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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_hierarchicalclustering.wasp
Title produced by softwareHierarchical Clustering
Date of computationThu, 13 Nov 2008 15:20:25 -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/13/t12266148438alhntmpmxvnhjj.htm/, Retrieved Sun, 19 May 2024 10:44:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24869, Retrieved Sun, 19 May 2024 10:44:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

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] [] [2008-11-13 22:20:25] [0655940460a4fd80d3d4d54548b75d49] [Current]
Feedback Forum
2008-11-19 14:50:28 [Sam De Cuyper] [reply] 
De definitie over hierarchical clustering is gegeven maar interpretatie ontbreekt. Bij hierarchical clustering begint men bovenaan vanuit het knooppunt. Van daaruit ontspringen 2 aparte takken die perioden bevatten die gelijkaardig zijn. Je zou kunnen zeggen dat de gegevens links anders zijn dan de gegevens rechts, die daarop volgen. Bij de clustering worden de gegevens telkens naar beneden toe opgesplitst tot ze helemaal onderaan de periodes allemaal apart weergeeft. We gebruiken deze methode louter als exploratief instrument.
2008-11-24 19:00:17 [Birgit Van Dyck] [reply] 
De student geeft enkel de definitie. Bij een dendrogram vertrekken er uit het knooppunt 2 takken, de gegevens worden telkens verder opgesplitst. de gegevens die zich onder eenzelfde tak bevinden zijn gelijkaardig. Deze methode is louter een exploratief element.
2008-11-24 19:36:56 [Jasmine Hendrikx] [reply] 
Evaluatie Q2:
De methode is goed uitgevoerd, maar er is geen bespreking gegeven. Het volgende zou je er nog bij kunnen vermelden:
Meestal wordt een dendrogram gebruikt in de marketing, om bijvoorbeeld te kijken welke producten men samen in 1 groep gaat zetten. Bij hierarchical clustering wordt er dus nagegaan of dat van de periodes groepen gemaakt kunnen worden die hetzelfde zijn voor de verschillende variabelen. We zien dat we de tijdreeks hier wordt opgesplitst in 2 groepen (takken) die gelijkaardig zijn. Deze worden dan nog verder onderverdeeld in kleinere groepjes die clusters genoemd worden. We kunnen hier niet echt een opvallende conclusie trekken. De volgnummers lijken willekeurig in de verschillende groepjes te zitten, ze zijn zowat overal verspreid. Zowel hoge als lage volgnummers zitten in de bepaalde groepjes. Als dit niet het geval was, als in de eerste groep bijvoorbeeld alleen de laagste nummer zaten (bijvoorbeeld tot periode 24) en in de tweede groep de hogere volgnummers (vanaf periode 25), dan zouden we kunnen concluderen dat er in maand 25 iets gebeurd moet zijn, die deze verandering teweeg heeft gebracht.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3.3	2.36	5.41
2.86	1.95	5.46
2.27	2.16	5.64
1.95	2.76	5.76
2.98	2.09	5.82
1.71	1.49	5.84
1.31	1.17	5.83
1.37	1.3	5.85
1.8	1.26	5.85
2.14	2.17	5.88
2.05	2.03	5.87
2.43	2.18	5.87
5.28	2.61	5.85
4.07	2.58	5.89
