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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationFri, 25 May 2012 16:42:11 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/25/t133797866421al1jwnttdfsas.htm/, Retrieved Sat, 04 May 2024 00:01:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167538, Retrieved Sat, 04 May 2024 00:01:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2012-05-25 20:42:11] [11011eb66bd10d46e8c3e1885748d37e] [Current]
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Dataseries X:
97,81
97,81
97,34
97,02
96,96
96,89
96,89
96,87
96,63
96,35
96,34
96,39
96,39
96,31
96,28
96,28
96,7
96,66
96,66
96,66
96,72
96,88
96,77
96,74
96,74
96,62
97,04
96,93
96,24
96,21
96,21
96,18
96,2
96,51
96,69
96,77
96,77
96,66
96,75
96,98
96,33
96,37
96,37
96,37
96,44
96,65
97,31
97,41
97,41
97,48
97,29
97,15
97,23
97,15
97,15
97,26
96,99
97,71
97,89
97,81
97,81
97,78
98
98,72
98,85
98,93
98,93
98,95
99,41
99,47
99,57
99,63




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167538&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167538&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167538&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
197.81NANA1.0010335557385NA
297.81NANA1.00012423810204NA
397.34NANA1.00076324458593NA
497.02NANA1.00168639993256NA
596.96NANA0.999667788879871NA
696.89NANA0.999051830037025NA
796.8996.7354758745496.88250.9984824490959671.00159738838377
896.8796.626177432893396.76083333333330.9986083635723131.00252335933786
996.6396.44298803759696.65416666666670.9978151109636181.00193909340854
1096.3596.571282058792596.57916666666670.9999183611937620.997708614258038
1196.3496.679157823368696.53751.001467386490930.996491924102315
1296.3996.650399620875296.51708333333331.001381271407480.997305757431975
1396.3996.597652642190896.49791666666671.00103355573850.997850334490426
1496.3196.491569773651996.47958333333331.000124238102040.998118283554948
1596.2896.548217036742296.47458333333331.000763244585930.997221936924634
1696.2896.663154962825796.50041666666671.001686399932560.996036183973376
1796.796.508344866708196.54041666666670.9996677888798711.00198589182683
1896.6696.481349127846596.57291666666670.9990518300370251.0018516622515
1996.6696.455484754439396.60208333333330.9984824490959671.0021203070627
2096.6696.495110085174496.62958333333330.9986083635723131.00170879036958
2196.7296.462944339815396.67416666666670.9978151109636181.00266481250333
2296.8896.72501950682696.73291666666670.9999183611937621.00160227926512
2396.7796.882789525288496.74083333333331.001467386490930.998835814639101
2496.7496.836489640478496.70291666666671.001381271407480.999003581802308
2596.7496.76532576277796.66541666666671.00103355573850.999738276468587
2696.6296.638671380339496.62666666666671.000124238102040.999806791835269
2797.0496.658717978331996.5851.000763244585931.00394462113344
2896.9396.710735066822596.54791666666671.001686399932561.00226722434718
2996.2496.497098604083296.52916666666670.9996677888798710.997335685654778
3096.2196.435559252303196.52708333333330.9990518300370250.99766103650923
3196.2196.383094776879996.52958333333330.9984824490959670.998204096088836
3296.1896.398161856544396.53250.9986083635723130.997736867048679
