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R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSun, 09 Dec 2012 13:26:49 -0500
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/Dec/09/t1355077628iq56ykthej3czlj.htm/, Retrieved Thu, 31 Oct 2024 23:40:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198024, Retrieved Thu, 31 Oct 2024 23:40:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2012-12-09 18:26:49] [50b2e07c322f56d9c76b19a7ea7f6b48] [Current]
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Dataseries X:
10
9,99
9,95
9,96
9,97
9,95
9,94
9,9
9,9
9,92
9,87
9,96
9,94
9,96
9,96
9,89
9,82
9,83
9,83
9,82
9,77
9,66
9,69
9,67
9,7
9,77
9,79
9,81
9,77
9,78
9,77
9,79
9,77
9,77
9,8
9,8
9,8
9,8
9,76
9,78
9,77
9,79
9,81
9,82
9,84
9,87
9,99
9,99
9,99
10,08
10,06
10,08
10,07
10,04
10,04
10,12
10,1
10,11
10,13
10,16
10,15
10,25
10,41
10,46
10,46
10,5
10,5
10,48
10,5
10,5
10,53
10,53




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198024&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198024&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198024&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 time4 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
110NANA0.998326441325252NA
29.99NANA1.00298933670607NA
39.95NANA1.00432191705148NA
49.96NANA1.00412163595221NA
59.97NANA1.00045999509418NA
69.95NANA1.00044210938845NA
79.949.928493242641219.940.9988423785353331.00115896310523
89.99.933204276506379.936250.9996934735444830.99665724416995
99.99.912363584274289.935416666666670.9976797065321150.998752710776883
109.929.891657387004919.932916666666660.9958462070058221.00286530475998
119.879.904564200745969.923750.9980666784981440.996510275460342
129.969.904670318132659.91250.9992101203664721.00558622145818
139.949.886343554573869.902916666666660.9983264413252521.00542732964214
149.969.924579486706519.8951.002989336706071.00356896867428
159.969.928977552450169.886251.004321917051481.00312443525891
169.899.91068054684839.871.004121635952210.997913307088192
179.829.85619838500289.851666666666671.000459995094180.99632734817332
189.839.836430189683029.832083333333331.000442109388450.999346288281519
199.839.798643733431629.810.9988423785353331.00320006190871
209.829.789081800737049.792083333333330.9996934735444831.00315843711314
219.779.754397630740039.777083333333330.9976797065321151.00159952155434
229.669.726097955090199.766666666666670.9958462070058220.993204062369575
239.699.742378365490019.761250.9980666784981440.994623657229784
249.679.74937641192579.757083333333330.9992101203664720.991858308821823
259.79.736178619024529.75250.9983264413252520.996284104838234
269.779.777892296213259.748751.002989336706070.999192842795343
279.799.789627886459279.74751.004321917051481.0000380109995
289.819.792277870608949.752083333333331.004121635952211.00180980662776
299.779.765740127113049.761251.000459995094181.00043620584119
309.789.775569961361899.771251.000442109388451.00045317445997
319.779.769510830724349.780833333333330.9988423785353331.00005007101012
329.799.78325025547479.786250.9996934735444831.00068992863814
339.779.763543028049919.786250.9976797065321151.00066133492028