3.24	3.86	5.88
1.22	3.81	5.89
1.18	2.41	5.9
1	1.47	5.91
1.18	1.33	5.89
1.86	1.38	5.92
2.38	1.57	5.91
1.48	2.6	5.96
1.62	2.18	5.96
2.44	2.36	5.99
3.91	2.24	5.92
3.83	2.41	5.96
2.9	2.51	5.96
1.67	2.98	5.97
1.19	1.87	5.96
1.26	1.9	5.95
1.6	1.47	5.97
2.61	1.45	5.98
2.19	2.71	5.99
1.46	2.9	6.03
2.17	2.11	6.05
2.6	2.18	6.08
4.33	2.24	6.1
2.9	2.05	6.11
2.05	2.42	6.09
1.51	2.77	6.1
1.19	1.99	6.12
1.08	1.47	6.13
1.1	1.09	6.13
1.39	0.93	6.17
1.35	1.32	6.19
1.69	2.03	6.23
2.35	2.04	6.21
3.7	2.78	6.23
3.55	2.8	6.25
3.75	3.03	6.23
4.23	3.11	6.23
2.13	2.75	6.24
1.33	2.78	6.28
1.46	1.76	6.3
2.1	1.29	6.34
1.76	1.28	6.27
1.28	1.43	6.22
1.26	1.71	6.31
1.99	1.89	6.33
3.06	1.84	6.31
3.33	2.08	6.35
4.02	2.09	6.33
2.43	2.36	6.36
1.39	2.99	6.37
1.52	2.75	6.33
1.75	1.58	6.34
2.22	1.69	6.42
2.57	1.3	6.42
2.37	1.97	6.48
1.69	1.84	6.47
2.71	1.96	6.5
3.06	1.86	6.52
4.64	2.75	6.49
3.22	2.62	6.51
2.35	2.41	6.52
2.01	3.61	6.54
1.49	2.03	6.59
1.31	1.45	6.6
1.29	1.4	6.59
1.33	1.3	6.58
1.33	1.58	6.55
1.39	2.1	6.57
2.39	2.27	6.61
3.04	2.54	6.61

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24869&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24869&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24869&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Summary of Dendrogram
LabelHeight
10.0547722557505166
20.076811457478686
30.12369316876853
40.133790881602596
50.144568322948010
60.151327459504216
70.152643375224738
80.155615857075599
90.155884572681199
100.166733320005331
110.171172427686237
120.171464281994822
130.192093727122985
140.198746069143518
150.206397674405503
160.210950231097290
170.216564078277077
180.220027507143814
190.220907220343746
200.225929180737146
210.234093998214392
220.244192777443496
230.245904079478557
240.252900297914676
250.260192236625154
260.268700576850888
270.275139657420847
280.279334856818157
290.279642629082192
300.296816441593117
310.299287040028603
320.303479818109870
330.316701752442263
340.317804971641414
350.32271985003553
360.333616546352245
370.347275107083707
380.360138862107382
390.360183346655995
400.385541607703055
410.388826001396361
420.414125584816974
430.424261224035659
440.430357979240401
450.446707566957678
460.505138777179615
470.521325188166175
480.53099376991057
490.561065427687481
500.603489850784584
510.604400529450462
520.62651269641963
530.636356585975002
540.672467871668472
550.695821987958553
560.749705787810854
570.76536477615575
580.818409704475618
590.823626603383826
600.82813391390275
610.89092478058693
620.892515726876682
631.04240107444304
641.10415466868235
651.13516835177840
661.22475908917341
671.29987267647895
681.51873904684064
691.59356596819206
701.70206372699082
711.89838849836904
721.95976012340632
732.04880599979331
742.0876408931404
752.62298046404135
762.65933696139283
773.01057698770479
784.10638032289735
794.92238409302335
805.21196383486164
8110.0989974059155
8218.2546356063909
8329.8884060752202

\begin{tabular}{lllllllll}
\hline
Summary of Dendrogram \tabularnewline
