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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 01 Jun 2010 17:09:04 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/01/t1275412442qgg0rey9fim2le7.htm/, Retrieved Sat, 27 Apr 2024 10:38:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76832, Retrieved Sat, 27 Apr 2024 10:38:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W52
Estimated Impact186
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Decompositie Gemi...] [2010-06-01 17:09:04] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0,47
0,47
0,47
0,47
0,47
0,47
0,47
0,47
0,47
0,47
0,47
0,46
0,46
0,46
0,45
0,45
0,46
0,46
0,46
0,46
0,46
0,44
0,44
0,43
0,44
0,44
0,44
0,44
0,44
0,44
0,44
0,44
0,44
0,44
0,44
0,43
0,43
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,42
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41
0,41




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 12 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76832&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76832&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 time12 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
10.47NANA0.999435206936909NA
20.47NANA0.99704990791683NA
30.47NANA0.994995496957232NA
40.47NANA0.992442453680009NA
50.47NANA0.999080931115287NA
60.47NANA1.00118196391945NA
70.470.4704552126592010.468751.003637787006290.99903239958459
80.470.4706885808123610.4679166666666671.005923948307810.998537077718834
90.470.4704959930438490.4666666666666671.008205699379680.998945808144635
100.470.4657231895802920.4651.001555246409231.00918315968668
110.470.4655259450442970.463751.003829531092821.00961075317784
120.460.4595197042109820.4629166666666670.992661827278451.0010452126092
130.460.4618223518720970.4620833333333330.9994352069369090.996053998112674
140.460.4598892700266380.461250.997049907916831.00024077529218
150.450.4581125100573920.4604166666666670.9949954969572320.982291446141963
160.450.4552829756257040.458750.9924424536800090.988396281195352
170.460.455830674821350.456250.9990809311152871.00914665337142
180.460.4542863161284510.453751.001181963919451.01257727487863
190.460.4533097337978430.4516666666666671.003637787006291.01475870845769
200.460.4526657767385130.451.005923948307811.01620229237194
210.460.452432307596630.448751.008205699379681.01672668435986
220.440.4486132874541350.4479166666666671.001555246409230.98080019541326
230.440.4483771905547950.4466666666666671.003829531092820.981316644264554
240.430.441734513138910.4450.992661827278450.973435371722426
250.440.443082941742030.4433333333333330.9994352069369090.99304206627791
260.440.4403637093299340.4416666666666670.997049907916830.999174070609753
270.440.4377980186611820.440.9949954969572321.00502967406192
280.440.4358476442411370.4391666666666670.9924424536800091.00952708088188
290.440.438763042248130.4391666666666670.9990809311152871.00281919312422
300.440.4396857458212930.4391666666666671.001181963919451.0007147245088
310.440.4403460790490120.438751.003637787006290.99921407487093
320.440.4400917273846650.43751.005923948307810.999791572122452
