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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSat, 24 May 2008 11:46:28 -0600
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/May/24/t1211653590asqrfk3b23rwil3.htm/, Retrieved Tue, 14 May 2024 18:21:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13098, Retrieved Tue, 14 May 2024 18:21:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Decompositiemodel...] [2008-05-24 17:46:28] [bd1a672bbeeae91e7f15e9efb6f60992] [Current]
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Dataseries X:
47,87
47,87
47,89
47,88
47,91
47,92
47,92
47,91
47,93
48,05
48,03
48,04
48,04
48,06
48,04
48,09
48,12
48,16
48,16
48,16
48,08
48,13
48,16
48,15
48,15
48,15
48,27
48,47
48,51
48,53
48,53
48,53
48,68
48,64
48,67
48,66
48,66
48,67
48,71
48,96
49,01
49,04
49,04
49,04
49,06
49,13
49,19
49,26
49,26
49,26
49,29
49,43
49,43
49,45
49,45
49,46
49,57
49,68
49,71
49,7
49,7
49,8
49,84
50,09
50,2
50,16
50,16
50,29
50,36
51,02
51,03
51,04




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13098&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13098&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13098&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
147.87NANA0.999087284126528NA
247.87NANA0.998584259244463NA
347.89NANA0.99877707837678NA
447.88NANA1.00136176424665NA
547.91NANA1.00127310977741NA
647.92NANA1.00112572505239NA
747.9247.96211872552947.94208333333331.000417908251010.99912183350844
847.9147.944857974620847.95708333333330.9997450771009660.999272956974046
947.9347.971543483372347.971251.000006117901290.999133997358524
1048.0547.994049971909847.986251.000162545977441.00116577009281
1148.0348.006697103443248.003751.000061393192061.00048540928585
1248.0447.99357781322248.02250.9993977367530231.00096725830607
1348.0447.998650847648748.04250.9990872841265281.00086146488747
1448.0647.994872036711748.06291666666670.9985842592444631.00135697753790
1548.0448.020785771239648.07958333333330.998777078376781.00040012316441
1648.0948.154652774484448.08916666666661.001361764246650.998657392987813
1748.1248.159150594647948.09791666666671.001273109777410.999187058032285
1848.1648.162072953676548.10791666666671.001125725052390.999956958794557
1948.1648.137191859472948.11708333333331.000417908251011.00047381535245
2048.1648.113148395932848.12541666666670.9997450771009661.00097377963466
2148.0848.139044508120848.138751.000006117901290.998773459076222
2248.1348.171995558214948.16416666666671.000162545977440.999128216347936
2348.1648.199208921632748.196251.000061393192060.999186523544475
2448.1548.198870764980148.22791666666670.9993977367530230.998986059959405
2548.1548.214703472841148.258750.9990872841265280.998658013672582
2648.1548.221217802140448.28958333333330.9985842592444630.998523102373054
2748.2748.270896197949848.330.998777078376780.999981433989829
2848.4748.442127047636948.376251.001361764246651.00057538663271
2948.5148.480392384034848.418751.001273109777411.00061071320815
3048.5348.515804043195148.461251.001125725052391.00029260479312
3148.5348.5240201173348.503751.000417908251011.00012323551626
3248.5348.534291009661648.54666666666670.9997450771009660.999911588083965
3348.6848.586963915097448.58666666666671.000006117901291.00191483635539