Label & Height \tabularnewline
1 & 0.0547722557505166 \tabularnewline
2 & 0.076811457478686 \tabularnewline
3 & 0.12369316876853 \tabularnewline
4 & 0.133790881602596 \tabularnewline
5 & 0.144568322948010 \tabularnewline
6 & 0.151327459504216 \tabularnewline
7 & 0.152643375224738 \tabularnewline
8 & 0.155615857075599 \tabularnewline
9 & 0.155884572681199 \tabularnewline
10 & 0.166733320005331 \tabularnewline
11 & 0.171172427686237 \tabularnewline
12 & 0.171464281994822 \tabularnewline
13 & 0.192093727122985 \tabularnewline
14 & 0.198746069143518 \tabularnewline
15 & 0.206397674405503 \tabularnewline
16 & 0.210950231097290 \tabularnewline
17 & 0.216564078277077 \tabularnewline
18 & 0.220027507143814 \tabularnewline
19 & 0.220907220343746 \tabularnewline
20 & 0.225929180737146 \tabularnewline
21 & 0.234093998214392 \tabularnewline
22 & 0.244192777443496 \tabularnewline
23 & 0.245904079478557 \tabularnewline
24 & 0.252900297914676 \tabularnewline
25 & 0.260192236625154 \tabularnewline
26 & 0.268700576850888 \tabularnewline
27 & 0.275139657420847 \tabularnewline
28 & 0.279334856818157 \tabularnewline
29 & 0.279642629082192 \tabularnewline
30 & 0.296816441593117 \tabularnewline
31 & 0.299287040028603 \tabularnewline
32 & 0.303479818109870 \tabularnewline
33 & 0.316701752442263 \tabularnewline
34 & 0.317804971641414 \tabularnewline
35 & 0.32271985003553 \tabularnewline
36 & 0.333616546352245 \tabularnewline
37 & 0.347275107083707 \tabularnewline
38 & 0.360138862107382 \tabularnewline
39 & 0.360183346655995 \tabularnewline
40 & 0.385541607703055 \tabularnewline
41 & 0.388826001396361 \tabularnewline
42 & 0.414125584816974 \tabularnewline
43 & 0.424261224035659 \tabularnewline
44 & 0.430357979240401 \tabularnewline
45 & 0.446707566957678 \tabularnewline
46 & 0.505138777179615 \tabularnewline
47 & 0.521325188166175 \tabularnewline
48 & 0.53099376991057 \tabularnewline
49 & 0.561065427687481 \tabularnewline
50 & 0.603489850784584 \tabularnewline
51 & 0.604400529450462 \tabularnewline
52 & 0.62651269641963 \tabularnewline
53 & 0.636356585975002 \tabularnewline
54 & 0.672467871668472 \tabularnewline
55 & 0.695821987958553 \tabularnewline
56 & 0.749705787810854 \tabularnewline
57 & 0.76536477615575 \tabularnewline
58 & 0.818409704475618 \tabularnewline
59 & 0.823626603383826 \tabularnewline
60 & 0.82813391390275 \tabularnewline
61 & 0.89092478058693 \tabularnewline
62 & 0.892515726876682 \tabularnewline
63 & 1.04240107444304 \tabularnewline
64 & 1.10415466868235 \tabularnewline
65 & 1.13516835177840 \tabularnewline
66 & 1.22475908917341 \tabularnewline
67 & 1.29987267647895 \tabularnewline
68 & 1.51873904684064 \tabularnewline
69 & 1.59356596819206 \tabularnewline
70 & 1.70206372699082 \tabularnewline
71 & 1.89838849836904 \tabularnewline
72 & 1.95976012340632 \tabularnewline
73 & 2.04880599979331 \tabularnewline
74 & 2.0876408931404 \tabularnewline
75 & 2.62298046404135 \tabularnewline
76 & 2.65933696139283 \tabularnewline
