FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationWed, 12 Nov 2008 11:44:29 -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/12/t1226515515mk4h5p6umogvac4.htm/, Retrieved Tue, 28 May 2024 10:14:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24374, Retrieved Tue, 28 May 2024 10:14:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSeverijns Britt
Estimated Impact159

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Variuos EDA topic...] [2008-11-09 13:17:45] [3548296885df7a66ea8efc200c4aca50]
F RMPD    [Hierarchical Clustering] [various EDA topic...] [2008-11-12 18:44:29] [78308c9f3efc33d1da821bcd963df161] [Current]
Feedback Forum
2008-11-23 16:00:26 [Aurélie Van Impe] [reply] 
Een dendogram poogt de gegevens in te delen in categorieën met gelijkaardige gegevens. In dit geval zijn er teveel gegevens om ze duidelijk te kunnen aflezen uit de grafiek, maar bij een reeks met minder gegevens zou je bijvoorbeeld kunnen vaststellen dat in de lage maanden meer of minder werkloosheid is dan in de hogere maanden.
2008-11-23 16:14:16 [Alexander Hendrickx] [reply] 
2008-11-23 16:14:28 [Alexander Hendrickx] [reply] 
De dendogram groepeert gegevens in clusters en verdeelt ze dan nog verder tot je uiteindelijk bij 1 gegeven terechtkomt. Zo kunnen groepen visueel onderscheiden worden. Hier zijn er echter zoveel gegevens dat een volledige analyse haast niet mogelijk is.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
116222	344744	31899	492865
110924	338653	31384	480961
103753	327532	30650	461935
99983	326225	30400	456608
93302	318672	30003	441977
91496	317756	29896	439148
119321	337302	31557	488180
139261	349420	31883	520564
133739	336923	30830	501492
123913	330758	30354	485025
113438	321002	29756	464196
109416	320820	29934	460170
109406	327032	30599	467037
105645	324047	30378	460070
101328	316735	29925	447988
97686	315710	29471	442867
93093	313427	29567	436087
91382	310527	29419	431328
122257	330962	30796	484015
139183	339015	31475	509673
139887	341332	31708	512927
131822	339092	31917	502831
116805	323308	30871	470984
113706	325849	31512	471067
113012	330675	32362	476049
110452	332225	31928	474605
107005	331735	31699	470439
102841	328047	30363	461251
98173	326165	30386	454724
98181	327081	30364	455626
137277	346764	32806	516847
147579	344190	33423	525192
146571	343333	33071	522975
138920	345777	33888	518585
130340	344094	34805	509239
128140	348609	35489	512238
127059	354846	37259	519164
122860	356427	37722	517009
117702	353467	38764	509933
113537	355996	39594	509127
108366	352487	40004	500857
111078	355178	40715	506971
150739	374556	44028	569323
159129	375021	45564	579714
157928	375787	44277	577992
147768	372720	44976	565464
137507	364431	45406	547344
136919	370490	47379	554788
136151	376974	49200	562325
133001	377632	50221	560854
125554	378205	51573	555332
119647	370861	53091	543599
114158	369167	53337	536662
116193	371551	54978	542722
152803	382842	57885	593530
161761	381903	67099	610763
160942	384502	67169	612613
149470	392058	69796	611324
139208	384359	70600	594167
134588	388884	71982	595454
130322	386586	73957	590865
126611	387495	75273	589379
122401	385705	76322	584428
117352	378670	77078	573100
112135	377367	77954	567456
112879	376911	79238	569028
148729	389827	82179	620735
157230	387820	83834	628884
157221	387267	83744	628232
146681	380575	84861	612117
136524	372402	86478	595404
132111	376740	88290	597141
125326	377795	90287	593408
122716	376126	91230	590072
116615	370804	92380	579799