3448.6448.63332053254748.62541666666671.000162545977441.00013734343820
3548.6748.669654468680148.66666666666671.000061393192061.00000709952277
3648.6648.679414510068848.708750.9993977367530230.99960117617962
3748.6648.706753960273448.751250.9990872841265280.999040092872714
3848.6748.724670699509548.793750.9985842592444630.998877966772795
3948.7148.771117051370248.83083333333330.998777078376780.998746859718104
4048.9648.933628780254748.86708333333331.001361764246651.00053891813059
4149.0148.971433404954848.90916666666671.001273109777411.00078753249320
4249.0449.010944141377248.95583333333331.001125725052391.00059284429492
4349.0449.02631327543149.00583333333331.000417908251011.00027917099318
4449.0449.042911317636749.05541666666670.9997450771009660.999940637340679
4549.0649.104467081111349.10416666666671.000006117901290.99909443918742
4649.1349.155905462820249.14791666666671.000162545977440.999472993883923
4749.1949.188019624151349.1851.000061393192061.00004026134542
4849.2649.189940187260149.21958333333330.9993977367530231.00142427115124
4949.2649.20879532054749.253750.9990872841265281.00104055949997
5049.2649.218553831060849.28833333333330.9985842592444631.00084208424899
5149.2949.266760176514649.32708333333330.998777078376781.00047171406039
5249.4349.438482003062349.371251.001361764246650.99982843318163
5349.4349.478745113908749.41583333333331.001273109777410.999014827199104
5449.4549.511507003903449.45583333333331.001125725052390.998757723050148
5549.4549.513183324113249.49251.000417908251010.998723909070851
5649.4649.520706152401249.53333333333330.9997450771009660.99877412587344
5749.5749.579053317898649.578751.000006117901290.99981739631371
5849.6849.637233688071949.62916666666671.000162545977441.00086157726268
5949.7149.691800550971849.688751.000061393192061.00036624652008
6049.749.720453819186549.75041666666670.9993977367530230.999588623642477
6149.749.76412133597449.80958333333330.9990872841265280.998711494662167
6249.849.803141699493549.873750.9985842592444630.999936917644423
6349.8449.880175765484449.941250.998777078376780.999194554452389
6450.0950.098129065259850.031.001361764246650.999837737148842
6550.250.204668118497350.14083333333331.001273109777410.999907018238099
6650.1650.308236226757650.25166666666671.001125725052390.997053440194376
6750.16NANA1.00041790825101NA
6850.29NANA0.999745077100966NA
6950.36NANA1.00000611790129NA
7051.02NANA1.00016254597744NA
7151.03NANA1.00006139319206NA
7251.04NANA0.999397736753023NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 47.87 & NA & NA & 0.999087284126528 & NA \tabularnewline
2 & 47.87 & NA & NA & 0.998584259244463 & NA \tabularnewline
3 & 47.89 & NA & NA & 0.99877707837678 & NA \tabularnewline
4 & 47.88 & NA & NA & 1.00136176424665 & NA \tabularnewline
5 & 47.91 & NA & NA & 1.00127310977741 & NA \tabularnewline
6 & 47.92 & NA & NA & 1.00112572505239 & NA \tabularnewline
7 & 47.92 & 47.962118725529 & 47.9420833333333 & 1.00041790825101 & 0.99912183350844 \tabularnewline
8 & 47.91 & 47.9448579746208 & 47.9570833333333 & 0.999745077100966 & 0.999272956974046 \tabularnewline
9 & 47.93 & 47.9715434833723 & 47.97125 & 1.00000611790129 & 0.999133997358524 \tabularnewline
10 & 48.05 & 47.9940499719098 & 47.98625 & 1.00016254597744 & 1.00116577009281 \tabularnewline