349.779.743110327793219.783750.9958462070058221.00275986531016
359.89.763587282408099.78250.9980666784981441.00372944047497
369.89.775189340035179.782916666666670.9992101203664721.00253812576941
379.89.768624228367599.7850.9983264413252521.00321189257555
389.89.817176045234249.787916666666671.002989336706070.998250408757559
399.769.834403905261149.792083333333331.004321917051480.992434324847961
409.789.839555264301699.799166666666661.004121635952210.993947362182338
419.779.815763126867749.811251.000459995094180.995337792255553
429.799.831427979136089.827083333333331.000442109388450.995786168680277
439.819.83152229505849.842916666666660.9988423785353330.997810888851951
449.829.859476882832469.86250.9996934735444830.995996046919974
459.849.863726698580849.886666666666660.9976797065321150.997594550284503
469.879.870495655106049.911666666666670.9958462070058220.999949784172613
479.999.917455895343229.936666666666670.9980666784981441.00731478974268
489.999.951716461299919.959583333333330.9992101203664721.00384692820067
499.999.962881915075469.979583333333330.9983264413252521.00272191170745
5010.0810.031565015955210.00166666666671.002989336706071.0048282580004
5110.0610.068327218441110.0251.004321917051480.999172929299934
5210.0810.087238601169910.04583333333331.004121635952210.999282400123949
5310.0710.066294983972610.06166666666671.000459995094181.00036806153936
5410.0410.079037401209710.07458333333331.000442109388450.996126872075597
5510.0410.07665486212410.08833333333330.9988423785353330.996362397777289
5610.1210.098986777535810.10208333333330.9996934735444831.00208072581211
5710.110.100259929004510.123750.9976797065321150.999974265117301
5810.1110.11198836030510.15416666666670.9958462070058220.99980336604097
5910.1310.166556703851710.186250.9980666784981440.996404219745524
6010.1610.21359278034610.22166666666670.9992101203664720.994752798403214
6110.1510.242829287997110.260.9983264413252520.990937143889934
6210.2510.324939396941710.29416666666671.002989336706070.992741904425717
6310.4110.370460728487410.32583333333331.004321917051481.00381268224699
6410.4610.401444996419910.358751.004121635952211.00562950663107
6510.4610.396446782353710.39166666666671.000459995094181.00611297484389
6610.510.428358437737910.423751.000442109388451.00686987915595
6710.5NANA0.998842378535333NA
6810.48NANA0.999693473544483NA
6910.5NANA0.997679706532115NA
7010.5NANA0.995846207005822NA
7110.53NANA0.998066678498144NA
7210.53NANA0.999210120366472NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 10 & NA & NA & 0.998326441325252 & NA \tabularnewline
2 & 9.99 & NA & NA & 1.00298933670607 & NA \tabularnewline
3 & 9.95 & NA & NA & 1.00432191705148 & NA \tabularnewline
4 & 9.96 & NA & NA & 1.00412163595221 & NA \tabularnewline
5 & 9.97 & NA & NA & 1.00045999509418 & NA \tabularnewline
6 & 9.95 & NA & NA & 1.00044210938845 & NA \tabularnewline
7 & 9.94 & 9.92849324264121 & 9.94 & 0.998842378535333 & 1.00115896310523 \tabularnewline
8 & 9.9 & 9.93320427650637 & 9.93625 & 0.999693473544483 & 0.99665724416995 \tabularnewline
9 & 9.9 & 9.91236358427428 & 9.93541666666667 & 0.997679706532115 & 0.998752710776883 \tabularnewline