113719	367980	92506	574205
110737	367866	94172	572775
112093	366121	94728	572942
143565	379421	96581	619567
149946	378519	97344	625809
149147	372423	98346	619916
134339	355072	98214	587625
122683	344693	98366	565742
115614	342892	98768	557274
116566	344178	99832	560576
111272	337606	99976	548854
104609	327103	99961	531673
101802	323953	100164	525919
94542	316532	99964	511038
93051	306307	99304	498662
124129	327225	104008	555362
130374	329573	104644	564591
123946	313761	103950	541657
114971	307836	104263	527070
105531	300074	104241	509846
104919	304198	105141	514258
104782	306122	106018	516922
101281	300414	105866	507561
94545	292133	105944	492622
93248	290616	106379	490243
84031	280244	105082	469357
87486	285179	104915	477580
115867	305486	107026	528379
120327	305957	107306	533590

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 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=24374&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]4 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=24374&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24374&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Summary of Dendrogram
LabelHeight
1859.705763619158
21283.43055908764
31285.7713638124
41999.85399467061
52209.36914072773
62284.90393671156
72578.9164391271
82605.66805253470
92796.18581036811
102804.45823645138
113135.66005810579
123294.38340209515
133351.05834028595
143369.56080224115
153403.9051103108
163480.71573099557
173552.57399641443
183682.62759453084
193820.39264997722
203958.90969838919
214059.34132588035
224062.86967548800
234077.70767702555
244090.97958929154
254305.56082293585
264649.2801593365
274984.08527214373
284998.95549090007
295102.93542973062
305290.39903977006
315520.67775877584
325831.59549351633
335889.57400836427
346377.03802717218
356383.22379366414
366677.82344780094
376736.93684102798
387138.03012041838
397292.01078397943
408369.31371530829
418575.02594748261
428932.89488005599
439231.5165182407
449321.18552885975
459330.23868933695
469377.26049019384
479816.47034325475
4810122.2868800018
4910194.9432563404
5011360.9040022629
5111405.7908976099
5211619.8738973113
5311624.7402046557
5412656.0127402690
5513086.5142799754
5613259.6443672086
5713364.5073669244
5813593.0808194382
5913679.9833942010
6015187.8868941546
6116136.1297094440
6218899.8160827252
6319006.0738217819
6419561.7663011172
6519639.3343489589
6620247.4861403751
6720428.7684774631
6820558.7116148443
6920650.7693847215
7020796.8202410109
7122224.9802067932
7225507.3634836792
7325520.3147569515
7425863.2256402882
7527149.8947250659
7628439.7236861846
7731863.346132451
7831972.4989600627
7933812.2232875745
8035823.1023129956
8136502.2418324199
8239178.6091678858
8350248.0370926284
8451970.3960943451
8552635.4887545891
8654266.1439152676
8759764.2131589394
8865954.3192554011
8973133.8195993697
9079848.4850096052
9198010.8836697785
92109912.576661638
93113039.824259602
94126918.217342389
95135616.498796359
96190527.347222519
97236237.710670613
98296052.669107166
99439379.675976635
100516394.295088344
101798427.304006475
1021330765.13198652
1033205469.01139512

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 859.705763619158 \tabularnewline
2 & 1283.43055908764 \tabularnewline
3 & 1285.7713638124 \tabularnewline
4 & 1999.85399467061 \tabularnewline
5 & 2209.36914072773 \tabularnewline
6 & 2284.90393671156 \tabularnewline
7 & 2578.9164391271 \tabularnewline
8 & 2605.66805253470 \tabularnewline