11 & 48.03 & 48.0066971034432 & 48.00375 & 1.00006139319206 & 1.00048540928585 \tabularnewline
12 & 48.04 & 47.993577813222 & 48.0225 & 0.999397736753023 & 1.00096725830607 \tabularnewline
13 & 48.04 & 47.9986508476487 & 48.0425 & 0.999087284126528 & 1.00086146488747 \tabularnewline
14 & 48.06 & 47.9948720367117 & 48.0629166666667 & 0.998584259244463 & 1.00135697753790 \tabularnewline
15 & 48.04 & 48.0207857712396 & 48.0795833333333 & 0.99877707837678 & 1.00040012316441 \tabularnewline
16 & 48.09 & 48.1546527744844 & 48.0891666666666 & 1.00136176424665 & 0.998657392987813 \tabularnewline
17 & 48.12 & 48.1591505946479 & 48.0979166666667 & 1.00127310977741 & 0.999187058032285 \tabularnewline
18 & 48.16 & 48.1620729536765 & 48.1079166666667 & 1.00112572505239 & 0.999956958794557 \tabularnewline
19 & 48.16 & 48.1371918594729 & 48.1170833333333 & 1.00041790825101 & 1.00047381535245 \tabularnewline
20 & 48.16 & 48.1131483959328 & 48.1254166666667 & 0.999745077100966 & 1.00097377963466 \tabularnewline
21 & 48.08 & 48.1390445081208 & 48.13875 & 1.00000611790129 & 0.998773459076222 \tabularnewline
22 & 48.13 & 48.1719955582149 & 48.1641666666667 & 1.00016254597744 & 0.999128216347936 \tabularnewline
23 & 48.16 & 48.1992089216327 & 48.19625 & 1.00006139319206 & 0.999186523544475 \tabularnewline
24 & 48.15 & 48.1988707649801 & 48.2279166666667 & 0.999397736753023 & 0.998986059959405 \tabularnewline
25 & 48.15 & 48.2147034728411 & 48.25875 & 0.999087284126528 & 0.998658013672582 \tabularnewline
26 & 48.15 & 48.2212178021404 & 48.2895833333333 & 0.998584259244463 & 0.998523102373054 \tabularnewline
27 & 48.27 & 48.2708961979498 & 48.33 & 0.99877707837678 & 0.999981433989829 \tabularnewline
28 & 48.47 & 48.4421270476369 & 48.37625 & 1.00136176424665 & 1.00057538663271 \tabularnewline
29 & 48.51 & 48.4803923840348 & 48.41875 & 1.00127310977741 & 1.00061071320815 \tabularnewline
30 & 48.53 & 48.5158040431951 & 48.46125 & 1.00112572505239 & 1.00029260479312 \tabularnewline
31 & 48.53 & 48.52402011733 & 48.50375 & 1.00041790825101 & 1.00012323551626 \tabularnewline
32 & 48.53 & 48.5342910096616 & 48.5466666666667 & 0.999745077100966 & 0.999911588083965 \tabularnewline
33 & 48.68 & 48.5869639150974 & 48.5866666666667 & 1.00000611790129 & 1.00191483635539 \tabularnewline
34 & 48.64 & 48.633320532547 & 48.6254166666667 & 1.00016254597744 & 1.00013734343820 \tabularnewline
35 & 48.67 & 48.6696544686801 & 48.6666666666667 & 1.00006139319206 & 1.00000709952277 \tabularnewline
36 & 48.66 & 48.6794145100688 & 48.70875 & 0.999397736753023 & 0.99960117617962 \tabularnewline
37 & 48.66 & 48.7067539602734 & 48.75125 & 0.999087284126528 & 0.999040092872714 \tabularnewline
38 & 48.67 & 48.7246706995095 & 48.79375 & 0.998584259244463 & 0.998877966772795 \tabularnewline
39 & 48.71 & 48.7711170513702 & 48.8308333333333 & 0.99877707837678 & 0.998746859718104 \tabularnewline
40 & 48.96 & 48.9336287802547 & 48.8670833333333 & 1.00136176424665 & 1.00053891813059 \tabularnewline
41 & 49.01 & 48.9714334049548 & 48.9091666666667 & 1.00127310977741 & 1.00078753249320 \tabularnewline
42 & 49.04 & 49.0109441413772 & 48.9558333333333 & 1.00112572505239 & 1.00059284429492 \tabularnewline
