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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationThu, 01 Nov 2007 06:53:41 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/01/7vq4nawtqqr785h1193925171.htm/, Retrieved Tue, 07 May 2024 15:33:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14433, Retrieved Tue, 07 May 2024 15:33:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS4HC
Estimated Impact289
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Hierarchical Clustering] [WS4 - Hierarchica...] [2007-11-01 13:53:41] [b6d7c4d5947e155f3cf6c48d4ebc585d] [Current]
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Dataseries X:
97.3	93.5	105.5	96.5
101	94.7	106.4	97.3
113.2	112.9	117.9	122.0
101	99.2	89.7	91.0
105.7	105.6	88.5	107.9
113.9	113.0	106.4	114.6
86.4	83.1	61.4	98.0
96.5	81.1	92.3	95.5
103.3	96.9	95.5	98.7
114.9	104.3	92.5	115.9
105.8	97.7	89.6	110.4
94.2	102.6	84.3	109.5
98.4	89.9	76.3	92.3
99.4	96.0	80.7	102.1
108.8	112.7	96.3	112.8
112.6	107.1	81	110.2
104.4	106.2	82.9	98.9
112.2	121.0	90.3	119.0
81.1	101.2	74.8	104.3
97.1	83.2	70.1	98.8
112.6	105.1	86.7	109.4
113.8	113.3	86.4	170.3
107.8	99.1	89.9	118.0
103.2	100.3	88.1	116.9
103.3	93.5	78.8	111.7
101.2	98.8	81.1	116.8
107.7	106.2	85.4	116.1
110.4	98.3	82.6	114.8
101.9	102.1	80.3	110.8
115.9	117.1	81.2	122.8
89.9	101.5	68	104.7
88.6	80.5	67.4	86.0
117.2	105.9	91.3	127.2
123.9	109.5	94.9	126.1
100	97.2	82.8	114.6
103.6	114.5	88.6	127.8
94.1	93.5	73.1	105.2
98.7	100.9	76.7	113.1
119.5	121.1	93.2	161.0
112.7	116.5	84.9	126.9
104.4	109.3	83.8	117.7
124.7	118.1	93.5	144.9
89.1	108.3	91.9	119.4
97	105.4	69.6	107.1
121.6	116.2	87	142.8
118.8	111.2	90.2	126.2
114	105.8	82.7	126.9
111.5	122.7	91.4	179.2
97.2	99.5	74.6	105.3
102.5	107.9	76.1	114.8
113.4	124.6	87.1	125.4
109.8	115.0	78.4	113.2
104.9	110.3	81.3	134.4
126.1	132.7	99.3	150.0
80	99.7	71	100.9
96.8	96.5	73.2	101.8
117.2	118.7	95.6	137.7
112.3	112.9	84	138.7
117.3	130.5	90.8	135.4
111.1	137.9	93.6	153.8
102.2	115.0	80.9	119.5
104.3	116.8	84.4	123.3
122.9	140.9	97.3	166.4
107.6	120.7	83.5	137.5
121.3	134.2	88.8	142.2
131.5	147.3	100.7	167.0
89	112.4	69.4	112.3
104.4	107.1	74.6	120.6
128.9	128.4	96.6	154.9
135.9	137.7	96.6	153.4
133.3	135.0	93.1	156.2
121.3	151.0	91.8	175.8
120.5	137.4	85.7	131.7
120.4	132.4	79.1	130.1
137.9	161.3	91.3	161.1
126.1	139.8	84.2	128.2
133.2	146.0	85.8	140.3
146.6	154.6	90	168.2
103.4	142.1	76.6	110.2
117.2	120.5	81.3	126.2




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14433&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14433&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14433&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Summary of Dendrogram
LabelHeight
13.42490875790874
24.07185461430047
34.83425278610873
44.98196748283247
55.06162029393751
65.20096144957834
75.42770669804476
85.47083174663597
95.7323642591866
105.8429444631966
115.86003412959344
126.09343909463285
136.33561362458286
146.51996388168818
157.18470597867442
167.31317808087963
177.5914425506619
187.73821684886124
198.09938269252664
208.35942581760254
218.50780406844028
228.59883713068226
238.8495476786472
