FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationTue, 11 Nov 2008 09:12:17 -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/2008/Nov/11/t1226420069nj3mn0zrmpcllko.htm/, Retrieved Sun, 19 May 2024 09:10:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23646, Retrieved Sun, 19 May 2024 09:10:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Hierarchical Clustering] [Hierarchical Clus...] [2008-11-11 16:12:17] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]
F RMPD    [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-11-11 16:22:43] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-11-11 16:29:02] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Box-Cox Normality Plot] [Box-Cox Normality...] [2008-11-11 16:33:57] [fce9014b1ad8484790f3b34d6ba09f7b]
F RMPD    [Maximum-likelihood Fitting - Normal Distribution] [Maximum-likelihoo...] [2008-11-11 16:44:01] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Harrell-Davis Quantiles] [Harrell-Davis Qua...] [2008-11-11 17:20:45] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Mean with known Variance - Critical Value] [Testing Mean with...] [2008-11-11 17:30:24] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Mean with known Variance - p-value] [Testing Mean with...] [2008-11-11 17:39:03] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Mean with known Variance - Type II Error] [Testing Mean with...] [2008-11-11 17:43:14] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Mean with known Variance - Sample Size] [Testing Mean with...] [2008-11-11 17:46:06] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Population Mean with known Variance - Confidence Interval] [Testing Mean with...] [2008-11-11 17:48:57] [fce9014b1ad8484790f3b34d6ba09f7b]
- RMPD    [Testing Sample Mean with known Variance - Confidence Interval] [Testing Sample Me...] [2008-11-11 17:51:17] [fce9014b1ad8484790f3b34d6ba09f7b]
Feedback Forum
2008-11-24 20:03:05 [Dries Van Gheluwe] [reply] 
Het dendogram stelt een boom voor met verschillende takken waar je gegevens onder geclasseerd worden. Dit wordt vooral gebruikt voor niet-tijdreeksen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2173	2752	572	582
2363	2373	582	552
2126	1415	574	436
1905	2466	461	602
2121	2318	576	640
1983	2346	460	551
1734	1644	455	421
2074	1421	444	382
2049	1423	488	382
2406	1930	513	427
2558	2694	468	542
2251	4938	488	708
2059	1727	536	465
2397	1899	486	474
1747	1364	460	371
1707	1992	376	463
2319	2051	503	515
1631	2082	369	509
1627	1746	353	380
1791	1271	359	313
2034	1363	400	313
1997	1664	374	359
2169	2179	430	427
2028	2305	433	415
2253	2098	418	402
2218	2231	438	388
1855	1407	389	353
2187	1966	368	464
1852	2293	386	429
1570	2045	261	398
1851	1532	294	291
1954	1333	263	272
1828	1583	293	241
2251	1712	303	288
2277	2641	326	365
2085	2267	314	312
2282	2126	332	325
2266	2231	347	346
1878	1517	290	282
2267	2010	340	362
2069	2628	371	369
1746	2115	340	340
2299	1829	376	308
2360	1636	322	294
2214	1787	364	306
2825	2122	379	328
2355	2620	343	351
2333	2555	358	366
3016	2337	433	350
2155	2524	344	356
2172	1801	357	295
2150	2417	385	359
2533	2389	392	380
2058	2267	308	360
2160	2135	294	336
2259	1760	300	299
2498	1905	302	262
2695	2176	400	299
2799	2344	392	313
2945	2673	373	357