330.440.4394096506463090.4358333333333331.008205699379681.00134350566225
340.440.4348419028160080.4341666666666671.001555246409231.01186200582462
350.440.4341562721976470.43251.003829531092821.01345996401888
360.430.4276718039191320.4308333333333330.992661827278451.00544388491253
370.430.4289242763104230.4291666666666670.9994352069369091.00250795711269
380.420.4262388356344450.42750.997049907916830.985363052089895
390.420.4237022491209540.4258333333333330.9949954969572320.991262144280245
400.420.4209610074359370.4241666666666670.9924424536800090.997717110566153
410.420.4221116933962090.42250.9990809311152870.99499731130588
420.420.4217479023010690.421251.001181963919450.995855575590223
430.420.4219460529538960.4204166666666671.003637787006290.995387910515402
440.420.4224880582892790.421.005923948307810.994110938189938
450.420.4234463937394640.421.008205699379680.991861086101056
460.420.4202358888058730.4195833333333331.001555246409230.999438675248458
470.420.420353616145120.418751.003829531092820.999158765069365
480.420.4148499219834520.4179166666666670.992661827278451.01241431598185
490.420.4168477675599360.4170833333333330.9994352069369091.00756207106138
500.420.4150220241703810.416250.997049907916831.01199448593016
510.420.4133377126943170.4154166666666670.9949954969572321.01611826625317
520.410.411450100588170.4145833333333330.9924424536800090.996475634381673
530.410.413369735248950.413750.9990809311152870.991848132648317
540.410.4134047192684070.4129166666666671.001181963919450.9917641983516
550.410.4135824047288440.4120833333333331.003637787006290.991338111370592
560.410.4136862237415850.411251.005923948307810.991089324396047
570.410.4137844224537420.4104166666666671.008205699379680.99085412053141
580.410.4106376510277850.411.001555246409230.998447168626187
590.410.4115701077480580.411.003829531092820.996185078268563
600.410.4069913491841650.410.992661827278451.00739241957321
610.410.4097684348441330.410.9994352069369091.00056511223456
620.410.4087904622459010.410.997049907916831.00295882087721
630.410.4079481537524650.410.9949954969572321.00502967406192
640.410.4069014060088040.410.9924424536800091.00761509777415
650.410.4096231817572680.410.9990809311152871.00091991434937
660.410.4104846052069750.411.001181963919450.998819431469955
670.41NANA1.00363778700629NA
680.41NANA1.00592394830781NA
690.41NANA1.00820569937968NA
700.41NANA1.00155524640923NA
710.41NANA1.00382953109282NA
720.41NANA0.99266182727845NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.47 & NA & NA & 0.999435206936909 & NA \tabularnewline
2 & 0.47 & NA & NA & 0.99704990791683 & NA \tabularnewline
3 & 0.47 & NA & NA & 0.994995496957232 & NA \tabularnewline
4 & 0.47 & NA & NA & 0.992442453680009 & NA \tabularnewline
5 & 0.47 & NA & NA & 0.999080931115287 & NA \tabularnewline
6 & 0.47 & NA & NA & 1.00118196391945 & NA \tabularnewline
7 & 0.47 & 0.470455212659201 & 0.46875 & 1.00363778700629 & 0.99903239958459 \tabularnewline
8 & 0.47 & 0.470688580812361 & 0.467916666666667 & 1.00592394830781 & 0.998537077718834 \tabularnewline