43 & 49.04 & 49.026313275431 & 49.0058333333333 & 1.00041790825101 & 1.00027917099318 \tabularnewline
44 & 49.04 & 49.0429113176367 & 49.0554166666667 & 0.999745077100966 & 0.999940637340679 \tabularnewline
45 & 49.06 & 49.1044670811113 & 49.1041666666667 & 1.00000611790129 & 0.99909443918742 \tabularnewline
46 & 49.13 & 49.1559054628202 & 49.1479166666667 & 1.00016254597744 & 0.999472993883923 \tabularnewline
47 & 49.19 & 49.1880196241513 & 49.185 & 1.00006139319206 & 1.00004026134542 \tabularnewline
48 & 49.26 & 49.1899401872601 & 49.2195833333333 & 0.999397736753023 & 1.00142427115124 \tabularnewline
49 & 49.26 & 49.208795320547 & 49.25375 & 0.999087284126528 & 1.00104055949997 \tabularnewline
50 & 49.26 & 49.2185538310608 & 49.2883333333333 & 0.998584259244463 & 1.00084208424899 \tabularnewline
51 & 49.29 & 49.2667601765146 & 49.3270833333333 & 0.99877707837678 & 1.00047171406039 \tabularnewline
52 & 49.43 & 49.4384820030623 & 49.37125 & 1.00136176424665 & 0.99982843318163 \tabularnewline
53 & 49.43 & 49.4787451139087 & 49.4158333333333 & 1.00127310977741 & 0.999014827199104 \tabularnewline
54 & 49.45 & 49.5115070039034 & 49.4558333333333 & 1.00112572505239 & 0.998757723050148 \tabularnewline
55 & 49.45 & 49.5131833241132 & 49.4925 & 1.00041790825101 & 0.998723909070851 \tabularnewline
56 & 49.46 & 49.5207061524012 & 49.5333333333333 & 0.999745077100966 & 0.99877412587344 \tabularnewline
57 & 49.57 & 49.5790533178986 & 49.57875 & 1.00000611790129 & 0.99981739631371 \tabularnewline
58 & 49.68 & 49.6372336880719 & 49.6291666666667 & 1.00016254597744 & 1.00086157726268 \tabularnewline
59 & 49.71 & 49.6918005509718 & 49.68875 & 1.00006139319206 & 1.00036624652008 \tabularnewline
60 & 49.7 & 49.7204538191865 & 49.7504166666667 & 0.999397736753023 & 0.999588623642477 \tabularnewline
61 & 49.7 & 49.764121335974 & 49.8095833333333 & 0.999087284126528 & 0.998711494662167 \tabularnewline
62 & 49.8 & 49.8031416994935 & 49.87375 & 0.998584259244463 & 0.999936917644423 \tabularnewline
63 & 49.84 & 49.8801757654844 & 49.94125 & 0.99877707837678 & 0.999194554452389 \tabularnewline
64 & 50.09 & 50.0981290652598 & 50.03 & 1.00136176424665 & 0.999837737148842 \tabularnewline
65 & 50.2 & 50.2046681184973 & 50.1408333333333 & 1.00127310977741 & 0.999907018238099 \tabularnewline
66 & 50.16 & 50.3082362267576 & 50.2516666666667 & 1.00112572505239 & 0.997053440194376 \tabularnewline
67 & 50.16 & NA & NA & 1.00041790825101 & NA \tabularnewline
68 & 50.29 & NA & NA & 0.999745077100966 & NA \tabularnewline
69 & 50.36 & NA & NA & 1.00000611790129 & NA \tabularnewline
70 & 51.02 & NA & NA & 1.00016254597744 & NA \tabularnewline
71 & 51.03 & NA & NA & 1.00006139319206 & NA \tabularnewline
72 & 51.04 & NA & NA & 0.999397736753023 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13098&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]47.87[/C][C]NA[/C][C]NA[/C][C]0.999087284126528[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]47.87[/C][C]NA[/C][C]NA[/C][C]0.998584259244463[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]47.89[/C][C]NA[/C][C]NA[/C][C]0.99877707837678[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]47.88[/C][C]NA[/C][C]NA[/C][C]1.00136176424665[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]47.91[/C][C]NA[/C][C]NA[/C][C]1.00127310977741[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]47.92[/C][C]NA[/C][C]NA[/C][C]1.00112572505239[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]47.92[/C][C]47.962118725529[/C][C]47.9420833333333[/C][C]1.00041790825101[/C][C]0.99912183350844[/C][/ROW]