77 & 3.01057698770479 \tabularnewline
78 & 4.10638032289735 \tabularnewline
79 & 4.92238409302335 \tabularnewline
80 & 5.21196383486164 \tabularnewline
81 & 10.0989974059155 \tabularnewline
82 & 18.2546356063909 \tabularnewline
83 & 29.8884060752202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24869&T=1

[TABLE]
[ROW][C]Summary of Dendrogram[/C][/ROW]
[ROW][C]Label[/C][C]Height[/C][/ROW]
[ROW][C]1[/C][C]0.0547722557505166[/C][/ROW]
[ROW][C]2[/C][C]0.076811457478686[/C][/ROW]
[ROW][C]3[/C][C]0.12369316876853[/C][/ROW]
[ROW][C]4[/C][C]0.133790881602596[/C][/ROW]
[ROW][C]5[/C][C]0.144568322948010[/C][/ROW]
[ROW][C]6[/C][C]0.151327459504216[/C][/ROW]
[ROW][C]7[/C][C]0.152643375224738[/C][/ROW]
[ROW][C]8[/C][C]0.155615857075599[/C][/ROW]
[ROW][C]9[/C][C]0.155884572681199[/C][/ROW]
[ROW][C]10[/C][C]0.166733320005331[/C][/ROW]
[ROW][C]11[/C][C]0.171172427686237[/C][/ROW]
[ROW][C]12[/C][C]0.171464281994822[/C][/ROW]
[ROW][C]13[/C][C]0.192093727122985[/C][/ROW]
[ROW][C]14[/C][C]0.198746069143518[/C][/ROW]
[ROW][C]15[/C][C]0.206397674405503[/C][/ROW]
[ROW][C]16[/C][C]0.210950231097290[/C][/ROW]
[ROW][C]17[/C][C]0.216564078277077[/C][/ROW]
[ROW][C]18[/C][C]0.220027507143814[/C][/ROW]
[ROW][C]19[/C][C]0.220907220343746[/C][/ROW]
[ROW][C]20[/C][C]0.225929180737146[/C][/ROW]
[ROW][C]21[/C][C]0.234093998214392[/C][/ROW]
[ROW][C]22[/C][C]0.244192777443496[/C][/ROW]
[ROW][C]23[/C][C]0.245904079478557[/C][/ROW]
[ROW][C]24[/C][C]0.252900297914676[/C][/ROW]
[ROW][C]25[/C][C]0.260192236625154[/C][/ROW]
[ROW][C]26[/C][C]0.268700576850888[/C][/ROW]
[ROW][C]27[/C][C]0.275139657420847[/C][/ROW]
[ROW][C]28[/C][C]0.279334856818157[/C][/ROW]
[ROW][C]29[/C][C]0.279642629082192[/C][/ROW]
[ROW][C]30[/C][C]0.296816441593117[/C][/ROW]
[ROW][C]31[/C][C]0.299287040028603[/C][/ROW]
[ROW][C]32[/C][C]0.303479818109870[/C][/ROW]
[ROW][C]33[/C][C]0.316701752442263[/C][/ROW]
[ROW][C]34[/C][C]0.317804971641414[/C][/ROW]
[ROW][C]35[/C][C]0.32271985003553[/C][/ROW]
[ROW][C]36[/C][C]0.333616546352245[/C][/ROW]
[ROW][C]37[/C][C]0.347275107083707[/C][/ROW]
[ROW][C]38[/C][C]0.360138862107382[/C][/ROW]
[ROW][C]39[/C][C]0.360183346655995[/C][/ROW]
[ROW][C]40[/C][C]0.385541607703055[/C][/ROW]
[ROW][C]41[/C][C]0.388826001396361[/C][/ROW]
[ROW][C]42[/C][C]0.414125584816974[/C][/ROW]
[ROW][C]43[/C][C]0.424261224035659[/C][/ROW]
[ROW][C]44[/C][C]0.430357979240401[/C][/ROW]
[ROW][C]45[/C][C]0.446707566957678[/C][/ROW]
[ROW][C]46[/C][C]0.505138777179615[/C][/ROW]
[ROW][C]47[/C][C]0.521325188166175[/C][/ROW]
[ROW][C]48[/C][C]0.53099376991057[/C][/ROW]
[ROW][C]49[/C][C]0.561065427687481[/C][/ROW]
[ROW][C]50[/C][C]0.603489850784584[/C][/ROW]
[ROW][C]51[/C][C]0.604400529450462[/C][/ROW]
[ROW][C]52[/C][C]0.62651269641963[/C][/ROW]
[ROW][C]53[/C][C]0.636356585975002[/C][/ROW]
[ROW][C]54[/C][C]0.672467871668472[/C][/ROW]
[ROW][C]55[/C][C]0.695821987958553[/C][/ROW]
[ROW][C]56[/C][C]0.749705787810854[/C][/ROW]
[ROW][C]57[/C][C]0.76536477615575[/C][/ROW]