9 & 0.47 & 0.470495993043849 & 0.466666666666667 & 1.00820569937968 & 0.998945808144635 \tabularnewline
10 & 0.47 & 0.465723189580292 & 0.465 & 1.00155524640923 & 1.00918315968668 \tabularnewline
11 & 0.47 & 0.465525945044297 & 0.46375 & 1.00382953109282 & 1.00961075317784 \tabularnewline
12 & 0.46 & 0.459519704210982 & 0.462916666666667 & 0.99266182727845 & 1.0010452126092 \tabularnewline
13 & 0.46 & 0.461822351872097 & 0.462083333333333 & 0.999435206936909 & 0.996053998112674 \tabularnewline
14 & 0.46 & 0.459889270026638 & 0.46125 & 0.99704990791683 & 1.00024077529218 \tabularnewline
15 & 0.45 & 0.458112510057392 & 0.460416666666667 & 0.994995496957232 & 0.982291446141963 \tabularnewline
16 & 0.45 & 0.455282975625704 & 0.45875 & 0.992442453680009 & 0.988396281195352 \tabularnewline
17 & 0.46 & 0.45583067482135 & 0.45625 & 0.999080931115287 & 1.00914665337142 \tabularnewline
18 & 0.46 & 0.454286316128451 & 0.45375 & 1.00118196391945 & 1.01257727487863 \tabularnewline
19 & 0.46 & 0.453309733797843 & 0.451666666666667 & 1.00363778700629 & 1.01475870845769 \tabularnewline
20 & 0.46 & 0.452665776738513 & 0.45 & 1.00592394830781 & 1.01620229237194 \tabularnewline
21 & 0.46 & 0.45243230759663 & 0.44875 & 1.00820569937968 & 1.01672668435986 \tabularnewline
22 & 0.44 & 0.448613287454135 & 0.447916666666667 & 1.00155524640923 & 0.98080019541326 \tabularnewline
23 & 0.44 & 0.448377190554795 & 0.446666666666667 & 1.00382953109282 & 0.981316644264554 \tabularnewline
24 & 0.43 & 0.44173451313891 & 0.445 & 0.99266182727845 & 0.973435371722426 \tabularnewline
25 & 0.44 & 0.44308294174203 & 0.443333333333333 & 0.999435206936909 & 0.99304206627791 \tabularnewline
26 & 0.44 & 0.440363709329934 & 0.441666666666667 & 0.99704990791683 & 0.999174070609753 \tabularnewline
27 & 0.44 & 0.437798018661182 & 0.44 & 0.994995496957232 & 1.00502967406192 \tabularnewline
28 & 0.44 & 0.435847644241137 & 0.439166666666667 & 0.992442453680009 & 1.00952708088188 \tabularnewline
29 & 0.44 & 0.43876304224813 & 0.439166666666667 & 0.999080931115287 & 1.00281919312422 \tabularnewline
30 & 0.44 & 0.439685745821293 & 0.439166666666667 & 1.00118196391945 & 1.0007147245088 \tabularnewline
31 & 0.44 & 0.440346079049012 & 0.43875 & 1.00363778700629 & 0.99921407487093 \tabularnewline
32 & 0.44 & 0.440091727384665 & 0.4375 & 1.00592394830781 & 0.999791572122452 \tabularnewline
33 & 0.44 & 0.439409650646309 & 0.435833333333333 & 1.00820569937968 & 1.00134350566225 \tabularnewline
34 & 0.44 & 0.434841902816008 & 0.434166666666667 & 1.00155524640923 & 1.01186200582462 \tabularnewline
35 & 0.44 & 0.434156272197647 & 0.4325 & 1.00382953109282 & 1.01345996401888 \tabularnewline
36 & 0.43 & 0.427671803919132 & 0.430833333333333 & 0.99266182727845 & 1.00544388491253 \tabularnewline
37 & 0.43 & 0.428924276310423 & 0.429166666666667 & 0.999435206936909 & 1.00250795711269 \tabularnewline
38 & 0.42 & 0.426238835634445 & 0.4275 & 0.99704990791683 & 0.985363052089895 \tabularnewline
39 & 0.42 & 0.423702249120954 & 0.425833333333333 & 0.994995496957232 & 0.991262144280245 \tabularnewline