[ROW][C]8[/C][C]47.91[/C][C]47.9448579746208[/C][C]47.9570833333333[/C][C]0.999745077100966[/C][C]0.999272956974046[/C][/ROW]
[ROW][C]9[/C][C]47.93[/C][C]47.9715434833723[/C][C]47.97125[/C][C]1.00000611790129[/C][C]0.999133997358524[/C][/ROW]
[ROW][C]10[/C][C]48.05[/C][C]47.9940499719098[/C][C]47.98625[/C][C]1.00016254597744[/C][C]1.00116577009281[/C][/ROW]
[ROW][C]11[/C][C]48.03[/C][C]48.0066971034432[/C][C]48.00375[/C][C]1.00006139319206[/C][C]1.00048540928585[/C][/ROW]
[ROW][C]12[/C][C]48.04[/C][C]47.993577813222[/C][C]48.0225[/C][C]0.999397736753023[/C][C]1.00096725830607[/C][/ROW]
[ROW][C]13[/C][C]48.04[/C][C]47.9986508476487[/C][C]48.0425[/C][C]0.999087284126528[/C][C]1.00086146488747[/C][/ROW]
[ROW][C]14[/C][C]48.06[/C][C]47.9948720367117[/C][C]48.0629166666667[/C][C]0.998584259244463[/C][C]1.00135697753790[/C][/ROW]
[ROW][C]15[/C][C]48.04[/C][C]48.0207857712396[/C][C]48.0795833333333[/C][C]0.99877707837678[/C][C]1.00040012316441[/C][/ROW]
[ROW][C]16[/C][C]48.09[/C][C]48.1546527744844[/C][C]48.0891666666666[/C][C]1.00136176424665[/C][C]0.998657392987813[/C][/ROW]
[ROW][C]17[/C][C]48.12[/C][C]48.1591505946479[/C][C]48.0979166666667[/C][C]1.00127310977741[/C][C]0.999187058032285[/C][/ROW]
[ROW][C]18[/C][C]48.16[/C][C]48.1620729536765[/C][C]48.1079166666667[/C][C]1.00112572505239[/C][C]0.999956958794557[/C][/ROW]
[ROW][C]19[/C][C]48.16[/C][C]48.1371918594729[/C][C]48.1170833333333[/C][C]1.00041790825101[/C][C]1.00047381535245[/C][/ROW]
[ROW][C]20[/C][C]48.16[/C][C]48.1131483959328[/C][C]48.1254166666667[/C][C]0.999745077100966[/C][C]1.00097377963466[/C][/ROW]
[ROW][C]21[/C][C]48.08[/C][C]48.1390445081208[/C][C]48.13875[/C][C]1.00000611790129[/C][C]0.998773459076222[/C][/ROW]
[ROW][C]22[/C][C]48.13[/C][C]48.1719955582149[/C][C]48.1641666666667[/C][C]1.00016254597744[/C][C]0.999128216347936[/C][/ROW]
[ROW][C]23[/C][C]48.16[/C][C]48.1992089216327[/C][C]48.19625[/C][C]1.00006139319206[/C][C]0.999186523544475[/C][/ROW]
[ROW][C]24[/C][C]48.15[/C][C]48.1988707649801[/C][C]48.2279166666667[/C][C]0.999397736753023[/C][C]0.998986059959405[/C][/ROW]
[ROW][C]25[/C][C]48.15[/C][C]48.2147034728411[/C][C]48.25875[/C][C]0.999087284126528[/C][C]0.998658013672582[/C][/ROW]
[ROW][C]26[/C][C]48.15[/C][C]48.2212178021404[/C][C]48.2895833333333[/C][C]0.998584259244463[/C][C]0.998523102373054[/C][/ROW]
[ROW][C]27[/C][C]48.27[/C][C]48.2708961979498[/C][C]48.33[/C][C]0.99877707837678[/C][C]0.999981433989829[/C][/ROW]
[ROW][C]28[/C][C]48.47[/C][C]48.4421270476369[/C][C]48.37625[/C][C]1.00136176424665[/C][C]1.00057538663271[/C][/ROW]
[ROW][C]29[/C][C]48.51[/C][C]48.4803923840348[/C][C]48.41875[/C][C]1.00127310977741[/C][C]1.00061071320815[/C][/ROW]
[ROW][C]30[/C][C]48.53[/C][C]48.5158040431951[/C][C]48.46125[/C][C]1.00112572505239[/C][C]1.00029260479312[/C][/ROW]
[ROW][C]31[/C][C]48.53[/C][C]48.52402011733[/C][C]48.50375[/C][C]1.00041790825101[/C][C]1.00012323551626[/C][/ROW]