2930	2766	379	356
2318	2785	303	368
2540	2003	324	284
2570	2588	353	338
2669	2739	392	352
2450	2703	327	342
2842	2464	376	315
3439	1974	329	277
2677	2164	359	317
2979	2385	413	291
2257	2936	338	326
2842	2700	421	353
2546	2855	390	371
2455	2764	370	356
2293	1808	366	274
2379	2588	405	352
2478	2600	418	347
2054	2526	346	345
2272	2259	349	336
2351	1738	326	276
2271	1902	318	312
2542	2137	379	330
2304	2460	336	325
2194	2495	372	328
2722	2525	420	332
2395	2465	425	341
2146	1828	422	316
1894	2273	396	377
2548	2377	457	380
2087	2344	313	373
2063	2071	334	346
2481	1611	384	272
2476	1671	342	283
2212	2256	385	302
2834	1983	435	301
2148	1921	405	303
2598	2027	454	320

Tables (Output of Computation)





Summary of computational 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 computational 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=23646&T=0

[TABLE]
[ROW][C]Summary of computational 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=23646&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23646&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational 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
130.3973683071413
232.4191301548947
341.6293165929973
446.1519230368573
549.7292670366254
649.9799959983992
750.6458290484024
855.3985559378582
962.6897120746299
1063.08724118235
1167.7790528113222
1270.4840407468244
1371.8261790714221
1474.2293742395825
1575.184724644052
1676.0986202240225
1781.7924201867141
1886.913750350563
1994.3980932010811
2095.4515583948214
2197.2308587241395
22100.850001501952
23102.674110511567
24104.043260233424
25108.765803449430
26111.067547015319
27113.639781766774
28119.363501590225
29121.095004025765
30122.270192606375
31123.308556069723
32124.968066493446
33126.653069445632
34128.386136323203
35128.487353463288
36128.902948993368
37137.397234324422
38140.301389399715
39144.779142144164
40151.429851746609
41152.535241829552
42160.886901063743
43163.405753937546
44170.146995271736
45171.787659626645
46174.573654396415
47180.599566325888
48184.222691327643
49185.321868328806
50203.161633296266
51209.171689618688
52210.127384181347
53212.222375235778
54212.821521468107
55219.652223727361
56227.187663726935
57235.572929253534
58239.496256243073
59242.469361391211
60251.620091586140
61257.488796002958
62258.362205450719
63263.379953679091
64266.538896689265
65275.527313926972
66328.818726995389
67343.995228451656
68344.214835353125
69390.811205663008
70400.785725534446
71456.004818755424
72460.090701392321
73463.874198909259
74505.222440962843
75539.102939441339
76564.126410825905
77615.769316128549
78627.68445157788
79713.90438738075
80762.221259548995
81789.159816363466
82814.109603036147
83891.596814623578
84901.324329387116
85953.609707005061
861012.12756920841
871049.18845133695
881213.17718744536
892239.5031153197
902574.80538434628
912746.79247330567
924164.06032441671
935218.79829262991
945670.35141122717
958058.11811292189
9616076.4706102691

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 30.3973683071413 \tabularnewline
2 & 32.4191301548947 \tabularnewline
3 & 41.6293165929973 \tabularnewline
4 & 46.1519230368573 \tabularnewline
5 & 49.7292670366254 \tabularnewline
6 & 49.9799959983992 \tabularnewline
7 & 50.6458290484024 \tabularnewline