10 & 9.92 & 9.89165738700491 & 9.93291666666666 & 0.995846207005822 & 1.00286530475998 \tabularnewline
11 & 9.87 & 9.90456420074596 & 9.92375 & 0.998066678498144 & 0.996510275460342 \tabularnewline
12 & 9.96 & 9.90467031813265 & 9.9125 & 0.999210120366472 & 1.00558622145818 \tabularnewline
13 & 9.94 & 9.88634355457386 & 9.90291666666666 & 0.998326441325252 & 1.00542732964214 \tabularnewline
14 & 9.96 & 9.92457948670651 & 9.895 & 1.00298933670607 & 1.00356896867428 \tabularnewline
15 & 9.96 & 9.92897755245016 & 9.88625 & 1.00432191705148 & 1.00312443525891 \tabularnewline
16 & 9.89 & 9.9106805468483 & 9.87 & 1.00412163595221 & 0.997913307088192 \tabularnewline
17 & 9.82 & 9.8561983850028 & 9.85166666666667 & 1.00045999509418 & 0.99632734817332 \tabularnewline
18 & 9.83 & 9.83643018968302 & 9.83208333333333 & 1.00044210938845 & 0.999346288281519 \tabularnewline
19 & 9.83 & 9.79864373343162 & 9.81 & 0.998842378535333 & 1.00320006190871 \tabularnewline
20 & 9.82 & 9.78908180073704 & 9.79208333333333 & 0.999693473544483 & 1.00315843711314 \tabularnewline
21 & 9.77 & 9.75439763074003 & 9.77708333333333 & 0.997679706532115 & 1.00159952155434 \tabularnewline
22 & 9.66 & 9.72609795509019 & 9.76666666666667 & 0.995846207005822 & 0.993204062369575 \tabularnewline
23 & 9.69 & 9.74237836549001 & 9.76125 & 0.998066678498144 & 0.994623657229784 \tabularnewline
24 & 9.67 & 9.7493764119257 & 9.75708333333333 & 0.999210120366472 & 0.991858308821823 \tabularnewline
25 & 9.7 & 9.73617861902452 & 9.7525 & 0.998326441325252 & 0.996284104838234 \tabularnewline
26 & 9.77 & 9.77789229621325 & 9.74875 & 1.00298933670607 & 0.999192842795343 \tabularnewline
27 & 9.79 & 9.78962788645927 & 9.7475 & 1.00432191705148 & 1.0000380109995 \tabularnewline
28 & 9.81 & 9.79227787060894 & 9.75208333333333 & 1.00412163595221 & 1.00180980662776 \tabularnewline
29 & 9.77 & 9.76574012711304 & 9.76125 & 1.00045999509418 & 1.00043620584119 \tabularnewline
30 & 9.78 & 9.77556996136189 & 9.77125 & 1.00044210938845 & 1.00045317445997 \tabularnewline
31 & 9.77 & 9.76951083072434 & 9.78083333333333 & 0.998842378535333 & 1.00005007101012 \tabularnewline
32 & 9.79 & 9.7832502554747 & 9.78625 & 0.999693473544483 & 1.00068992863814 \tabularnewline
33 & 9.77 & 9.76354302804991 & 9.78625 & 0.997679706532115 & 1.00066133492028 \tabularnewline
34 & 9.77 & 9.74311032779321 & 9.78375 & 0.995846207005822 & 1.00275986531016 \tabularnewline
35 & 9.8 & 9.76358728240809 & 9.7825 & 0.998066678498144 & 1.00372944047497 \tabularnewline
36 & 9.8 & 9.77518934003517 & 9.78291666666667 & 0.999210120366472 & 1.00253812576941 \tabularnewline
37 & 9.8 & 9.76862422836759 & 9.785 & 0.998326441325252 & 1.00321189257555 \tabularnewline
38 & 9.8 & 9.81717604523424 & 9.78791666666667 & 1.00298933670607 & 0.998250408757559 \tabularnewline
39 & 9.76 & 9.83440390526114 & 9.79208333333333 & 1.00432191705148 & 0.992434324847961 \tabularnewline
40 & 9.78 & 9.83955526430169 & 9.79916666666666 & 1.00412163595221 & 0.993947362182338 \tabularnewline
41 & 9.77 & 9.81576312686774 & 9.81125 & 1.00045999509418 & 0.995337792255553 \tabularnewline
42 & 9.79 & 9.83142797913608 & 9.82708333333333 & 1.00044210938845 & 0.995786168680277 \tabularnewline