[ROW][C]32[/C][C]48.53[/C][C]48.5342910096616[/C][C]48.5466666666667[/C][C]0.999745077100966[/C][C]0.999911588083965[/C][/ROW]
[ROW][C]33[/C][C]48.68[/C][C]48.5869639150974[/C][C]48.5866666666667[/C][C]1.00000611790129[/C][C]1.00191483635539[/C][/ROW]
[ROW][C]34[/C][C]48.64[/C][C]48.633320532547[/C][C]48.6254166666667[/C][C]1.00016254597744[/C][C]1.00013734343820[/C][/ROW]
[ROW][C]35[/C][C]48.67[/C][C]48.6696544686801[/C][C]48.6666666666667[/C][C]1.00006139319206[/C][C]1.00000709952277[/C][/ROW]
[ROW][C]36[/C][C]48.66[/C][C]48.6794145100688[/C][C]48.70875[/C][C]0.999397736753023[/C][C]0.99960117617962[/C][/ROW]
[ROW][C]37[/C][C]48.66[/C][C]48.7067539602734[/C][C]48.75125[/C][C]0.999087284126528[/C][C]0.999040092872714[/C][/ROW]
[ROW][C]38[/C][C]48.67[/C][C]48.7246706995095[/C][C]48.79375[/C][C]0.998584259244463[/C][C]0.998877966772795[/C][/ROW]
[ROW][C]39[/C][C]48.71[/C][C]48.7711170513702[/C][C]48.8308333333333[/C][C]0.99877707837678[/C][C]0.998746859718104[/C][/ROW]
[ROW][C]40[/C][C]48.96[/C][C]48.9336287802547[/C][C]48.8670833333333[/C][C]1.00136176424665[/C][C]1.00053891813059[/C][/ROW]
[ROW][C]41[/C][C]49.01[/C][C]48.9714334049548[/C][C]48.9091666666667[/C][C]1.00127310977741[/C][C]1.00078753249320[/C][/ROW]
[ROW][C]42[/C][C]49.04[/C][C]49.0109441413772[/C][C]48.9558333333333[/C][C]1.00112572505239[/C][C]1.00059284429492[/C][/ROW]
[ROW][C]43[/C][C]49.04[/C][C]49.026313275431[/C][C]49.0058333333333[/C][C]1.00041790825101[/C][C]1.00027917099318[/C][/ROW]
[ROW][C]44[/C][C]49.04[/C][C]49.0429113176367[/C][C]49.0554166666667[/C][C]0.999745077100966[/C][C]0.999940637340679[/C][/ROW]
[ROW][C]45[/C][C]49.06[/C][C]49.1044670811113[/C][C]49.1041666666667[/C][C]1.00000611790129[/C][C]0.99909443918742[/C][/ROW]
[ROW][C]46[/C][C]49.13[/C][C]49.1559054628202[/C][C]49.1479166666667[/C][C]1.00016254597744[/C][C]0.999472993883923[/C][/ROW]
[ROW][C]47[/C][C]49.19[/C][C]49.1880196241513[/C][C]49.185[/C][C]1.00006139319206[/C][C]1.00004026134542[/C][/ROW]
[ROW][C]48[/C][C]49.26[/C][C]49.1899401872601[/C][C]49.2195833333333[/C][C]0.999397736753023[/C][C]1.00142427115124[/C][/ROW]
[ROW][C]49[/C][C]49.26[/C][C]49.208795320547[/C][C]49.25375[/C][C]0.999087284126528[/C][C]1.00104055949997[/C][/ROW]
[ROW][C]50[/C][C]49.26[/C][C]49.2185538310608[/C][C]49.2883333333333[/C][C]0.998584259244463[/C][C]1.00084208424899[/C][/ROW]
[ROW][C]51[/C][C]49.29[/C][C]49.2667601765146[/C][C]49.3270833333333[/C][C]0.99877707837678[/C][C]1.00047171406039[/C][/ROW]
[ROW][C]52[/C][C]49.43[/C][C]49.4384820030623[/C][C]49.37125[/C][C]1.00136176424665[/C][C]0.99982843318163[/C][/ROW]
[ROW][C]53[/C][C]49.43[/C][C]49.4787451139087[/C][C]49.4158333333333[/C][C]1.00127310977741[/C][C]0.999014827199104[/C][/ROW]
[ROW][C]54[/C][C]49.45[/C][C]49.5115070039034[/C][C]49.4558333333333[/C][C]1.00112572505239[/C][C]0.998757723050148[/C][/ROW]
[ROW][C]55[/C][C]49.45[/C][C]49.5131833241132[/C][C]49.4925[/C][C]1.00041790825101[/C][C]0.998723909070851[/C][/ROW]
[ROW][C]56[/C][C]49.46[/C][C]49.5207061524012[/C][C]49.5333333333333[/C][C]0.999745077100966[/C][C]0.99877412587344[/C][/ROW]
[ROW][C]57[/C][C]49.57[/C][C]49.5790533178986[/C][C]49.57875[/C][C]1.00000611790129[/C][C]0.99981739631371[/C][/ROW]
[ROW][C]58[/C][C]49.68[/C][C]49.6372336880719[/C][C]49.6291666666667[/C][C]1.00016254597744[/C][C]1.00086157726268[/C][/ROW]