3396.296.311193291689696.52208333333330.9978151109636180.998845479036348
3496.5196.504204202062496.51208333333330.9999183611937621.00006005746574
3596.6996.659545753716596.51791666666671.001467386490931.00031506713637
3696.7796.661665160178596.52833333333331.001381271407481.00112076322751
3796.7796.641447860254496.54166666666671.00103355573851.00133019674883
3896.6696.568245965239896.556251.000124238102041.00095014705759
3996.7596.647876376515596.57416666666671.000763244585931.00105665667279
4096.9896.752889369486496.591.001686399932561.00234732659659
4196.3396.589567874554596.62166666666660.9996677888798710.997312671748447
4296.3796.582503125637796.67416666666670.9990518300370250.997799776162756
4396.3796.580711094930196.72750.9984824490959670.997818290085657
4496.3796.653639162891596.78833333333330.9986083635723130.997065406275976
4596.4496.633404421271696.8450.9978151109636180.997998575933138
4696.6596.866674607995296.87458333333330.9999183611937620.997763166652804
4797.3197.06138454254696.91916666666671.001467386490931.00256142500569
4897.4197.123135029418896.98916666666671.001381271407481.00295362140539
4997.4197.154477557570397.05416666666671.00103355573851.0026300634706
5097.4897.135816470362797.123751.000124238102041.00354332255747
5197.2997.257924971027797.183751.000763244585931.00032979347423
5297.1597.414837132108497.25083333333331.001686399932560.997281347072938
5397.2397.286836157298297.31916666666660.9996677888798710.999415787792643
5497.1597.267686172404897.360.9990518300370250.998790079449447
5597.1597.245533992286597.39333333333330.9984824490959670.999017600208827
5697.2697.286923300123697.42250.9986083635723130.999723258797685
5796.9997.251634033772897.46458333333330.9978151109636180.997309720948422
5897.7197.551618685412997.55958333333330.9999183611937621.00162356418808
5997.8997.835852654765697.69251.001467386490931.00055345094631
6097.8197.969302203758197.83416666666671.001381271407480.9983739579626
6197.8198.083770375147697.98251.00103355573850.997208810651339
6297.7898.13927445592598.12708333333331.000124238102040.99633913682451
639898.373359004055898.29833333333331.000763244585930.996204673624692
6498.7298.638564017359498.47251.001686399932561.0008255998397
6598.8598.583072056879298.61583333333330.9996677888798711.00270764480708
6698.9398.6680238208498.76166666666670.9990518300370251.00265512745685
6798.93NANA0.998482449095967NA
6898.95NANA0.998608363572313NA
6999.41NANA0.997815110963618NA
7099.47NANA0.999918361193762NA
7199.57NANA1.00146738649093NA
7299.63NANA1.00138127140748NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 97.81 & NA & NA & 1.0010335557385 & NA \tabularnewline
2 & 97.81 & NA & NA & 1.00012423810204 & NA \tabularnewline
3 & 97.34 & NA & NA & 1.00076324458593 & NA \tabularnewline
4 & 97.02 & NA & NA & 1.00168639993256 & NA \tabularnewline
5 & 96.96 & NA & NA & 0.999667788879871 & NA \tabularnewline
6 & 96.89 & NA & NA & 0.999051830037025 & NA \tabularnewline
7 & 96.89 & 96.73547587454 & 96.8825 & 0.998482449095967 & 1.00159738838377 \tabularnewline
8 & 96.87 & 96.6261774328933 & 96.7608333333333 & 0.998608363572313 & 1.00252335933786 \tabularnewline
9 & 96.63 & 96.442988037596 & 96.6541666666667 & 0.997815110963618 & 1.00193909340854 \tabularnewline