248.94035793466904
259.1989129792601
2610.0647700592165
2710.1498768338859
2810.1739864360043
2910.2004898382589
3010.2231087223271
3110.4347668272364
3210.7609056860358
3311.2623265802409
3411.2814006222632
3511.4608027642046
3611.9737990389705
3712.8903416743467
3813.0818322731710
3913.1407762327802
4013.1688210771077
4113.2056920815861
4213.8419651783986
4313.9519397759106
4414.0662717164144
4514.3299579684984
4614.7195098958274
4714.7927284330719
4815.2363221047147
4915.7475997770911
5017.2483110420655
5118.6854260533227
5219.0527337526540
5320.7403782816229
5421.2335085226022
5521.5138443692751
5623.9686294558721
5724.0262986291667
5824.200498182342
5925.6907921049861
6028.1760936307079
6128.3562180469680
6232.557869096833
6334.0737556766259
6434.6636483703758
6538.6131748737818
6638.7226258914067
6748.2294077439159
6853.904964478872
6956.2050076936645
7056.8333786129471
7165.4707304100143
7270.7948423759706
7383.415108412949
7483.9137771639779
75115.721435368988
76116.135537296676
77213.422176127059
78330.436876956095
79958.799363482108

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 3.42490875790874 \tabularnewline
2 & 4.07185461430047 \tabularnewline
3 & 4.83425278610873 \tabularnewline
4 & 4.98196748283247 \tabularnewline
5 & 5.06162029393751 \tabularnewline
6 & 5.20096144957834 \tabularnewline
7 & 5.42770669804476 \tabularnewline
8 & 5.47083174663597 \tabularnewline
9 & 5.7323642591866 \tabularnewline
10 & 5.8429444631966 \tabularnewline
11 & 5.86003412959344 \tabularnewline
12 & 6.09343909463285 \tabularnewline
13 & 6.33561362458286 \tabularnewline
14 & 6.51996388168818 \tabularnewline
15 & 7.18470597867442 \tabularnewline
16 & 7.31317808087963 \tabularnewline
17 & 7.5914425506619 \tabularnewline
18 & 7.73821684886124 \tabularnewline
19 & 8.09938269252664 \tabularnewline
20 & 8.35942581760254 \tabularnewline
21 & 8.50780406844028 \tabularnewline
22 & 8.59883713068226 \tabularnewline
23 & 8.8495476786472 \tabularnewline
24 & 8.94035793466904 \tabularnewline
25 & 9.1989129792601 \tabularnewline
26 & 10.0647700592165 \tabularnewline
27 & 10.1498768338859 \tabularnewline
28 & 10.1739864360043 \tabularnewline
29 & 10.2004898382589 \tabularnewline
30 & 10.2231087223271 \tabularnewline
31 & 10.4347668272364 \tabularnewline
32 & 10.7609056860358 \tabularnewline
33 & 11.2623265802409 \tabularnewline
34 & 11.2814006222632 \tabularnewline
35 & 11.4608027642046 \tabularnewline
36 & 11.9737990389705 \tabularnewline
37 & 12.8903416743467 \tabularnewline
38 & 13.0818322731710 \tabularnewline
39 & 13.1407762327802 \tabularnewline
40 & 13.1688210771077 \tabularnewline
41 & 13.2056920815861 \tabularnewline
42 & 13.8419651783986 \tabularnewline
43 & 13.9519397759106 \tabularnewline
44 & 14.0662717164144 \tabularnewline
45 & 14.3299579684984 \tabularnewline
46 & 14.7195098958274 \tabularnewline
47 & 14.7927284330719 \tabularnewline
48 & 15.2363221047147 \tabularnewline
49 & 15.7475997770911 \tabularnewline
50 & 17.2483110420655 \tabularnewline
51 & 18.6854260533227 \tabularnewline
52 & 19.0527337526540 \tabularnewline
53 & 20.7403782816229 \tabularnewline
54 & 21.2335085226022 \tabularnewline