9 & 2796.18581036811 \tabularnewline
10 & 2804.45823645138 \tabularnewline
11 & 3135.66005810579 \tabularnewline
12 & 3294.38340209515 \tabularnewline
13 & 3351.05834028595 \tabularnewline
14 & 3369.56080224115 \tabularnewline
15 & 3403.9051103108 \tabularnewline
16 & 3480.71573099557 \tabularnewline
17 & 3552.57399641443 \tabularnewline
18 & 3682.62759453084 \tabularnewline
19 & 3820.39264997722 \tabularnewline
20 & 3958.90969838919 \tabularnewline
21 & 4059.34132588035 \tabularnewline
22 & 4062.86967548800 \tabularnewline
23 & 4077.70767702555 \tabularnewline
24 & 4090.97958929154 \tabularnewline
25 & 4305.56082293585 \tabularnewline
26 & 4649.2801593365 \tabularnewline
27 & 4984.08527214373 \tabularnewline
28 & 4998.95549090007 \tabularnewline
29 & 5102.93542973062 \tabularnewline
30 & 5290.39903977006 \tabularnewline
31 & 5520.67775877584 \tabularnewline
32 & 5831.59549351633 \tabularnewline
33 & 5889.57400836427 \tabularnewline
34 & 6377.03802717218 \tabularnewline
35 & 6383.22379366414 \tabularnewline
36 & 6677.82344780094 \tabularnewline
37 & 6736.93684102798 \tabularnewline
38 & 7138.03012041838 \tabularnewline
39 & 7292.01078397943 \tabularnewline
40 & 8369.31371530829 \tabularnewline
41 & 8575.02594748261 \tabularnewline
42 & 8932.89488005599 \tabularnewline
43 & 9231.5165182407 \tabularnewline
44 & 9321.18552885975 \tabularnewline
45 & 9330.23868933695 \tabularnewline
46 & 9377.26049019384 \tabularnewline
47 & 9816.47034325475 \tabularnewline
48 & 10122.2868800018 \tabularnewline
49 & 10194.9432563404 \tabularnewline
50 & 11360.9040022629 \tabularnewline
51 & 11405.7908976099 \tabularnewline
52 & 11619.8738973113 \tabularnewline
53 & 11624.7402046557 \tabularnewline
54 & 12656.0127402690 \tabularnewline
55 & 13086.5142799754 \tabularnewline
56 & 13259.6443672086 \tabularnewline
57 & 13364.5073669244 \tabularnewline
58 & 13593.0808194382 \tabularnewline
59 & 13679.9833942010 \tabularnewline
60 & 15187.8868941546 \tabularnewline
61 & 16136.1297094440 \tabularnewline
62 & 18899.8160827252 \tabularnewline
63 & 19006.0738217819 \tabularnewline
64 & 19561.7663011172 \tabularnewline
65 & 19639.3343489589 \tabularnewline
66 & 20247.4861403751 \tabularnewline
67 & 20428.7684774631 \tabularnewline
68 & 20558.7116148443 \tabularnewline
69 & 20650.7693847215 \tabularnewline
70 & 20796.8202410109 \tabularnewline
71 & 22224.9802067932 \tabularnewline
72 & 25507.3634836792 \tabularnewline
73 & 25520.3147569515 \tabularnewline
74 & 25863.2256402882 \tabularnewline
75 & 27149.8947250659 \tabularnewline
76 & 28439.7236861846 \tabularnewline
77 & 31863.346132451 \tabularnewline
78 & 31972.4989600627 \tabularnewline
79 & 33812.2232875745 \tabularnewline
80 & 35823.1023129956 \tabularnewline
81 & 36502.2418324199 \tabularnewline
82 & 39178.6091678858 \tabularnewline
83 & 50248.0370926284 \tabularnewline
84 & 51970.3960943451 \tabularnewline
85 & 52635.4887545891 \tabularnewline
86 & 54266.1439152676 \tabularnewline
87 & 59764.2131589394 \tabularnewline
88 & 65954.3192554011 \tabularnewline
89 & 73133.8195993697 \tabularnewline
90 & 79848.4850096052 \tabularnewline
91 & 98010.8836697785 \tabularnewline
92 & 109912.576661638 \tabularnewline
93 & 113039.824259602 \tabularnewline
94 & 126918.217342389 \tabularnewline
95 & 135616.498796359 \tabularnewline
96 & 190527.347222519 \tabularnewline
97 & 236237.710670613 \tabularnewline
98 & 296052.669107166 \tabularnewline
99 & 439379.675976635 \tabularnewline