43 & 9.81 & 9.8315222950584 & 9.84291666666666 & 0.998842378535333 & 0.997810888851951 \tabularnewline
44 & 9.82 & 9.85947688283246 & 9.8625 & 0.999693473544483 & 0.995996046919974 \tabularnewline
45 & 9.84 & 9.86372669858084 & 9.88666666666666 & 0.997679706532115 & 0.997594550284503 \tabularnewline
46 & 9.87 & 9.87049565510604 & 9.91166666666667 & 0.995846207005822 & 0.999949784172613 \tabularnewline
47 & 9.99 & 9.91745589534322 & 9.93666666666667 & 0.998066678498144 & 1.00731478974268 \tabularnewline
48 & 9.99 & 9.95171646129991 & 9.95958333333333 & 0.999210120366472 & 1.00384692820067 \tabularnewline
49 & 9.99 & 9.96288191507546 & 9.97958333333333 & 0.998326441325252 & 1.00272191170745 \tabularnewline
50 & 10.08 & 10.0315650159552 & 10.0016666666667 & 1.00298933670607 & 1.0048282580004 \tabularnewline
51 & 10.06 & 10.0683272184411 & 10.025 & 1.00432191705148 & 0.999172929299934 \tabularnewline
52 & 10.08 & 10.0872386011699 & 10.0458333333333 & 1.00412163595221 & 0.999282400123949 \tabularnewline
53 & 10.07 & 10.0662949839726 & 10.0616666666667 & 1.00045999509418 & 1.00036806153936 \tabularnewline
54 & 10.04 & 10.0790374012097 & 10.0745833333333 & 1.00044210938845 & 0.996126872075597 \tabularnewline
55 & 10.04 & 10.076654862124 & 10.0883333333333 & 0.998842378535333 & 0.996362397777289 \tabularnewline
56 & 10.12 & 10.0989867775358 & 10.1020833333333 & 0.999693473544483 & 1.00208072581211 \tabularnewline
57 & 10.1 & 10.1002599290045 & 10.12375 & 0.997679706532115 & 0.999974265117301 \tabularnewline
58 & 10.11 & 10.111988360305 & 10.1541666666667 & 0.995846207005822 & 0.99980336604097 \tabularnewline
59 & 10.13 & 10.1665567038517 & 10.18625 & 0.998066678498144 & 0.996404219745524 \tabularnewline
60 & 10.16 & 10.213592780346 & 10.2216666666667 & 0.999210120366472 & 0.994752798403214 \tabularnewline
61 & 10.15 & 10.2428292879971 & 10.26 & 0.998326441325252 & 0.990937143889934 \tabularnewline
62 & 10.25 & 10.3249393969417 & 10.2941666666667 & 1.00298933670607 & 0.992741904425717 \tabularnewline
63 & 10.41 & 10.3704607284874 & 10.3258333333333 & 1.00432191705148 & 1.00381268224699 \tabularnewline
64 & 10.46 & 10.4014449964199 & 10.35875 & 1.00412163595221 & 1.00562950663107 \tabularnewline
65 & 10.46 & 10.3964467823537 & 10.3916666666667 & 1.00045999509418 & 1.00611297484389 \tabularnewline
66 & 10.5 & 10.4283584377379 & 10.42375 & 1.00044210938845 & 1.00686987915595 \tabularnewline
67 & 10.5 & NA & NA & 0.998842378535333 & NA \tabularnewline
68 & 10.48 & NA & NA & 0.999693473544483 & NA \tabularnewline
69 & 10.5 & NA & NA & 0.997679706532115 & NA \tabularnewline
70 & 10.5 & NA & NA & 0.995846207005822 & NA \tabularnewline
71 & 10.53 & NA & NA & 0.998066678498144 & NA \tabularnewline
72 & 10.53 & NA & NA & 0.999210120366472 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198024&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]10[/C][C]NA[/C][C]NA[/C][C]0.998326441325252[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.99[/C][C]NA[/C][C]NA[/C][C]1.00298933670607[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9.95[/C][C]NA[/C][C]NA[/C][C]1.00432191705148[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9.96[/C][C]NA[/C][C]NA[/C][C]1.00412163595221[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]9.97[/C][C]NA[/C][C]NA[/C][C]1.00045999509418[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9.95[/C][C]NA[/C][C]NA[/C][C]1.00044210938845[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9.94[/C][C]9.92849324264121[/C][C]9.94[/C][C]0.998842378535333[/C][C]1.00115896310523[/C][/ROW]