10 & 96.35 & 96.5712820587925 & 96.5791666666667 & 0.999918361193762 & 0.997708614258038 \tabularnewline
11 & 96.34 & 96.6791578233686 & 96.5375 & 1.00146738649093 & 0.996491924102315 \tabularnewline
12 & 96.39 & 96.6503996208752 & 96.5170833333333 & 1.00138127140748 & 0.997305757431975 \tabularnewline
13 & 96.39 & 96.5976526421908 & 96.4979166666667 & 1.0010335557385 & 0.997850334490426 \tabularnewline
14 & 96.31 & 96.4915697736519 & 96.4795833333333 & 1.00012423810204 & 0.998118283554948 \tabularnewline
15 & 96.28 & 96.5482170367422 & 96.4745833333333 & 1.00076324458593 & 0.997221936924634 \tabularnewline
16 & 96.28 & 96.6631549628257 & 96.5004166666667 & 1.00168639993256 & 0.996036183973376 \tabularnewline
17 & 96.7 & 96.5083448667081 & 96.5404166666667 & 0.999667788879871 & 1.00198589182683 \tabularnewline
18 & 96.66 & 96.4813491278465 & 96.5729166666667 & 0.999051830037025 & 1.0018516622515 \tabularnewline
19 & 96.66 & 96.4554847544393 & 96.6020833333333 & 0.998482449095967 & 1.0021203070627 \tabularnewline
20 & 96.66 & 96.4951100851744 & 96.6295833333333 & 0.998608363572313 & 1.00170879036958 \tabularnewline
21 & 96.72 & 96.4629443398153 & 96.6741666666667 & 0.997815110963618 & 1.00266481250333 \tabularnewline
22 & 96.88 & 96.725019506826 & 96.7329166666667 & 0.999918361193762 & 1.00160227926512 \tabularnewline
23 & 96.77 & 96.8827895252884 & 96.7408333333333 & 1.00146738649093 & 0.998835814639101 \tabularnewline
24 & 96.74 & 96.8364896404784 & 96.7029166666667 & 1.00138127140748 & 0.999003581802308 \tabularnewline
25 & 96.74 & 96.765325762777 & 96.6654166666667 & 1.0010335557385 & 0.999738276468587 \tabularnewline
26 & 96.62 & 96.6386713803394 & 96.6266666666667 & 1.00012423810204 & 0.999806791835269 \tabularnewline
27 & 97.04 & 96.6587179783319 & 96.585 & 1.00076324458593 & 1.00394462113344 \tabularnewline
28 & 96.93 & 96.7107350668225 & 96.5479166666667 & 1.00168639993256 & 1.00226722434718 \tabularnewline
29 & 96.24 & 96.4970986040832 & 96.5291666666667 & 0.999667788879871 & 0.997335685654778 \tabularnewline
30 & 96.21 & 96.4355592523031 & 96.5270833333333 & 0.999051830037025 & 0.99766103650923 \tabularnewline
31 & 96.21 & 96.3830947768799 & 96.5295833333333 & 0.998482449095967 & 0.998204096088836 \tabularnewline
32 & 96.18 & 96.3981618565443 & 96.5325 & 0.998608363572313 & 0.997736867048679 \tabularnewline
33 & 96.2 & 96.3111932916896 & 96.5220833333333 & 0.997815110963618 & 0.998845479036348 \tabularnewline
34 & 96.51 & 96.5042042020624 & 96.5120833333333 & 0.999918361193762 & 1.00006005746574 \tabularnewline
35 & 96.69 & 96.6595457537165 & 96.5179166666667 & 1.00146738649093 & 1.00031506713637 \tabularnewline
36 & 96.77 & 96.6616651601785 & 96.5283333333333 & 1.00138127140748 & 1.00112076322751 \tabularnewline
37 & 96.77 & 96.6414478602544 & 96.5416666666667 & 1.0010335557385 & 1.00133019674883 \tabularnewline
38 & 96.66 & 96.5682459652398 & 96.55625 & 1.00012423810204 & 1.00095014705759 \tabularnewline
39 & 96.75 & 96.6478763765155 & 96.5741666666667 & 1.00076324458593 & 1.00105665667279 \tabularnewline
40 & 96.98 & 96.7528893694864 & 96.59 & 1.00168639993256 & 1.00234732659659 \tabularnewline
41 & 96.33 & 96.5895678745545 & 96.6216666666666 & 0.999667788879871 & 0.997312671748447 \tabularnewline