100 & 516394.295088344 \tabularnewline
101 & 798427.304006475 \tabularnewline
102 & 1330765.13198652 \tabularnewline
103 & 3205469.01139512 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24374&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]859.705763619158[/C][/ROW]
[ROW][C]2[/C][C]1283.43055908764[/C][/ROW]
[ROW][C]3[/C][C]1285.7713638124[/C][/ROW]
[ROW][C]4[/C][C]1999.85399467061[/C][/ROW]
[ROW][C]5[/C][C]2209.36914072773[/C][/ROW]
[ROW][C]6[/C][C]2284.90393671156[/C][/ROW]
[ROW][C]7[/C][C]2578.9164391271[/C][/ROW]
[ROW][C]8[/C][C]2605.66805253470[/C][/ROW]
[ROW][C]9[/C][C]2796.18581036811[/C][/ROW]
[ROW][C]10[/C][C]2804.45823645138[/C][/ROW]
[ROW][C]11[/C][C]3135.66005810579[/C][/ROW]
[ROW][C]12[/C][C]3294.38340209515[/C][/ROW]
[ROW][C]13[/C][C]3351.05834028595[/C][/ROW]
[ROW][C]14[/C][C]3369.56080224115[/C][/ROW]
[ROW][C]15[/C][C]3403.9051103108[/C][/ROW]
[ROW][C]16[/C][C]3480.71573099557[/C][/ROW]
[ROW][C]17[/C][C]3552.57399641443[/C][/ROW]
[ROW][C]18[/C][C]3682.62759453084[/C][/ROW]
[ROW][C]19[/C][C]3820.39264997722[/C][/ROW]
[ROW][C]20[/C][C]3958.90969838919[/C][/ROW]
[ROW][C]21[/C][C]4059.34132588035[/C][/ROW]
[ROW][C]22[/C][C]4062.86967548800[/C][/ROW]
[ROW][C]23[/C][C]4077.70767702555[/C][/ROW]
[ROW][C]24[/C][C]4090.97958929154[/C][/ROW]
[ROW][C]25[/C][C]4305.56082293585[/C][/ROW]
[ROW][C]26[/C][C]4649.2801593365[/C][/ROW]
[ROW][C]27[/C][C]4984.08527214373[/C][/ROW]
[ROW][C]28[/C][C]4998.95549090007[/C][/ROW]
[ROW][C]29[/C][C]5102.93542973062[/C][/ROW]
[ROW][C]30[/C][C]5290.39903977006[/C][/ROW]
[ROW][C]31[/C][C]5520.67775877584[/C][/ROW]
[ROW][C]32[/C][C]5831.59549351633[/C][/ROW]
[ROW][C]33[/C][C]5889.57400836427[/C][/ROW]
[ROW][C]34[/C][C]6377.03802717218[/C][/ROW]
[ROW][C]35[/C][C]6383.22379366414[/C][/ROW]
[ROW][C]36[/C][C]6677.82344780094[/C][/ROW]
[ROW][C]37[/C][C]6736.93684102798[/C][/ROW]
[ROW][C]38[/C][C]7138.03012041838[/C][/ROW]
[ROW][C]39[/C][C]7292.01078397943[/C][/ROW]
[ROW][C]40[/C][C]8369.31371530829[/C][/ROW]
[ROW][C]41[/C][C]8575.02594748261[/C][/ROW]
[ROW][C]42[/C][C]8932.89488005599[/C][/ROW]
[ROW][C]43[/C][C]9231.5165182407[/C][/ROW]
[ROW][C]44[/C][C]9321.18552885975[/C][/ROW]
[ROW][C]45[/C][C]9330.23868933695[/C][/ROW]
[ROW][C]46[/C][C]9377.26049019384[/C][/ROW]
[ROW][C]47[/C][C]9816.47034325475[/C][/ROW]
[ROW][C]48[/C][C]10122.2868800018[/C][/ROW]
[ROW][C]49[/C][C]10194.9432563404[/C][/ROW]
[ROW][C]50[/C][C]11360.9040022629[/C][/ROW]
[ROW][C]51[/C][C]11405.7908976099[/C][/ROW]
[ROW][C]52[/C][C]11619.8738973113[/C][/ROW]
[ROW][C]53[/C][C]11624.7402046557[/C][/ROW]
[ROW][C]54[/C][C]12656.0127402690[/C][/ROW]
[ROW][C]55[/C][C]13086.5142799754[/C][/ROW]
[ROW][C]56[/C][C]13259.6443672086[/C][/ROW]
[ROW][C]57[/C][C]13364.5073669244[/C][/ROW]
[ROW][C]58[/C][C]13593.0808194382[/C][/ROW]
[ROW][C]59[/C][C]13679.9833942010[/C][/ROW]
[ROW][C]60[/C][C]15187.8868941546[/C][/ROW]
[ROW][C]61[/C][C]16136.1297094440[/C][/ROW]
[ROW][C]62[/C][C]18899.8160827252[/C][/ROW]
[ROW][C]63[/C][C]19006.0738217819[/C][/ROW]
[ROW][C]64[/C][C]19561.7663011172[/C][/ROW]
[ROW][C]65[/C][C]19639.3343489589[/C][/ROW]
[ROW][C]66[/C][C]20247.4861403751[/C][/ROW]
[ROW][C]67[/C][C]20428.7684774631[/C][/ROW]
[ROW][C]68[/C][C]20558.7116148443[/C][/ROW]
[ROW][C]69[/C][C]20650.7693847215[/C][/ROW]
[ROW][C]70[/C][C]20796.8202410109[/C][/ROW]
[ROW][C]71[/C][C]22224.9802067932[/C][/ROW]
[ROW][C]72[/C][C]25507.3634836792[/C][/ROW]
[ROW][C]73[/C][C]25520.3147569515[/C][/ROW]
[ROW][C]74[/C][C]25863.2256402882[/C][/ROW]
