76.132


Summary of Dendrogram
LabelHeight
13.10644491340182
25.27446679769624
36.78527818147495
46.9217049922689
58.1154174261094
68.22800097228968
78.66833317310772
89.35467797414748
99.53362470417207
109.73755616158387
1110.1158291800524
1210.6995327000762
1311.0837719211467
1411.1176927402039
1511.1269942032878
1611.2836164415492
1711.7175082675456
1812.7935987209316
1913.5029626378806
2013.6532047519987
2113.9061137633776
2214.2912560679599
2315.244999180059
2416.0269525882465
2516.8193341128595
2617.1662459495371
2719.4935455419710
2820.0022498734517
2920.0336167449125
3021.0595438480890
3122.0762446720005
3223.7975771603291
3323.9556004851981
3424.2371643624292
3524.9908236827359
3625.0168668958763
3725.6682683482934
3825.7766400098992
3926.3351708478073
4028.1081516181605
4128.9168438491848
4231.1928358628244
4332.9363646128943
4433.6722116314038
4535.0108618388809
4636.5513987414996
4738.9268424596249
4842.7107786497974
4949.2672534002783
5050.4039449846778
5160.0205150909532
5275.5401160570481
53106.383508431499
54113.264347553177
55127.052901228084
56141.116772317358
57221.984795688692
58338.522129849007
59358.319593075369
60976.283725306065
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/09/t12262210920d6lpoik4k83rcy/1l8811226221001.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/09/t12262210920d6lpoik4k83rcy/1l8811226221001.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/09/t12262210920d6lpoik4k83rcy/2gd3m1226221001.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Nov/09/t12262210920d6lpoik4k83rcy/2gd3m1226221001.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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