42 & 96.37 & 96.5825031256377 & 96.6741666666667 & 0.999051830037025 & 0.997799776162756 \tabularnewline
43 & 96.37 & 96.5807110949301 & 96.7275 & 0.998482449095967 & 0.997818290085657 \tabularnewline
44 & 96.37 & 96.6536391628915 & 96.7883333333333 & 0.998608363572313 & 0.997065406275976 \tabularnewline
45 & 96.44 & 96.6334044212716 & 96.845 & 0.997815110963618 & 0.997998575933138 \tabularnewline
46 & 96.65 & 96.8666746079952 & 96.8745833333333 & 0.999918361193762 & 0.997763166652804 \tabularnewline
47 & 97.31 & 97.061384542546 & 96.9191666666667 & 1.00146738649093 & 1.00256142500569 \tabularnewline
48 & 97.41 & 97.1231350294188 & 96.9891666666667 & 1.00138127140748 & 1.00295362140539 \tabularnewline
49 & 97.41 & 97.1544775575703 & 97.0541666666667 & 1.0010335557385 & 1.0026300634706 \tabularnewline
50 & 97.48 & 97.1358164703627 & 97.12375 & 1.00012423810204 & 1.00354332255747 \tabularnewline
51 & 97.29 & 97.2579249710277 & 97.18375 & 1.00076324458593 & 1.00032979347423 \tabularnewline
52 & 97.15 & 97.4148371321084 & 97.2508333333333 & 1.00168639993256 & 0.997281347072938 \tabularnewline
53 & 97.23 & 97.2868361572982 & 97.3191666666666 & 0.999667788879871 & 0.999415787792643 \tabularnewline
54 & 97.15 & 97.2676861724048 & 97.36 & 0.999051830037025 & 0.998790079449447 \tabularnewline
55 & 97.15 & 97.2455339922865 & 97.3933333333333 & 0.998482449095967 & 0.999017600208827 \tabularnewline
56 & 97.26 & 97.2869233001236 & 97.4225 & 0.998608363572313 & 0.999723258797685 \tabularnewline
57 & 96.99 & 97.2516340337728 & 97.4645833333333 & 0.997815110963618 & 0.997309720948422 \tabularnewline
58 & 97.71 & 97.5516186854129 & 97.5595833333333 & 0.999918361193762 & 1.00162356418808 \tabularnewline
59 & 97.89 & 97.8358526547656 & 97.6925 & 1.00146738649093 & 1.00055345094631 \tabularnewline
60 & 97.81 & 97.9693022037581 & 97.8341666666667 & 1.00138127140748 & 0.9983739579626 \tabularnewline
61 & 97.81 & 98.0837703751476 & 97.9825 & 1.0010335557385 & 0.997208810651339 \tabularnewline
62 & 97.78 & 98.139274455925 & 98.1270833333333 & 1.00012423810204 & 0.99633913682451 \tabularnewline
63 & 98 & 98.3733590040558 & 98.2983333333333 & 1.00076324458593 & 0.996204673624692 \tabularnewline
64 & 98.72 & 98.6385640173594 & 98.4725 & 1.00168639993256 & 1.0008255998397 \tabularnewline
65 & 98.85 & 98.5830720568792 & 98.6158333333333 & 0.999667788879871 & 1.00270764480708 \tabularnewline
66 & 98.93 & 98.66802382084 & 98.7616666666667 & 0.999051830037025 & 1.00265512745685 \tabularnewline
67 & 98.93 & NA & NA & 0.998482449095967 & NA \tabularnewline
68 & 98.95 & NA & NA & 0.998608363572313 & NA \tabularnewline
69 & 99.41 & NA & NA & 0.997815110963618 & NA \tabularnewline
70 & 99.47 & NA & NA & 0.999918361193762 & NA \tabularnewline
71 & 99.57 & NA & NA & 1.00146738649093 & NA \tabularnewline
72 & 99.63 & NA & NA & 1.00138127140748 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167538&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]97.81[/C][C]NA[/C][C]NA[/C][C]1.0010335557385[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]97.81[/C][C]NA[/C][C]NA[/C][C]1.00012423810204[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]97.34[/C][C]NA[/C][C]NA[/C][C]1.00076324458593[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]97.02[/C][C]NA[/C][C]NA[/C][C]1.00168639993256[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]96.96[/C][C]NA[/C][C]NA[/C][C]0.999667788879871[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]96.89[/C][C]NA[/C][C]NA[/C][C]0.999051830037025[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]96.89[/C][C]96.73547587454[/C][C]96.8825[/C][C]0.998482449095967[/C][C]1.00159738838377[/C][/ROW]