40 & 0.42 & 0.420961007435937 & 0.424166666666667 & 0.992442453680009 & 0.997717110566153 \tabularnewline
41 & 0.42 & 0.422111693396209 & 0.4225 & 0.999080931115287 & 0.99499731130588 \tabularnewline
42 & 0.42 & 0.421747902301069 & 0.42125 & 1.00118196391945 & 0.995855575590223 \tabularnewline
43 & 0.42 & 0.421946052953896 & 0.420416666666667 & 1.00363778700629 & 0.995387910515402 \tabularnewline
44 & 0.42 & 0.422488058289279 & 0.42 & 1.00592394830781 & 0.994110938189938 \tabularnewline
45 & 0.42 & 0.423446393739464 & 0.42 & 1.00820569937968 & 0.991861086101056 \tabularnewline
46 & 0.42 & 0.420235888805873 & 0.419583333333333 & 1.00155524640923 & 0.999438675248458 \tabularnewline
47 & 0.42 & 0.42035361614512 & 0.41875 & 1.00382953109282 & 0.999158765069365 \tabularnewline
48 & 0.42 & 0.414849921983452 & 0.417916666666667 & 0.99266182727845 & 1.01241431598185 \tabularnewline
49 & 0.42 & 0.416847767559936 & 0.417083333333333 & 0.999435206936909 & 1.00756207106138 \tabularnewline
50 & 0.42 & 0.415022024170381 & 0.41625 & 0.99704990791683 & 1.01199448593016 \tabularnewline
51 & 0.42 & 0.413337712694317 & 0.415416666666667 & 0.994995496957232 & 1.01611826625317 \tabularnewline
52 & 0.41 & 0.41145010058817 & 0.414583333333333 & 0.992442453680009 & 0.996475634381673 \tabularnewline
53 & 0.41 & 0.41336973524895 & 0.41375 & 0.999080931115287 & 0.991848132648317 \tabularnewline
54 & 0.41 & 0.413404719268407 & 0.412916666666667 & 1.00118196391945 & 0.9917641983516 \tabularnewline
55 & 0.41 & 0.413582404728844 & 0.412083333333333 & 1.00363778700629 & 0.991338111370592 \tabularnewline
56 & 0.41 & 0.413686223741585 & 0.41125 & 1.00592394830781 & 0.991089324396047 \tabularnewline
57 & 0.41 & 0.413784422453742 & 0.410416666666667 & 1.00820569937968 & 0.99085412053141 \tabularnewline
58 & 0.41 & 0.410637651027785 & 0.41 & 1.00155524640923 & 0.998447168626187 \tabularnewline
59 & 0.41 & 0.411570107748058 & 0.41 & 1.00382953109282 & 0.996185078268563 \tabularnewline
60 & 0.41 & 0.406991349184165 & 0.41 & 0.99266182727845 & 1.00739241957321 \tabularnewline
61 & 0.41 & 0.409768434844133 & 0.41 & 0.999435206936909 & 1.00056511223456 \tabularnewline
62 & 0.41 & 0.408790462245901 & 0.41 & 0.99704990791683 & 1.00295882087721 \tabularnewline
63 & 0.41 & 0.407948153752465 & 0.41 & 0.994995496957232 & 1.00502967406192 \tabularnewline
64 & 0.41 & 0.406901406008804 & 0.41 & 0.992442453680009 & 1.00761509777415 \tabularnewline
65 & 0.41 & 0.409623181757268 & 0.41 & 0.999080931115287 & 1.00091991434937 \tabularnewline
66 & 0.41 & 0.410484605206975 & 0.41 & 1.00118196391945 & 0.998819431469955 \tabularnewline
67 & 0.41 & NA & NA & 1.00363778700629 & NA \tabularnewline
68 & 0.41 & NA & NA & 1.00592394830781 & NA \tabularnewline
69 & 0.41 & NA & NA & 1.00820569937968 & NA \tabularnewline
70 & 0.41 & NA & NA & 1.00155524640923 & NA \tabularnewline
71 & 0.41 & NA & NA & 1.00382953109282 & NA \tabularnewline