[ROW][C]75[/C][C]27149.8947250659[/C][/ROW]
[ROW][C]76[/C][C]28439.7236861846[/C][/ROW]
[ROW][C]77[/C][C]31863.346132451[/C][/ROW]
[ROW][C]78[/C][C]31972.4989600627[/C][/ROW]
[ROW][C]79[/C][C]33812.2232875745[/C][/ROW]
[ROW][C]80[/C][C]35823.1023129956[/C][/ROW]
[ROW][C]81[/C][C]36502.2418324199[/C][/ROW]
[ROW][C]82[/C][C]39178.6091678858[/C][/ROW]
[ROW][C]83[/C][C]50248.0370926284[/C][/ROW]
[ROW][C]84[/C][C]51970.3960943451[/C][/ROW]
[ROW][C]85[/C][C]52635.4887545891[/C][/ROW]
[ROW][C]86[/C][C]54266.1439152676[/C][/ROW]
[ROW][C]87[/C][C]59764.2131589394[/C][/ROW]
[ROW][C]88[/C][C]65954.3192554011[/C][/ROW]
[ROW][C]89[/C][C]73133.8195993697[/C][/ROW]
[ROW][C]90[/C][C]79848.4850096052[/C][/ROW]
[ROW][C]91[/C][C]98010.8836697785[/C][/ROW]
[ROW][C]92[/C][C]109912.576661638[/C][/ROW]
[ROW][C]93[/C][C]113039.824259602[/C][/ROW]
[ROW][C]94[/C][C]126918.217342389[/C][/ROW]
[ROW][C]95[/C][C]135616.498796359[/C][/ROW]
[ROW][C]96[/C][C]190527.347222519[/C][/ROW]
[ROW][C]97[/C][C]236237.710670613[/C][/ROW]
[ROW][C]98[/C][C]296052.669107166[/C][/ROW]
[ROW][C]99[/C][C]439379.675976635[/C][/ROW]
[ROW][C]100[/C][C]516394.295088344[/C][/ROW]
[ROW][C]101[/C][C]798427.304006475[/C][/ROW]
[ROW][C]102[/C][C]1330765.13198652[/C][/ROW]
[ROW][C]103[/C][C]3205469.01139512[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24374&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24374&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
1859.705763619158
21283.43055908764
31285.7713638124
41999.85399467061
52209.36914072773
62284.90393671156
72578.9164391271
82605.66805253470
92796.18581036811
102804.45823645138
113135.66005810579
123294.38340209515
133351.05834028595
143369.56080224115
153403.9051103108
163480.71573099557
173552.57399641443
183682.62759453084
193820.39264997722
203958.90969838919
214059.34132588035
224062.86967548800
234077.70767702555
244090.97958929154
254305.56082293585
264649.2801593365
274984.08527214373
284998.95549090007
295102.93542973062
305290.39903977006
315520.67775877584
325831.59549351633
335889.57400836427
346377.03802717218
356383.22379366414
366677.82344780094
376736.93684102798
387138.03012041838
397292.01078397943
408369.31371530829
418575.02594748261
428932.89488005599
439231.5165182407
449321.18552885975
459330.23868933695
469377.26049019384
479816.47034325475
4810122.2868800018
4910194.9432563404
5011360.9040022629
5111405.7908976099
5211619.8738973113
5311624.7402046557
5412656.0127402690
5513086.5142799754
5613259.6443672086
5713364.5073669244
5813593.0808194382
5913679.9833942010
6015187.8868941546
6116136.1297094440
6218899.8160827252
6319006.0738217819
6419561.7663011172
6519639.3343489589
6620247.4861403751
6720428.7684774631
6820558.7116148443
6920650.7693847215
7020796.8202410109
7122224.9802067932
7225507.3634836792
7325520.3147569515
7425863.2256402882
7527149.8947250659
7628439.7236861846
7731863.346132451
7831972.4989600627
7933812.2232875745
8035823.1023129956
8136502.2418324199
8239178.6091678858
8350248.0370926284
8451970.3960943451
8552635.4887545891
8654266.1439152676
8759764.2131589394
8865954.3192554011
8973133.8195993697
9079848.4850096052
9198010.8836697785
92109912.576661638
93113039.824259602
94126918.217342389
95135616.498796359
96190527.347222519
97236237.710670613
98296052.669107166
99439379.675976635
100516394.295088344
101798427.304006475
1021330765.13198652
1033205469.01139512


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')
}