8 & 55.3985559378582 \tabularnewline
9 & 62.6897120746299 \tabularnewline
10 & 63.08724118235 \tabularnewline
11 & 67.7790528113222 \tabularnewline
12 & 70.4840407468244 \tabularnewline
13 & 71.8261790714221 \tabularnewline
14 & 74.2293742395825 \tabularnewline
15 & 75.184724644052 \tabularnewline
16 & 76.0986202240225 \tabularnewline
17 & 81.7924201867141 \tabularnewline
18 & 86.913750350563 \tabularnewline
19 & 94.3980932010811 \tabularnewline
20 & 95.4515583948214 \tabularnewline
21 & 97.2308587241395 \tabularnewline
22 & 100.850001501952 \tabularnewline
23 & 102.674110511567 \tabularnewline
24 & 104.043260233424 \tabularnewline
25 & 108.765803449430 \tabularnewline
26 & 111.067547015319 \tabularnewline
27 & 113.639781766774 \tabularnewline
28 & 119.363501590225 \tabularnewline
29 & 121.095004025765 \tabularnewline
30 & 122.270192606375 \tabularnewline
31 & 123.308556069723 \tabularnewline
32 & 124.968066493446 \tabularnewline
33 & 126.653069445632 \tabularnewline
34 & 128.386136323203 \tabularnewline
35 & 128.487353463288 \tabularnewline
36 & 128.902948993368 \tabularnewline
37 & 137.397234324422 \tabularnewline
38 & 140.301389399715 \tabularnewline
39 & 144.779142144164 \tabularnewline
40 & 151.429851746609 \tabularnewline
41 & 152.535241829552 \tabularnewline
42 & 160.886901063743 \tabularnewline
43 & 163.405753937546 \tabularnewline
44 & 170.146995271736 \tabularnewline
45 & 171.787659626645 \tabularnewline
46 & 174.573654396415 \tabularnewline
47 & 180.599566325888 \tabularnewline
48 & 184.222691327643 \tabularnewline
49 & 185.321868328806 \tabularnewline
50 & 203.161633296266 \tabularnewline
51 & 209.171689618688 \tabularnewline
52 & 210.127384181347 \tabularnewline
53 & 212.222375235778 \tabularnewline
54 & 212.821521468107 \tabularnewline
55 & 219.652223727361 \tabularnewline
56 & 227.187663726935 \tabularnewline
57 & 235.572929253534 \tabularnewline
58 & 239.496256243073 \tabularnewline
59 & 242.469361391211 \tabularnewline
60 & 251.620091586140 \tabularnewline
61 & 257.488796002958 \tabularnewline
62 & 258.362205450719 \tabularnewline
63 & 263.379953679091 \tabularnewline
64 & 266.538896689265 \tabularnewline
65 & 275.527313926972 \tabularnewline
66 & 328.818726995389 \tabularnewline
67 & 343.995228451656 \tabularnewline
68 & 344.214835353125 \tabularnewline
69 & 390.811205663008 \tabularnewline
70 & 400.785725534446 \tabularnewline
71 & 456.004818755424 \tabularnewline
72 & 460.090701392321 \tabularnewline
73 & 463.874198909259 \tabularnewline
74 & 505.222440962843 \tabularnewline
75 & 539.102939441339 \tabularnewline
76 & 564.126410825905 \tabularnewline
77 & 615.769316128549 \tabularnewline
78 & 627.68445157788 \tabularnewline
79 & 713.90438738075 \tabularnewline
80 & 762.221259548995 \tabularnewline
81 & 789.159816363466 \tabularnewline
82 & 814.109603036147 \tabularnewline
83 & 891.596814623578 \tabularnewline
84 & 901.324329387116 \tabularnewline
85 & 953.609707005061 \tabularnewline
86 & 1012.12756920841 \tabularnewline
87 & 1049.18845133695 \tabularnewline
88 & 1213.17718744536 \tabularnewline
89 & 2239.5031153197 \tabularnewline
90 & 2574.80538434628 \tabularnewline
91 & 2746.79247330567 \tabularnewline
92 & 4164.06032441671 \tabularnewline
93 & 5218.79829262991 \tabularnewline