72 & 0.41 & NA & NA & 0.99266182727845 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76832&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]0.47[/C][C]NA[/C][C]NA[/C][C]0.999435206936909[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.47[/C][C]NA[/C][C]NA[/C][C]0.99704990791683[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.47[/C][C]NA[/C][C]NA[/C][C]0.994995496957232[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.47[/C][C]NA[/C][C]NA[/C][C]0.992442453680009[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.47[/C][C]NA[/C][C]NA[/C][C]0.999080931115287[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.47[/C][C]NA[/C][C]NA[/C][C]1.00118196391945[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.47[/C][C]0.470455212659201[/C][C]0.46875[/C][C]1.00363778700629[/C][C]0.99903239958459[/C][/ROW]
[ROW][C]8[/C][C]0.47[/C][C]0.470688580812361[/C][C]0.467916666666667[/C][C]1.00592394830781[/C][C]0.998537077718834[/C][/ROW]
[ROW][C]9[/C][C]0.47[/C][C]0.470495993043849[/C][C]0.466666666666667[/C][C]1.00820569937968[/C][C]0.998945808144635[/C][/ROW]
[ROW][C]10[/C][C]0.47[/C][C]0.465723189580292[/C][C]0.465[/C][C]1.00155524640923[/C][C]1.00918315968668[/C][/ROW]
[ROW][C]11[/C][C]0.47[/C][C]0.465525945044297[/C][C]0.46375[/C][C]1.00382953109282[/C][C]1.00961075317784[/C][/ROW]
[ROW][C]12[/C][C]0.46[/C][C]0.459519704210982[/C][C]0.462916666666667[/C][C]0.99266182727845[/C][C]1.0010452126092[/C][/ROW]
[ROW][C]13[/C][C]0.46[/C][C]0.461822351872097[/C][C]0.462083333333333[/C][C]0.999435206936909[/C][C]0.996053998112674[/C][/ROW]
[ROW][C]14[/C][C]0.46[/C][C]0.459889270026638[/C][C]0.46125[/C][C]0.99704990791683[/C][C]1.00024077529218[/C][/ROW]
[ROW][C]15[/C][C]0.45[/C][C]0.458112510057392[/C][C]0.460416666666667[/C][C]0.994995496957232[/C][C]0.982291446141963[/C][/ROW]
[ROW][C]16[/C][C]0.45[/C][C]0.455282975625704[/C][C]0.45875[/C][C]0.992442453680009[/C][C]0.988396281195352[/C][/ROW]
[ROW][C]17[/C][C]0.46[/C][C]0.45583067482135[/C][C]0.45625[/C][C]0.999080931115287[/C][C]1.00914665337142[/C][/ROW]
[ROW][C]18[/C][C]0.46[/C][C]0.454286316128451[/C][C]0.45375[/C][C]1.00118196391945[/C][C]1.01257727487863[/C][/ROW]
[ROW][C]19[/C][C]0.46[/C][C]0.453309733797843[/C][C]0.451666666666667[/C][C]1.00363778700629[/C][C]1.01475870845769[/C][/ROW]
[ROW][C]20[/C][C]0.46[/C][C]0.452665776738513[/C][C]0.45[/C][C]1.00592394830781[/C][C]1.01620229237194[/C][/ROW]
[ROW][C]21[/C][C]0.46[/C][C]0.45243230759663[/C][C]0.44875[/C][C]1.00820569937968[/C][C]1.01672668435986[/C][/ROW]
[ROW][C]22[/C][C]0.44[/C][C]0.448613287454135[/C][C]0.447916666666667[/C][C]1.00155524640923[/C][C]0.98080019541326[/C][/ROW]
[ROW][C]23[/C][C]0.44[/C][C]0.448377190554795[/C][C]0.446666666666667[/C][C]1.00382953109282[/C][C]0.981316644264554[/C][/ROW]
[ROW][C]24[/C][C]0.43[/C][C]0.44173451313891[/C][C]0.445[/C][C]0.99266182727845[/C][C]0.973435371722426[/C][/ROW]
[ROW][C]25[/C][C]0.44[/C][C]0.44308294174203[/C][C]0.443333333333333[/C][C]0.999435206936909[/C][C]0.99304206627791[/C][/ROW]
[ROW][C]26[/C][C]0.44[/C][C]0.440363709329934[/C][C]0.441666666666667[/C][C]0.99704990791683[/C][C]0.999174070609753[/C][/ROW]
[ROW][C]27[/C][C]0.44[/C][C]0.437798018661182[/C][C]0.44[/C][C]0.994995496957232[/C][C]1.00502967406192[/C][/ROW]