55 & 21.5138443692751 \tabularnewline
56 & 23.9686294558721 \tabularnewline
57 & 24.0262986291667 \tabularnewline
58 & 24.200498182342 \tabularnewline
59 & 25.6907921049861 \tabularnewline
60 & 28.1760936307079 \tabularnewline
61 & 28.3562180469680 \tabularnewline
62 & 32.557869096833 \tabularnewline
63 & 34.0737556766259 \tabularnewline
64 & 34.6636483703758 \tabularnewline
65 & 38.6131748737818 \tabularnewline
66 & 38.7226258914067 \tabularnewline
67 & 48.2294077439159 \tabularnewline
68 & 53.904964478872 \tabularnewline
69 & 56.2050076936645 \tabularnewline
70 & 56.8333786129471 \tabularnewline
71 & 65.4707304100143 \tabularnewline
72 & 70.7948423759706 \tabularnewline
73 & 83.415108412949 \tabularnewline
74 & 83.9137771639779 \tabularnewline
75 & 115.721435368988 \tabularnewline
76 & 116.135537296676 \tabularnewline
77 & 213.422176127059 \tabularnewline
78 & 330.436876956095 \tabularnewline
79 & 958.799363482108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14433&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]3.42490875790874[/C][/ROW]
[ROW][C]2[/C][C]4.07185461430047[/C][/ROW]
[ROW][C]3[/C][C]4.83425278610873[/C][/ROW]
[ROW][C]4[/C][C]4.98196748283247[/C][/ROW]
[ROW][C]5[/C][C]5.06162029393751[/C][/ROW]
[ROW][C]6[/C][C]5.20096144957834[/C][/ROW]
[ROW][C]7[/C][C]5.42770669804476[/C][/ROW]
[ROW][C]8[/C][C]5.47083174663597[/C][/ROW]
[ROW][C]9[/C][C]5.7323642591866[/C][/ROW]
[ROW][C]10[/C][C]5.8429444631966[/C][/ROW]
[ROW][C]11[/C][C]5.86003412959344[/C][/ROW]
[ROW][C]12[/C][C]6.09343909463285[/C][/ROW]
[ROW][C]13[/C][C]6.33561362458286[/C][/ROW]
[ROW][C]14[/C][C]6.51996388168818[/C][/ROW]
[ROW][C]15[/C][C]7.18470597867442[/C][/ROW]
[ROW][C]16[/C][C]7.31317808087963[/C][/ROW]
[ROW][C]17[/C][C]7.5914425506619[/C][/ROW]
[ROW][C]18[/C][C]7.73821684886124[/C][/ROW]
[ROW][C]19[/C][C]8.09938269252664[/C][/ROW]
[ROW][C]20[/C][C]8.35942581760254[/C][/ROW]
[ROW][C]21[/C][C]8.50780406844028[/C][/ROW]
[ROW][C]22[/C][C]8.59883713068226[/C][/ROW]
[ROW][C]23[/C][C]8.8495476786472[/C][/ROW]
[ROW][C]24[/C][C]8.94035793466904[/C][/ROW]
[ROW][C]25[/C][C]9.1989129792601[/C][/ROW]
[ROW][C]26[/C][C]10.0647700592165[/C][/ROW]
[ROW][C]27[/C][C]10.1498768338859[/C][/ROW]
[ROW][C]28[/C][C]10.1739864360043[/C][/ROW]
[ROW][C]29[/C][C]10.2004898382589[/C][/ROW]
[ROW][C]30[/C][C]10.2231087223271[/C][/ROW]
[ROW][C]31[/C][C]10.4347668272364[/C][/ROW]
[ROW][C]32[/C][C]10.7609056860358[/C][/ROW]
[ROW][C]33[/C][C]11.2623265802409[/C][/ROW]
[ROW][C]34[/C][C]11.2814006222632[/C][/ROW]
[ROW][C]35[/C][C]11.4608027642046[/C][/ROW]
[ROW][C]36[/C][C]11.9737990389705[/C][/ROW]
[ROW][C]37[/C][C]12.8903416743467[/C][/ROW]
[ROW][C]38[/C][C]13.0818322731710[/C][/ROW]
[ROW][C]39[/C][C]13.1407762327802[/C][/ROW]
[ROW][C]40[/C][C]13.1688210771077[/C][/ROW]
[ROW][C]41[/C][C]13.2056920815861[/C][/ROW]
[ROW][C]42[/C][C]13.8419651783986[/C][/ROW]
[ROW][C]43[/C][C]13.9519397759106[/C][/ROW]
[ROW][C]44[/C][C]14.0662717164144[/C][/ROW]
[ROW][C]45[/C][C]14.3299579684984[/C][/ROW]
[ROW][C]46[/C][C]14.7195098958274[/C][/ROW]
[ROW][C]47[/C][C]14.7927284330719[/C][/ROW]
[ROW][C]48[/C][C]15.2363221047147[/C][/ROW]