[ROW][C]8[/C][C]9.9[/C][C]9.93320427650637[/C][C]9.93625[/C][C]0.999693473544483[/C][C]0.99665724416995[/C][/ROW]
[ROW][C]9[/C][C]9.9[/C][C]9.91236358427428[/C][C]9.93541666666667[/C][C]0.997679706532115[/C][C]0.998752710776883[/C][/ROW]
[ROW][C]10[/C][C]9.92[/C][C]9.89165738700491[/C][C]9.93291666666666[/C][C]0.995846207005822[/C][C]1.00286530475998[/C][/ROW]
[ROW][C]11[/C][C]9.87[/C][C]9.90456420074596[/C][C]9.92375[/C][C]0.998066678498144[/C][C]0.996510275460342[/C][/ROW]
[ROW][C]12[/C][C]9.96[/C][C]9.90467031813265[/C][C]9.9125[/C][C]0.999210120366472[/C][C]1.00558622145818[/C][/ROW]
[ROW][C]13[/C][C]9.94[/C][C]9.88634355457386[/C][C]9.90291666666666[/C][C]0.998326441325252[/C][C]1.00542732964214[/C][/ROW]
[ROW][C]14[/C][C]9.96[/C][C]9.92457948670651[/C][C]9.895[/C][C]1.00298933670607[/C][C]1.00356896867428[/C][/ROW]
[ROW][C]15[/C][C]9.96[/C][C]9.92897755245016[/C][C]9.88625[/C][C]1.00432191705148[/C][C]1.00312443525891[/C][/ROW]
[ROW][C]16[/C][C]9.89[/C][C]9.9106805468483[/C][C]9.87[/C][C]1.00412163595221[/C][C]0.997913307088192[/C][/ROW]
[ROW][C]17[/C][C]9.82[/C][C]9.8561983850028[/C][C]9.85166666666667[/C][C]1.00045999509418[/C][C]0.99632734817332[/C][/ROW]
[ROW][C]18[/C][C]9.83[/C][C]9.83643018968302[/C][C]9.83208333333333[/C][C]1.00044210938845[/C][C]0.999346288281519[/C][/ROW]
[ROW][C]19[/C][C]9.83[/C][C]9.79864373343162[/C][C]9.81[/C][C]0.998842378535333[/C][C]1.00320006190871[/C][/ROW]
[ROW][C]20[/C][C]9.82[/C][C]9.78908180073704[/C][C]9.79208333333333[/C][C]0.999693473544483[/C][C]1.00315843711314[/C][/ROW]
[ROW][C]21[/C][C]9.77[/C][C]9.75439763074003[/C][C]9.77708333333333[/C][C]0.997679706532115[/C][C]1.00159952155434[/C][/ROW]
[ROW][C]22[/C][C]9.66[/C][C]9.72609795509019[/C][C]9.76666666666667[/C][C]0.995846207005822[/C][C]0.993204062369575[/C][/ROW]
[ROW][C]23[/C][C]9.69[/C][C]9.74237836549001[/C][C]9.76125[/C][C]0.998066678498144[/C][C]0.994623657229784[/C][/ROW]
[ROW][C]24[/C][C]9.67[/C][C]9.7493764119257[/C][C]9.75708333333333[/C][C]0.999210120366472[/C][C]0.991858308821823[/C][/ROW]
[ROW][C]25[/C][C]9.7[/C][C]9.73617861902452[/C][C]9.7525[/C][C]0.998326441325252[/C][C]0.996284104838234[/C][/ROW]
[ROW][C]26[/C][C]9.77[/C][C]9.77789229621325[/C][C]9.74875[/C][C]1.00298933670607[/C][C]0.999192842795343[/C][/ROW]
[ROW][C]27[/C][C]9.79[/C][C]9.78962788645927[/C][C]9.7475[/C][C]1.00432191705148[/C][C]1.0000380109995[/C][/ROW]
[ROW][C]28[/C][C]9.81[/C][C]9.79227787060894[/C][C]9.75208333333333[/C][C]1.00412163595221[/C][C]1.00180980662776[/C][/ROW]
[ROW][C]29[/C][C]9.77[/C][C]9.76574012711304[/C][C]9.76125[/C][C]1.00045999509418[/C][C]1.00043620584119[/C][/ROW]
[ROW][C]30[/C][C]9.78[/C][C]9.77556996136189[/C][C]9.77125[/C][C]1.00044210938845[/C][C]1.00045317445997[/C][/ROW]