[ROW][C]8[/C][C]96.87[/C][C]96.6261774328933[/C][C]96.7608333333333[/C][C]0.998608363572313[/C][C]1.00252335933786[/C][/ROW]
[ROW][C]9[/C][C]96.63[/C][C]96.442988037596[/C][C]96.6541666666667[/C][C]0.997815110963618[/C][C]1.00193909340854[/C][/ROW]
[ROW][C]10[/C][C]96.35[/C][C]96.5712820587925[/C][C]96.5791666666667[/C][C]0.999918361193762[/C][C]0.997708614258038[/C][/ROW]
[ROW][C]11[/C][C]96.34[/C][C]96.6791578233686[/C][C]96.5375[/C][C]1.00146738649093[/C][C]0.996491924102315[/C][/ROW]
[ROW][C]12[/C][C]96.39[/C][C]96.6503996208752[/C][C]96.5170833333333[/C][C]1.00138127140748[/C][C]0.997305757431975[/C][/ROW]
[ROW][C]13[/C][C]96.39[/C][C]96.5976526421908[/C][C]96.4979166666667[/C][C]1.0010335557385[/C][C]0.997850334490426[/C][/ROW]
[ROW][C]14[/C][C]96.31[/C][C]96.4915697736519[/C][C]96.4795833333333[/C][C]1.00012423810204[/C][C]0.998118283554948[/C][/ROW]
[ROW][C]15[/C][C]96.28[/C][C]96.5482170367422[/C][C]96.4745833333333[/C][C]1.00076324458593[/C][C]0.997221936924634[/C][/ROW]
[ROW][C]16[/C][C]96.28[/C][C]96.6631549628257[/C][C]96.5004166666667[/C][C]1.00168639993256[/C][C]0.996036183973376[/C][/ROW]
[ROW][C]17[/C][C]96.7[/C][C]96.5083448667081[/C][C]96.5404166666667[/C][C]0.999667788879871[/C][C]1.00198589182683[/C][/ROW]
[ROW][C]18[/C][C]96.66[/C][C]96.4813491278465[/C][C]96.5729166666667[/C][C]0.999051830037025[/C][C]1.0018516622515[/C][/ROW]
[ROW][C]19[/C][C]96.66[/C][C]96.4554847544393[/C][C]96.6020833333333[/C][C]0.998482449095967[/C][C]1.0021203070627[/C][/ROW]
[ROW][C]20[/C][C]96.66[/C][C]96.4951100851744[/C][C]96.6295833333333[/C][C]0.998608363572313[/C][C]1.00170879036958[/C][/ROW]
[ROW][C]21[/C][C]96.72[/C][C]96.4629443398153[/C][C]96.6741666666667[/C][C]0.997815110963618[/C][C]1.00266481250333[/C][/ROW]
[ROW][C]22[/C][C]96.88[/C][C]96.725019506826[/C][C]96.7329166666667[/C][C]0.999918361193762[/C][C]1.00160227926512[/C][/ROW]
[ROW][C]23[/C][C]96.77[/C][C]96.8827895252884[/C][C]96.7408333333333[/C][C]1.00146738649093[/C][C]0.998835814639101[/C][/ROW]
[ROW][C]24[/C][C]96.74[/C][C]96.8364896404784[/C][C]96.7029166666667[/C][C]1.00138127140748[/C][C]0.999003581802308[/C][/ROW]
[ROW][C]25[/C][C]96.74[/C][C]96.765325762777[/C][C]96.6654166666667[/C][C]1.0010335557385[/C][C]0.999738276468587[/C][/ROW]
[ROW][C]26[/C][C]96.62[/C][C]96.6386713803394[/C][C]96.6266666666667[/C][C]1.00012423810204[/C][C]0.999806791835269[/C][/ROW]
[ROW][C]27[/C][C]97.04[/C][C]96.6587179783319[/C][C]96.585[/C][C]1.00076324458593[/C][C]1.00394462113344[/C][/ROW]
[ROW][C]28[/C][C]96.93[/C][C]96.7107350668225[/C][C]96.5479166666667[/C][C]1.00168639993256[/C][C]1.00226722434718[/C][/ROW]
[ROW][C]29[/C][C]96.24[/C][C]96.4970986040832[/C][C]96.5291666666667[/C][C]0.999667788879871[/C][C]0.997335685654778[/C][/ROW]
[ROW][C]30[/C][C]96.21[/C][C]96.4355592523031[/C][C]96.5270833333333[/C][C]0.999051830037025[/C][C]0.99766103650923[/C][/ROW]