[ROW][C]49[/C][C]15.7475997770911[/C][/ROW]
[ROW][C]50[/C][C]17.2483110420655[/C][/ROW]
[ROW][C]51[/C][C]18.6854260533227[/C][/ROW]
[ROW][C]52[/C][C]19.0527337526540[/C][/ROW]
[ROW][C]53[/C][C]20.7403782816229[/C][/ROW]
[ROW][C]54[/C][C]21.2335085226022[/C][/ROW]
[ROW][C]55[/C][C]21.5138443692751[/C][/ROW]
[ROW][C]56[/C][C]23.9686294558721[/C][/ROW]
[ROW][C]57[/C][C]24.0262986291667[/C][/ROW]
[ROW][C]58[/C][C]24.200498182342[/C][/ROW]
[ROW][C]59[/C][C]25.6907921049861[/C][/ROW]
[ROW][C]60[/C][C]28.1760936307079[/C][/ROW]
[ROW][C]61[/C][C]28.3562180469680[/C][/ROW]
[ROW][C]62[/C][C]32.557869096833[/C][/ROW]
[ROW][C]63[/C][C]34.0737556766259[/C][/ROW]
[ROW][C]64[/C][C]34.6636483703758[/C][/ROW]
[ROW][C]65[/C][C]38.6131748737818[/C][/ROW]
[ROW][C]66[/C][C]38.7226258914067[/C][/ROW]
[ROW][C]67[/C][C]48.2294077439159[/C][/ROW]
[ROW][C]68[/C][C]53.904964478872[/C][/ROW]
[ROW][C]69[/C][C]56.2050076936645[/C][/ROW]
[ROW][C]70[/C][C]56.8333786129471[/C][/ROW]
[ROW][C]71[/C][C]65.4707304100143[/C][/ROW]
[ROW][C]72[/C][C]70.7948423759706[/C][/ROW]
[ROW][C]73[/C][C]83.415108412949[/C][/ROW]
[ROW][C]74[/C][C]83.9137771639779[/C][/ROW]
[ROW][C]75[/C][C]115.721435368988[/C][/ROW]
[ROW][C]76[/C][C]116.135537296676[/C][/ROW]
[ROW][C]77[/C][C]213.422176127059[/C][/ROW]
[ROW][C]78[/C][C]330.436876956095[/C][/ROW]
[ROW][C]79[/C][C]958.799363482108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14433&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14433&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of Dendrogram
LabelHeight
13.42490875790874
24.07185461430047
34.83425278610873
44.98196748283247
55.06162029393751
65.20096144957834
75.42770669804476
85.47083174663597
95.7323642591866
105.8429444631966
115.86003412959344
126.09343909463285
136.33561362458286
146.51996388168818
157.18470597867442
167.31317808087963
177.5914425506619
187.73821684886124
198.09938269252664
208.35942581760254
218.50780406844028
228.59883713068226
238.8495476786472
248.94035793466904
259.1989129792601
2610.0647700592165
2710.1498768338859
2810.1739864360043
2910.2004898382589
3010.2231087223271
3110.4347668272364
3210.7609056860358
3311.2623265802409
3411.2814006222632
3511.4608027642046
3611.9737990389705
3712.8903416743467
3813.0818322731710
3913.1407762327802
4013.1688210771077
4113.2056920815861
4213.8419651783986
4313.9519397759106
4414.0662717164144
4514.3299579684984
4614.7195098958274
4714.7927284330719
4815.2363221047147
4915.7475997770911
5017.2483110420655
5118.6854260533227
5219.0527337526540
5320.7403782816229
5421.2335085226022
5521.5138443692751
5623.9686294558721
5724.0262986291667
5824.200498182342
5925.6907921049861
6028.1760936307079
6128.3562180469680
6232.557869096833
6334.0737556766259
6434.6636483703758
6538.6131748737818
6638.7226258914067
6748.2294077439159
6853.904964478872
6956.2050076936645
7056.8333786129471
7165.4707304100143
7270.7948423759706
7383.415108412949
7483.9137771639779
75115.721435368988
76116.135537296676
77213.422176127059
78330.436876956095
79958.799363482108



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
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')
}