[ROW][C]31[/C][C]9.77[/C][C]9.76951083072434[/C][C]9.78083333333333[/C][C]0.998842378535333[/C][C]1.00005007101012[/C][/ROW]
[ROW][C]32[/C][C]9.79[/C][C]9.7832502554747[/C][C]9.78625[/C][C]0.999693473544483[/C][C]1.00068992863814[/C][/ROW]
[ROW][C]33[/C][C]9.77[/C][C]9.76354302804991[/C][C]9.78625[/C][C]0.997679706532115[/C][C]1.00066133492028[/C][/ROW]
[ROW][C]34[/C][C]9.77[/C][C]9.74311032779321[/C][C]9.78375[/C][C]0.995846207005822[/C][C]1.00275986531016[/C][/ROW]
[ROW][C]35[/C][C]9.8[/C][C]9.76358728240809[/C][C]9.7825[/C][C]0.998066678498144[/C][C]1.00372944047497[/C][/ROW]
[ROW][C]36[/C][C]9.8[/C][C]9.77518934003517[/C][C]9.78291666666667[/C][C]0.999210120366472[/C][C]1.00253812576941[/C][/ROW]
[ROW][C]37[/C][C]9.8[/C][C]9.76862422836759[/C][C]9.785[/C][C]0.998326441325252[/C][C]1.00321189257555[/C][/ROW]
[ROW][C]38[/C][C]9.8[/C][C]9.81717604523424[/C][C]9.78791666666667[/C][C]1.00298933670607[/C][C]0.998250408757559[/C][/ROW]
[ROW][C]39[/C][C]9.76[/C][C]9.83440390526114[/C][C]9.79208333333333[/C][C]1.00432191705148[/C][C]0.992434324847961[/C][/ROW]
[ROW][C]40[/C][C]9.78[/C][C]9.83955526430169[/C][C]9.79916666666666[/C][C]1.00412163595221[/C][C]0.993947362182338[/C][/ROW]
[ROW][C]41[/C][C]9.77[/C][C]9.81576312686774[/C][C]9.81125[/C][C]1.00045999509418[/C][C]0.995337792255553[/C][/ROW]
[ROW][C]42[/C][C]9.79[/C][C]9.83142797913608[/C][C]9.82708333333333[/C][C]1.00044210938845[/C][C]0.995786168680277[/C][/ROW]
[ROW][C]43[/C][C]9.81[/C][C]9.8315222950584[/C][C]9.84291666666666[/C][C]0.998842378535333[/C][C]0.997810888851951[/C][/ROW]
[ROW][C]44[/C][C]9.82[/C][C]9.85947688283246[/C][C]9.8625[/C][C]0.999693473544483[/C][C]0.995996046919974[/C][/ROW]
[ROW][C]45[/C][C]9.84[/C][C]9.86372669858084[/C][C]9.88666666666666[/C][C]0.997679706532115[/C][C]0.997594550284503[/C][/ROW]
[ROW][C]46[/C][C]9.87[/C][C]9.87049565510604[/C][C]9.91166666666667[/C][C]0.995846207005822[/C][C]0.999949784172613[/C][/ROW]
[ROW][C]47[/C][C]9.99[/C][C]9.91745589534322[/C][C]9.93666666666667[/C][C]0.998066678498144[/C][C]1.00731478974268[/C][/ROW]
[ROW][C]48[/C][C]9.99[/C][C]9.95171646129991[/C][C]9.95958333333333[/C][C]0.999210120366472[/C][C]1.00384692820067[/C][/ROW]
[ROW][C]49[/C][C]9.99[/C][C]9.96288191507546[/C][C]9.97958333333333[/C][C]0.998326441325252[/C][C]1.00272191170745[/C][/ROW]
[ROW][C]50[/C][C]10.08[/C][C]10.0315650159552[/C][C]10.0016666666667[/C][C]1.00298933670607[/C][C]1.0048282580004[/C][/ROW]
[ROW][C]51[/C][C]10.06[/C][C]10.0683272184411[/C][C]10.025[/C][C]1.00432191705148[/C][C]0.999172929299934[/C][/ROW]
[ROW][C]52[/C][C]10.08[/C][C]10.0872386011699[/C][C]10.0458333333333[/C][C]1.00412163595221[/C][C]0.999282400123949[/C][/ROW]
[ROW][C]53[/C][C]10.07[/C][C]10.0662949839726[/C][C]10.0616666666667[/C][C]1.00045999509418[/C][C]1.00036806153936[/C][/ROW]
[ROW][C]54[/C][C]10.04[/C][C]10.0790374012097[/C][C]10.0745833333333[/C][C]1.00044210938845[/C][C]0.996126872075597[/C][/ROW]
[ROW][C]55[/C][C]10.04[/C][C]10.076654862124[/C][C]10.0883333333333[/C][C]0.998842378535333[/C][C]0.996362397777289[/C][/ROW]
[ROW][C]56[/C][C]10.12[/C][C]10.0989867775358[/C][C]10.1020833333333[/C][C]0.999693473544483[/C][C]1.00208072581211[/C][/ROW]