[ROW][C]31[/C][C]96.21[/C][C]96.3830947768799[/C][C]96.5295833333333[/C][C]0.998482449095967[/C][C]0.998204096088836[/C][/ROW]
[ROW][C]32[/C][C]96.18[/C][C]96.3981618565443[/C][C]96.5325[/C][C]0.998608363572313[/C][C]0.997736867048679[/C][/ROW]
[ROW][C]33[/C][C]96.2[/C][C]96.3111932916896[/C][C]96.5220833333333[/C][C]0.997815110963618[/C][C]0.998845479036348[/C][/ROW]
[ROW][C]34[/C][C]96.51[/C][C]96.5042042020624[/C][C]96.5120833333333[/C][C]0.999918361193762[/C][C]1.00006005746574[/C][/ROW]
[ROW][C]35[/C][C]96.69[/C][C]96.6595457537165[/C][C]96.5179166666667[/C][C]1.00146738649093[/C][C]1.00031506713637[/C][/ROW]
[ROW][C]36[/C][C]96.77[/C][C]96.6616651601785[/C][C]96.5283333333333[/C][C]1.00138127140748[/C][C]1.00112076322751[/C][/ROW]
[ROW][C]37[/C][C]96.77[/C][C]96.6414478602544[/C][C]96.5416666666667[/C][C]1.0010335557385[/C][C]1.00133019674883[/C][/ROW]
[ROW][C]38[/C][C]96.66[/C][C]96.5682459652398[/C][C]96.55625[/C][C]1.00012423810204[/C][C]1.00095014705759[/C][/ROW]
[ROW][C]39[/C][C]96.75[/C][C]96.6478763765155[/C][C]96.5741666666667[/C][C]1.00076324458593[/C][C]1.00105665667279[/C][/ROW]
[ROW][C]40[/C][C]96.98[/C][C]96.7528893694864[/C][C]96.59[/C][C]1.00168639993256[/C][C]1.00234732659659[/C][/ROW]
[ROW][C]41[/C][C]96.33[/C][C]96.5895678745545[/C][C]96.6216666666666[/C][C]0.999667788879871[/C][C]0.997312671748447[/C][/ROW]
[ROW][C]42[/C][C]96.37[/C][C]96.5825031256377[/C][C]96.6741666666667[/C][C]0.999051830037025[/C][C]0.997799776162756[/C][/ROW]
[ROW][C]43[/C][C]96.37[/C][C]96.5807110949301[/C][C]96.7275[/C][C]0.998482449095967[/C][C]0.997818290085657[/C][/ROW]
[ROW][C]44[/C][C]96.37[/C][C]96.6536391628915[/C][C]96.7883333333333[/C][C]0.998608363572313[/C][C]0.997065406275976[/C][/ROW]
[ROW][C]45[/C][C]96.44[/C][C]96.6334044212716[/C][C]96.845[/C][C]0.997815110963618[/C][C]0.997998575933138[/C][/ROW]
[ROW][C]46[/C][C]96.65[/C][C]96.8666746079952[/C][C]96.8745833333333[/C][C]0.999918361193762[/C][C]0.997763166652804[/C][/ROW]
[ROW][C]47[/C][C]97.31[/C][C]97.061384542546[/C][C]96.9191666666667[/C][C]1.00146738649093[/C][C]1.00256142500569[/C][/ROW]
[ROW][C]48[/C][C]97.41[/C][C]97.1231350294188[/C][C]96.9891666666667[/C][C]1.00138127140748[/C][C]1.00295362140539[/C][/ROW]
[ROW][C]49[/C][C]97.41[/C][C]97.1544775575703[/C][C]97.0541666666667[/C][C]1.0010335557385[/C][C]1.0026300634706[/C][/ROW]
[ROW][C]50[/C][C]97.48[/C][C]97.1358164703627[/C][C]97.12375[/C][C]1.00012423810204[/C][C]1.00354332255747[/C][/ROW]
[ROW][C]51[/C][C]97.29[/C][C]97.2579249710277[/C][C]97.18375[/C][C]1.00076324458593[/C][C]1.00032979347423[/C][/ROW]
[ROW][C]52[/C][C]97.15[/C][C]97.4148371321084[/C][C]97.2508333333333[/C][C]1.00168639993256[/C][C]0.997281347072938[/C][/ROW]
[ROW][C]53[/C][C]97.23[/C][C]97.2868361572982[/C][C]97.3191666666666[/C][C]0.999667788879871[/C][C]0.999415787792643[/C][/ROW]
[ROW][C]54[/C][C]97.15[/C][C]97.2676861724048[/C][C]97.36[/C][C]0.999051830037025[/C][C]0.998790079449447[/C][/ROW]
[ROW][C]55[/C][C]97.15[/C][C]97.2455339922865[/C][C]97.3933333333333[/C][C]0.998482449095967[/C][C]0.999017600208827[/C][/ROW]
[ROW][C]56[/C][C]97.26[/C][C]97.2869233001236[/C][C]97.4225[/C][C]0.998608363572313[/C][C]0.999723258797685[/C][/ROW]
[ROW][C]57[/C][C]96.99[/C][C]97.2516340337728[/C][C]97.4645833333333[/C][C]0.997815110963618[/C][C]0.997309720948422[/C][/ROW]