94 & 5670.35141122717 \tabularnewline
95 & 8058.11811292189 \tabularnewline
96 & 16076.4706102691 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23646&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]30.3973683071413[/C][/ROW]
[ROW][C]2[/C][C]32.4191301548947[/C][/ROW]
[ROW][C]3[/C][C]41.6293165929973[/C][/ROW]
[ROW][C]4[/C][C]46.1519230368573[/C][/ROW]
[ROW][C]5[/C][C]49.7292670366254[/C][/ROW]
[ROW][C]6[/C][C]49.9799959983992[/C][/ROW]
[ROW][C]7[/C][C]50.6458290484024[/C][/ROW]
[ROW][C]8[/C][C]55.3985559378582[/C][/ROW]
[ROW][C]9[/C][C]62.6897120746299[/C][/ROW]
[ROW][C]10[/C][C]63.08724118235[/C][/ROW]
[ROW][C]11[/C][C]67.7790528113222[/C][/ROW]
[ROW][C]12[/C][C]70.4840407468244[/C][/ROW]
[ROW][C]13[/C][C]71.8261790714221[/C][/ROW]
[ROW][C]14[/C][C]74.2293742395825[/C][/ROW]
[ROW][C]15[/C][C]75.184724644052[/C][/ROW]
[ROW][C]16[/C][C]76.0986202240225[/C][/ROW]
[ROW][C]17[/C][C]81.7924201867141[/C][/ROW]
[ROW][C]18[/C][C]86.913750350563[/C][/ROW]
[ROW][C]19[/C][C]94.3980932010811[/C][/ROW]
[ROW][C]20[/C][C]95.4515583948214[/C][/ROW]
[ROW][C]21[/C][C]97.2308587241395[/C][/ROW]
[ROW][C]22[/C][C]100.850001501952[/C][/ROW]
[ROW][C]23[/C][C]102.674110511567[/C][/ROW]
[ROW][C]24[/C][C]104.043260233424[/C][/ROW]
[ROW][C]25[/C][C]108.765803449430[/C][/ROW]
[ROW][C]26[/C][C]111.067547015319[/C][/ROW]
[ROW][C]27[/C][C]113.639781766774[/C][/ROW]
[ROW][C]28[/C][C]119.363501590225[/C][/ROW]
[ROW][C]29[/C][C]121.095004025765[/C][/ROW]
[ROW][C]30[/C][C]122.270192606375[/C][/ROW]
[ROW][C]31[/C][C]123.308556069723[/C][/ROW]
[ROW][C]32[/C][C]124.968066493446[/C][/ROW]
[ROW][C]33[/C][C]126.653069445632[/C][/ROW]
[ROW][C]34[/C][C]128.386136323203[/C][/ROW]
[ROW][C]35[/C][C]128.487353463288[/C][/ROW]
[ROW][C]36[/C][C]128.902948993368[/C][/ROW]
[ROW][C]37[/C][C]137.397234324422[/C][/ROW]
[ROW][C]38[/C][C]140.301389399715[/C][/ROW]
[ROW][C]39[/C][C]144.779142144164[/C][/ROW]
[ROW][C]40[/C][C]151.429851746609[/C][/ROW]
[ROW][C]41[/C][C]152.535241829552[/C][/ROW]
[ROW][C]42[/C][C]160.886901063743[/C][/ROW]
[ROW][C]43[/C][C]163.405753937546[/C][/ROW]
[ROW][C]44[/C][C]170.146995271736[/C][/ROW]
[ROW][C]45[/C][C]171.787659626645[/C][/ROW]
[ROW][C]46[/C][C]174.573654396415[/C][/ROW]
[ROW][C]47[/C][C]180.599566325888[/C][/ROW]
[ROW][C]48[/C][C]184.222691327643[/C][/ROW]
[ROW][C]49[/C][C]185.321868328806[/C][/ROW]
[ROW][C]50[/C][C]203.161633296266[/C][/ROW]
[ROW][C]51[/C][C]209.171689618688[/C][/ROW]
[ROW][C]52[/C][C]210.127384181347[/C][/ROW]
[ROW][C]53[/C][C]212.222375235778[/C][/ROW]
[ROW][C]54[/C][C]212.821521468107[/C][/ROW]
[ROW][C]55[/C][C]219.652223727361[/C][/ROW]
[ROW][C]56[/C][C]227.187663726935[/C][/ROW]
[ROW][C]57[/C][C]235.572929253534[/C][/ROW]
[ROW][C]58[/C][C]239.496256243073[/C][/ROW]
[ROW][C]59[/C][C]242.469361391211[/C][/ROW]
[ROW][C]60[/C][C]251.620091586140[/C][/ROW]
[ROW][C]61[/C][C]257.488796002958[/C][/ROW]
[ROW][C]62[/C][C]258.362205450719[/C][/ROW]
[ROW][C]63[/C][C]263.379953679091[/C][/ROW]
[ROW][C]64[/C][C]266.538896689265[/C][/ROW]
[ROW][C]65[/C][C]275.527313926972[/C][/ROW]
[ROW][C]66[/C][C]328.818726995389[/C][/ROW]
[ROW][C]67[/C][C]343.995228451656[/C][/ROW]
[ROW][C]68[/C][C]344.214835353125[/C][/ROW]
[ROW][C]69[/C][C]390.811205663008[/C][/ROW]
[ROW][C]70[/C][C]400.785725534446[/C][/ROW]