[ROW][C]57[/C][C]10.1[/C][C]10.1002599290045[/C][C]10.12375[/C][C]0.997679706532115[/C][C]0.999974265117301[/C][/ROW]
[ROW][C]58[/C][C]10.11[/C][C]10.111988360305[/C][C]10.1541666666667[/C][C]0.995846207005822[/C][C]0.99980336604097[/C][/ROW]
[ROW][C]59[/C][C]10.13[/C][C]10.1665567038517[/C][C]10.18625[/C][C]0.998066678498144[/C][C]0.996404219745524[/C][/ROW]
[ROW][C]60[/C][C]10.16[/C][C]10.213592780346[/C][C]10.2216666666667[/C][C]0.999210120366472[/C][C]0.994752798403214[/C][/ROW]
[ROW][C]61[/C][C]10.15[/C][C]10.2428292879971[/C][C]10.26[/C][C]0.998326441325252[/C][C]0.990937143889934[/C][/ROW]
[ROW][C]62[/C][C]10.25[/C][C]10.3249393969417[/C][C]10.2941666666667[/C][C]1.00298933670607[/C][C]0.992741904425717[/C][/ROW]
[ROW][C]63[/C][C]10.41[/C][C]10.3704607284874[/C][C]10.3258333333333[/C][C]1.00432191705148[/C][C]1.00381268224699[/C][/ROW]
[ROW][C]64[/C][C]10.46[/C][C]10.4014449964199[/C][C]10.35875[/C][C]1.00412163595221[/C][C]1.00562950663107[/C][/ROW]
[ROW][C]65[/C][C]10.46[/C][C]10.3964467823537[/C][C]10.3916666666667[/C][C]1.00045999509418[/C][C]1.00611297484389[/C][/ROW]
[ROW][C]66[/C][C]10.5[/C][C]10.4283584377379[/C][C]10.42375[/C][C]1.00044210938845[/C][C]1.00686987915595[/C][/ROW]
[ROW][C]67[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.998842378535333[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]10.48[/C][C]NA[/C][C]NA[/C][C]0.999693473544483[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.997679706532115[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.995846207005822[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]10.53[/C][C]NA[/C][C]NA[/C][C]0.998066678498144[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10.53[/C][C]NA[/C][C]NA[/C][C]0.999210120366472[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198024&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198024&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
110NANA0.998326441325252NA
29.99NANA1.00298933670607NA
39.95NANA1.00432191705148NA
49.96NANA1.00412163595221NA
59.97NANA1.00045999509418NA
69.95NANA1.00044210938845NA
79.949.928493242641219.940.9988423785353331.00115896310523
89.99.933204276506379.936250.9996934735444830.99665724416995
99.99.912363584274289.935416666666670.9976797065321150.998752710776883
109.929.891657387004919.932916666666660.9958462070058221.00286530475998
119.879.904564200745969.923750.9980666784981440.996510275460342
129.969.904670318132659.91250.9992101203664721.00558622145818
139.949.886343554573869.902916666666660.9983264413252521.00542732964214
149.969.924579486706519.8951.002989336706071.00356896867428
159.969.928977552450169.886251.004321917051481.00312443525891
169.899.91068054684839.871.004121635952210.997913307088192
179.829.85619838500289.851666666666671.000459995094180.99632734817332
189.839.836430189683029.832083333333331.000442109388450.999346288281519
199.839.798643733431629.810.9988423785353331.00320006190871
209.829.789081800737049.792083333333330.9996934735444831.00315843711314
219.779.754397630740039.777083333333330.9976797065321151.00159952155434
229.669.726097955090199.766666666666670.9958462070058220.993204062369575
239.699.742378365490019.761250.9980666784981440.994623657229784