[ROW][C]58[/C][C]97.71[/C][C]97.5516186854129[/C][C]97.5595833333333[/C][C]0.999918361193762[/C][C]1.00162356418808[/C][/ROW]
[ROW][C]59[/C][C]97.89[/C][C]97.8358526547656[/C][C]97.6925[/C][C]1.00146738649093[/C][C]1.00055345094631[/C][/ROW]
[ROW][C]60[/C][C]97.81[/C][C]97.9693022037581[/C][C]97.8341666666667[/C][C]1.00138127140748[/C][C]0.9983739579626[/C][/ROW]
[ROW][C]61[/C][C]97.81[/C][C]98.0837703751476[/C][C]97.9825[/C][C]1.0010335557385[/C][C]0.997208810651339[/C][/ROW]
[ROW][C]62[/C][C]97.78[/C][C]98.139274455925[/C][C]98.1270833333333[/C][C]1.00012423810204[/C][C]0.99633913682451[/C][/ROW]
[ROW][C]63[/C][C]98[/C][C]98.3733590040558[/C][C]98.2983333333333[/C][C]1.00076324458593[/C][C]0.996204673624692[/C][/ROW]
[ROW][C]64[/C][C]98.72[/C][C]98.6385640173594[/C][C]98.4725[/C][C]1.00168639993256[/C][C]1.0008255998397[/C][/ROW]
[ROW][C]65[/C][C]98.85[/C][C]98.5830720568792[/C][C]98.6158333333333[/C][C]0.999667788879871[/C][C]1.00270764480708[/C][/ROW]
[ROW][C]66[/C][C]98.93[/C][C]98.66802382084[/C][C]98.7616666666667[/C][C]0.999051830037025[/C][C]1.00265512745685[/C][/ROW]
[ROW][C]67[/C][C]98.93[/C][C]NA[/C][C]NA[/C][C]0.998482449095967[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]98.95[/C][C]NA[/C][C]NA[/C][C]0.998608363572313[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]99.41[/C][C]NA[/C][C]NA[/C][C]0.997815110963618[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]99.47[/C][C]NA[/C][C]NA[/C][C]0.999918361193762[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]99.57[/C][C]NA[/C][C]NA[/C][C]1.00146738649093[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]99.63[/C][C]NA[/C][C]NA[/C][C]1.00138127140748[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167538&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167538&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
197.81NANA1.0010335557385NA
297.81NANA1.00012423810204NA
397.34NANA1.00076324458593NA
497.02NANA1.00168639993256NA
596.96NANA0.999667788879871NA
696.89NANA0.999051830037025NA
796.8996.7354758745496.88250.9984824490959671.00159738838377
896.8796.626177432893396.76083333333330.9986083635723131.00252335933786
996.6396.44298803759696.65416666666670.9978151109636181.00193909340854
1096.3596.571282058792596.57916666666670.9999183611937620.997708614258038
1196.3496.679157823368696.53751.001467386490930.996491924102315
1296.3996.650399620875296.51708333333331.001381271407480.997305757431975
1396.3996.597652642190896.49791666666671.00103355573850.997850334490426
1496.3196.491569773651996.47958333333331.000124238102040.998118283554948
1596.2896.548217036742296.47458333333331.000763244585930.997221936924634
1696.2896.663154962825796.50041666666671.001686399932560.996036183973376
1796.796.508344866708196.54041666666670.9996677888798711.00198589182683
1896.6696.481349127846596.57291666666670.9990518300370251.0018516622515
1996.6696.455484754439396.60208333333330.9984824490959671.0021203070627
2096.6696.495110085174496.62958333333330.9986083635723131.00170879036958
2196.7296.462944339815396.67416666666670.9978151109636181.00266481250333
2296.8896.72501950682696.73291666666670.9999183611937621.00160227926512
2396.7796.882789525288496.74083333333331.001467386490930.998835814639101