[ROW][C]59[/C][C]49.71[/C][C]49.6918005509718[/C][C]49.68875[/C][C]1.00006139319206[/C][C]1.00036624652008[/C][/ROW]
[ROW][C]60[/C][C]49.7[/C][C]49.7204538191865[/C][C]49.7504166666667[/C][C]0.999397736753023[/C][C]0.999588623642477[/C][/ROW]
[ROW][C]61[/C][C]49.7[/C][C]49.764121335974[/C][C]49.8095833333333[/C][C]0.999087284126528[/C][C]0.998711494662167[/C][/ROW]
[ROW][C]62[/C][C]49.8[/C][C]49.8031416994935[/C][C]49.87375[/C][C]0.998584259244463[/C][C]0.999936917644423[/C][/ROW]
[ROW][C]63[/C][C]49.84[/C][C]49.8801757654844[/C][C]49.94125[/C][C]0.99877707837678[/C][C]0.999194554452389[/C][/ROW]
[ROW][C]64[/C][C]50.09[/C][C]50.0981290652598[/C][C]50.03[/C][C]1.00136176424665[/C][C]0.999837737148842[/C][/ROW]
[ROW][C]65[/C][C]50.2[/C][C]50.2046681184973[/C][C]50.1408333333333[/C][C]1.00127310977741[/C][C]0.999907018238099[/C][/ROW]
[ROW][C]66[/C][C]50.16[/C][C]50.3082362267576[/C][C]50.2516666666667[/C][C]1.00112572505239[/C][C]0.997053440194376[/C][/ROW]
[ROW][C]67[/C][C]50.16[/C][C]NA[/C][C]NA[/C][C]1.00041790825101[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]50.29[/C][C]NA[/C][C]NA[/C][C]0.999745077100966[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]50.36[/C][C]NA[/C][C]NA[/C][C]1.00000611790129[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]51.02[/C][C]NA[/C][C]NA[/C][C]1.00016254597744[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]51.03[/C][C]NA[/C][C]NA[/C][C]1.00006139319206[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]51.04[/C][C]NA[/C][C]NA[/C][C]0.999397736753023[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13098&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13098&T=1

As an alternative you can also use a QR Code:  

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

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
147.87NANA0.999087284126528NA
247.87NANA0.998584259244463NA
347.89NANA0.99877707837678NA
447.88NANA1.00136176424665NA
547.91NANA1.00127310977741NA
647.92NANA1.00112572505239NA
747.9247.96211872552947.94208333333331.000417908251010.99912183350844
847.9147.944857974620847.95708333333330.9997450771009660.999272956974046
947.9347.971543483372347.971251.000006117901290.999133997358524
1048.0547.994049971909847.986251.000162545977441.00116577009281
1148.0348.006697103443248.003751.000061393192061.00048540928585
1248.0447.99357781322248.02250.9993977367530231.00096725830607
1348.0447.998650847648748.04250.9990872841265281.00086146488747
1448.0647.994872036711748.06291666666670.9985842592444631.00135697753790
1548.0448.020785771239648.07958333333330.998777078376781.00040012316441
1648.0948.154652774484448.08916666666661.001361764246650.998657392987813
1748.1248.159150594647948.09791666666671.001273109777410.999187058032285
1848.1648.162072953676548.10791666666671.001125725052390.999956958794557
1948.1648.137191859472948.11708333333331.000417908251011.00047381535245
2048.1648.113148395932848.12541666666670.9997450771009661.00097377963466
2148.0848.139044508120848.138751.000006117901290.998773459076222
2248.1348.171995558214948.16416666666671.000162545977440.999128216347936
2348.1648.199208921632748.196251.000061393192060.999186523544475