[ROW][C]71[/C][C]456.004818755424[/C][/ROW]
[ROW][C]72[/C][C]460.090701392321[/C][/ROW]
[ROW][C]73[/C][C]463.874198909259[/C][/ROW]
[ROW][C]74[/C][C]505.222440962843[/C][/ROW]
[ROW][C]75[/C][C]539.102939441339[/C][/ROW]
[ROW][C]76[/C][C]564.126410825905[/C][/ROW]
[ROW][C]77[/C][C]615.769316128549[/C][/ROW]
[ROW][C]78[/C][C]627.68445157788[/C][/ROW]
[ROW][C]79[/C][C]713.90438738075[/C][/ROW]
[ROW][C]80[/C][C]762.221259548995[/C][/ROW]
[ROW][C]81[/C][C]789.159816363466[/C][/ROW]
[ROW][C]82[/C][C]814.109603036147[/C][/ROW]
[ROW][C]83[/C][C]891.596814623578[/C][/ROW]
[ROW][C]84[/C][C]901.324329387116[/C][/ROW]
[ROW][C]85[/C][C]953.609707005061[/C][/ROW]
[ROW][C]86[/C][C]1012.12756920841[/C][/ROW]
[ROW][C]87[/C][C]1049.18845133695[/C][/ROW]
[ROW][C]88[/C][C]1213.17718744536[/C][/ROW]
[ROW][C]89[/C][C]2239.5031153197[/C][/ROW]
[ROW][C]90[/C][C]2574.80538434628[/C][/ROW]
[ROW][C]91[/C][C]2746.79247330567[/C][/ROW]
[ROW][C]92[/C][C]4164.06032441671[/C][/ROW]
[ROW][C]93[/C][C]5218.79829262991[/C][/ROW]
[ROW][C]94[/C][C]5670.35141122717[/C][/ROW]
[ROW][C]95[/C][C]8058.11811292189[/C][/ROW]
[ROW][C]96[/C][C]16076.4706102691[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23646&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23646&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Summary of Dendrogram
LabelHeight
130.3973683071413
232.4191301548947
341.6293165929973
446.1519230368573
549.7292670366254
649.9799959983992
750.6458290484024
855.3985559378582
962.6897120746299
1063.08724118235
1167.7790528113222
1270.4840407468244
1371.8261790714221
1474.2293742395825
1575.184724644052
1676.0986202240225
1781.7924201867141
1886.913750350563
1994.3980932010811
2095.4515583948214
2197.2308587241395
22100.850001501952
23102.674110511567
24104.043260233424
25108.765803449430
26111.067547015319
27113.639781766774
28119.363501590225
29121.095004025765
30122.270192606375
31123.308556069723
32124.968066493446
33126.653069445632
34128.386136323203
35128.487353463288
36128.902948993368
37137.397234324422
38140.301389399715
39144.779142144164
40151.429851746609
41152.535241829552
42160.886901063743
43163.405753937546
44170.146995271736
45171.787659626645
46174.573654396415
47180.599566325888
48184.222691327643
49185.321868328806
50203.161633296266
51209.171689618688
52210.127384181347
53212.222375235778
54212.821521468107
55219.652223727361
56227.187663726935
57235.572929253534
58239.496256243073
59242.469361391211
60251.620091586140
61257.488796002958
62258.362205450719
63263.379953679091
64266.538896689265
65275.527313926972
66328.818726995389
67343.995228451656
68344.214835353125
69390.811205663008
70400.785725534446
71456.004818755424
72460.090701392321
73463.874198909259
74505.222440962843
75539.102939441339
76564.126410825905
77615.769316128549
78627.68445157788
79713.90438738075
80762.221259548995
81789.159816363466
82814.109603036147
83891.596814623578
84901.324329387116
85953.609707005061
861012.12756920841
871049.18845133695
881213.17718744536
892239.5031153197
902574.80538434628
912746.79247330567
924164.06032441671
935218.79829262991
945670.35141122717
958058.11811292189
9616076.4706102691


Figures (Output of Computation)

Input Parameters & R Code

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')
}