2496.7496.836489640478496.70291666666671.001381271407480.999003581802308
2596.7496.76532576277796.66541666666671.00103355573850.999738276468587
2696.6296.638671380339496.62666666666671.000124238102040.999806791835269
2797.0496.658717978331996.5851.000763244585931.00394462113344
2896.9396.710735066822596.54791666666671.001686399932561.00226722434718
2996.2496.497098604083296.52916666666670.9996677888798710.997335685654778
3096.2196.435559252303196.52708333333330.9990518300370250.99766103650923
3196.2196.383094776879996.52958333333330.9984824490959670.998204096088836
3296.1896.398161856544396.53250.9986083635723130.997736867048679
3396.296.311193291689696.52208333333330.9978151109636180.998845479036348
3496.5196.504204202062496.51208333333330.9999183611937621.00006005746574
3596.6996.659545753716596.51791666666671.001467386490931.00031506713637
3696.7796.661665160178596.52833333333331.001381271407481.00112076322751
3796.7796.641447860254496.54166666666671.00103355573851.00133019674883
3896.6696.568245965239896.556251.000124238102041.00095014705759
3996.7596.647876376515596.57416666666671.000763244585931.00105665667279
4096.9896.752889369486496.591.001686399932561.00234732659659
4196.3396.589567874554596.62166666666660.9996677888798710.997312671748447
4296.3796.582503125637796.67416666666670.9990518300370250.997799776162756
4396.3796.580711094930196.72750.9984824490959670.997818290085657
4496.3796.653639162891596.78833333333330.9986083635723130.997065406275976
4596.4496.633404421271696.8450.9978151109636180.997998575933138
4696.6596.866674607995296.87458333333330.9999183611937620.997763166652804
4797.3197.06138454254696.91916666666671.001467386490931.00256142500569
4897.4197.123135029418896.98916666666671.001381271407481.00295362140539
4997.4197.154477557570397.05416666666671.00103355573851.0026300634706
5097.4897.135816470362797.123751.000124238102041.00354332255747
5197.2997.257924971027797.183751.000763244585931.00032979347423
5297.1597.414837132108497.25083333333331.001686399932560.997281347072938
5397.2397.286836157298297.31916666666660.9996677888798710.999415787792643
5497.1597.267686172404897.360.9990518300370250.998790079449447
5597.1597.245533992286597.39333333333330.9984824490959670.999017600208827
5697.2697.286923300123697.42250.9986083635723130.999723258797685
5796.9997.251634033772897.46458333333330.9978151109636180.997309720948422
5897.7197.551618685412997.55958333333330.9999183611937621.00162356418808
5997.8997.835852654765697.69251.001467386490931.00055345094631
6097.8197.969302203758197.83416666666671.001381271407480.9983739579626
6197.8198.083770375147697.98251.00103355573850.997208810651339
6297.7898.13927445592598.12708333333331.000124238102040.99633913682451
639898.373359004055898.29833333333331.000763244585930.996204673624692
6498.7298.638564017359498.47251.001686399932561.0008255998397
6598.8598.583072056879298.61583333333330.9996677888798711.00270764480708
6698.9398.6680238208498.76166666666670.9990518300370251.00265512745685
6798.93NANA0.998482449095967NA
6898.95NANA0.998608363572313NA
6999.41NANA0.997815110963618NA
7099.47NANA0.999918361193762NA
7199.57NANA1.00146738649093NA
7299.63NANA1.00138127140748NA



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')