[ROW][C]58[/C][C]0.818409704475618[/C][/ROW]
[ROW][C]59[/C][C]0.823626603383826[/C][/ROW]
[ROW][C]60[/C][C]0.82813391390275[/C][/ROW]
[ROW][C]61[/C][C]0.89092478058693[/C][/ROW]
[ROW][C]62[/C][C]0.892515726876682[/C][/ROW]
[ROW][C]63[/C][C]1.04240107444304[/C][/ROW]
[ROW][C]64[/C][C]1.10415466868235[/C][/ROW]
[ROW][C]65[/C][C]1.13516835177840[/C][/ROW]
[ROW][C]66[/C][C]1.22475908917341[/C][/ROW]
[ROW][C]67[/C][C]1.29987267647895[/C][/ROW]
[ROW][C]68[/C][C]1.51873904684064[/C][/ROW]
[ROW][C]69[/C][C]1.59356596819206[/C][/ROW]
[ROW][C]70[/C][C]1.70206372699082[/C][/ROW]
[ROW][C]71[/C][C]1.89838849836904[/C][/ROW]
[ROW][C]72[/C][C]1.95976012340632[/C][/ROW]
[ROW][C]73[/C][C]2.04880599979331[/C][/ROW]
[ROW][C]74[/C][C]2.0876408931404[/C][/ROW]
[ROW][C]75[/C][C]2.62298046404135[/C][/ROW]
[ROW][C]76[/C][C]2.65933696139283[/C][/ROW]
[ROW][C]77[/C][C]3.01057698770479[/C][/ROW]
[ROW][C]78[/C][C]4.10638032289735[/C][/ROW]
[ROW][C]79[/C][C]4.92238409302335[/C][/ROW]
[ROW][C]80[/C][C]5.21196383486164[/C][/ROW]
[ROW][C]81[/C][C]10.0989974059155[/C][/ROW]
[ROW][C]82[/C][C]18.2546356063909[/C][/ROW]
[ROW][C]83[/C][C]29.8884060752202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24869&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24869&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
10.0547722557505166
20.076811457478686
30.12369316876853
40.133790881602596
50.144568322948010
60.151327459504216
70.152643375224738
80.155615857075599
90.155884572681199
100.166733320005331
110.171172427686237
120.171464281994822
130.192093727122985
140.198746069143518
150.206397674405503
160.210950231097290
170.216564078277077
180.220027507143814
190.220907220343746
200.225929180737146
210.234093998214392
220.244192777443496
230.245904079478557
240.252900297914676
250.260192236625154
260.268700576850888
270.275139657420847
280.279334856818157
290.279642629082192
300.296816441593117
310.299287040028603
320.303479818109870
330.316701752442263
340.317804971641414
350.32271985003553
360.333616546352245
370.347275107083707
380.360138862107382
390.360183346655995
400.385541607703055
410.388826001396361
420.414125584816974
430.424261224035659
440.430357979240401
450.446707566957678
460.505138777179615
470.521325188166175
480.53099376991057
490.561065427687481
500.603489850784584
510.604400529450462
520.62651269641963
530.636356585975002
540.672467871668472
550.695821987958553
560.749705787810854
570.76536477615575
580.818409704475618
590.823626603383826
600.82813391390275
610.89092478058693
620.892515726876682
631.04240107444304
641.10415466868235
651.13516835177840
661.22475908917341
671.29987267647895
681.51873904684064
691.59356596819206
701.70206372699082
711.89838849836904
721.95976012340632
732.04880599979331
742.0876408931404
752.62298046404135
762.65933696139283
773.01057698770479
784.10638032289735
794.92238409302335
805.21196383486164
8110.0989974059155
8218.2546356063909
8329.8884060752202


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')
}