2448.1548.198870764980148.22791666666670.9993977367530230.998986059959405
2548.1548.214703472841148.258750.9990872841265280.998658013672582
2648.1548.221217802140448.28958333333330.9985842592444630.998523102373054
2748.2748.270896197949848.330.998777078376780.999981433989829
2848.4748.442127047636948.376251.001361764246651.00057538663271
2948.5148.480392384034848.418751.001273109777411.00061071320815
3048.5348.515804043195148.461251.001125725052391.00029260479312
3148.5348.5240201173348.503751.000417908251011.00012323551626
3248.5348.534291009661648.54666666666670.9997450771009660.999911588083965
3348.6848.586963915097448.58666666666671.000006117901291.00191483635539
3448.6448.63332053254748.62541666666671.000162545977441.00013734343820
3548.6748.669654468680148.66666666666671.000061393192061.00000709952277
3648.6648.679414510068848.708750.9993977367530230.99960117617962
3748.6648.706753960273448.751250.9990872841265280.999040092872714
3848.6748.724670699509548.793750.9985842592444630.998877966772795
3948.7148.771117051370248.83083333333330.998777078376780.998746859718104
4048.9648.933628780254748.86708333333331.001361764246651.00053891813059
4149.0148.971433404954848.90916666666671.001273109777411.00078753249320
4249.0449.010944141377248.95583333333331.001125725052391.00059284429492
4349.0449.02631327543149.00583333333331.000417908251011.00027917099318
4449.0449.042911317636749.05541666666670.9997450771009660.999940637340679
4549.0649.104467081111349.10416666666671.000006117901290.99909443918742
4649.1349.155905462820249.14791666666671.000162545977440.999472993883923
4749.1949.188019624151349.1851.000061393192061.00004026134542
4849.2649.189940187260149.21958333333330.9993977367530231.00142427115124
4949.2649.20879532054749.253750.9990872841265281.00104055949997
5049.2649.218553831060849.28833333333330.9985842592444631.00084208424899
5149.2949.266760176514649.32708333333330.998777078376781.00047171406039
5249.4349.438482003062349.371251.001361764246650.99982843318163
5349.4349.478745113908749.41583333333331.001273109777410.999014827199104
5449.4549.511507003903449.45583333333331.001125725052390.998757723050148
5549.4549.513183324113249.49251.000417908251010.998723909070851
5649.4649.520706152401249.53333333333330.9997450771009660.99877412587344
5749.5749.579053317898649.578751.000006117901290.99981739631371
5849.6849.637233688071949.62916666666671.000162545977441.00086157726268
5949.7149.691800550971849.688751.000061393192061.00036624652008
6049.749.720453819186549.75041666666670.9993977367530230.999588623642477
6149.749.76412133597449.80958333333330.9990872841265280.998711494662167
6249.849.803141699493549.873750.9985842592444630.999936917644423
6349.8449.880175765484449.941250.998777078376780.999194554452389
6450.0950.098129065259850.031.001361764246650.999837737148842
6550.250.204668118497350.14083333333331.001273109777410.999907018238099
6650.1650.308236226757650.25166666666671.001125725052390.997053440194376
6750.16NANA1.00041790825101NA
6850.29NANA0.999745077100966NA
6950.36NANA1.00000611790129NA
7051.02NANA1.00016254597744NA
7151.03NANA1.00006139319206NA
7251.04NANA0.999397736753023NA



Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = multiplicative ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')