249.679.74937641192579.757083333333330.9992101203664720.991858308821823
259.79.736178619024529.75250.9983264413252520.996284104838234
269.779.777892296213259.748751.002989336706070.999192842795343
279.799.789627886459279.74751.004321917051481.0000380109995
289.819.792277870608949.752083333333331.004121635952211.00180980662776
299.779.765740127113049.761251.000459995094181.00043620584119
309.789.775569961361899.771251.000442109388451.00045317445997
319.779.769510830724349.780833333333330.9988423785353331.00005007101012
329.799.78325025547479.786250.9996934735444831.00068992863814
339.779.763543028049919.786250.9976797065321151.00066133492028
349.779.743110327793219.783750.9958462070058221.00275986531016
359.89.763587282408099.78250.9980666784981441.00372944047497
369.89.775189340035179.782916666666670.9992101203664721.00253812576941
379.89.768624228367599.7850.9983264413252521.00321189257555
389.89.817176045234249.787916666666671.002989336706070.998250408757559
399.769.834403905261149.792083333333331.004321917051480.992434324847961
409.789.839555264301699.799166666666661.004121635952210.993947362182338
419.779.815763126867749.811251.000459995094180.995337792255553
429.799.831427979136089.827083333333331.000442109388450.995786168680277
439.819.83152229505849.842916666666660.9988423785353330.997810888851951
449.829.859476882832469.86250.9996934735444830.995996046919974
459.849.863726698580849.886666666666660.9976797065321150.997594550284503
469.879.870495655106049.911666666666670.9958462070058220.999949784172613
479.999.917455895343229.936666666666670.9980666784981441.00731478974268
489.999.951716461299919.959583333333330.9992101203664721.00384692820067
499.999.962881915075469.979583333333330.9983264413252521.00272191170745
5010.0810.031565015955210.00166666666671.002989336706071.0048282580004
5110.0610.068327218441110.0251.004321917051480.999172929299934
5210.0810.087238601169910.04583333333331.004121635952210.999282400123949
5310.0710.066294983972610.06166666666671.000459995094181.00036806153936
5410.0410.079037401209710.07458333333331.000442109388450.996126872075597
5510.0410.07665486212410.08833333333330.9988423785353330.996362397777289
5610.1210.098986777535810.10208333333330.9996934735444831.00208072581211
5710.110.100259929004510.123750.9976797065321150.999974265117301
5810.1110.11198836030510.15416666666670.9958462070058220.99980336604097
5910.1310.166556703851710.186250.9980666784981440.996404219745524
6010.1610.21359278034610.22166666666670.9992101203664720.994752798403214
6110.1510.242829287997110.260.9983264413252520.990937143889934
6210.2510.324939396941710.29416666666671.002989336706070.992741904425717
6310.4110.370460728487410.32583333333331.004321917051481.00381268224699
6410.4610.401444996419910.358751.004121635952211.00562950663107
6510.4610.396446782353710.39166666666671.000459995094181.00611297484389
6610.510.428358437737910.423751.000442109388451.00686987915595
6710.5NANA0.998842378535333NA
6810.48NANA0.999693473544483NA
6910.5NANA0.997679706532115NA
7010.5NANA0.995846207005822NA
7110.53NANA0.998066678498144NA
7210.53NANA0.999210120366472NA



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')