[ROW][C]28[/C][C]0.44[/C][C]0.435847644241137[/C][C]0.439166666666667[/C][C]0.992442453680009[/C][C]1.00952708088188[/C][/ROW]
[ROW][C]29[/C][C]0.44[/C][C]0.43876304224813[/C][C]0.439166666666667[/C][C]0.999080931115287[/C][C]1.00281919312422[/C][/ROW]
[ROW][C]30[/C][C]0.44[/C][C]0.439685745821293[/C][C]0.439166666666667[/C][C]1.00118196391945[/C][C]1.0007147245088[/C][/ROW]
[ROW][C]31[/C][C]0.44[/C][C]0.440346079049012[/C][C]0.43875[/C][C]1.00363778700629[/C][C]0.99921407487093[/C][/ROW]
[ROW][C]32[/C][C]0.44[/C][C]0.440091727384665[/C][C]0.4375[/C][C]1.00592394830781[/C][C]0.999791572122452[/C][/ROW]
[ROW][C]33[/C][C]0.44[/C][C]0.439409650646309[/C][C]0.435833333333333[/C][C]1.00820569937968[/C][C]1.00134350566225[/C][/ROW]
[ROW][C]34[/C][C]0.44[/C][C]0.434841902816008[/C][C]0.434166666666667[/C][C]1.00155524640923[/C][C]1.01186200582462[/C][/ROW]
[ROW][C]35[/C][C]0.44[/C][C]0.434156272197647[/C][C]0.4325[/C][C]1.00382953109282[/C][C]1.01345996401888[/C][/ROW]
[ROW][C]36[/C][C]0.43[/C][C]0.427671803919132[/C][C]0.430833333333333[/C][C]0.99266182727845[/C][C]1.00544388491253[/C][/ROW]
[ROW][C]37[/C][C]0.43[/C][C]0.428924276310423[/C][C]0.429166666666667[/C][C]0.999435206936909[/C][C]1.00250795711269[/C][/ROW]
[ROW][C]38[/C][C]0.42[/C][C]0.426238835634445[/C][C]0.4275[/C][C]0.99704990791683[/C][C]0.985363052089895[/C][/ROW]
[ROW][C]39[/C][C]0.42[/C][C]0.423702249120954[/C][C]0.425833333333333[/C][C]0.994995496957232[/C][C]0.991262144280245[/C][/ROW]
[ROW][C]40[/C][C]0.42[/C][C]0.420961007435937[/C][C]0.424166666666667[/C][C]0.992442453680009[/C][C]0.997717110566153[/C][/ROW]
[ROW][C]41[/C][C]0.42[/C][C]0.422111693396209[/C][C]0.4225[/C][C]0.999080931115287[/C][C]0.99499731130588[/C][/ROW]
[ROW][C]42[/C][C]0.42[/C][C]0.421747902301069[/C][C]0.42125[/C][C]1.00118196391945[/C][C]0.995855575590223[/C][/ROW]
[ROW][C]43[/C][C]0.42[/C][C]0.421946052953896[/C][C]0.420416666666667[/C][C]1.00363778700629[/C][C]0.995387910515402[/C][/ROW]
[ROW][C]44[/C][C]0.42[/C][C]0.422488058289279[/C][C]0.42[/C][C]1.00592394830781[/C][C]0.994110938189938[/C][/ROW]
[ROW][C]45[/C][C]0.42[/C][C]0.423446393739464[/C][C]0.42[/C][C]1.00820569937968[/C][C]0.991861086101056[/C][/ROW]
[ROW][C]46[/C][C]0.42[/C][C]0.420235888805873[/C][C]0.419583333333333[/C][C]1.00155524640923[/C][C]0.999438675248458[/C][/ROW]
[ROW][C]47[/C][C]0.42[/C][C]0.42035361614512[/C][C]0.41875[/C][C]1.00382953109282[/C][C]0.999158765069365[/C][/ROW]
[ROW][C]48[/C][C]0.42[/C][C]0.414849921983452[/C][C]0.417916666666667[/C][C]0.99266182727845[/C][C]1.01241431598185[/C][/ROW]
[ROW][C]49[/C][C]0.42[/C][C]0.416847767559936[/C][C]0.417083333333333[/C][C]0.999435206936909[/C][C]1.00756207106138[/C][/ROW]
[ROW][C]50[/C][C]0.42[/C][C]0.415022024170381[/C][C]0.41625[/C][C]0.99704990791683[/C][C]1.01199448593016[/C][/ROW]
[ROW][C]51[/C][C]0.42[/C][C]0.413337712694317[/C][C]0.415416666666667[/C][C]0.994995496957232[/C][C]1.01611826625317[/C][/ROW]
[ROW][C]52[/C][C]0.41[/C][C]0.41145010058817[/C][C]0.414583333333333[/C][C]0.992442453680009[/C][C]0.996475634381673[/C][/ROW]
[ROW][C]53[/C][C]0.41[/C][C]0.41336973524895[/C][C]0.41375[/C][C]0.999080931115287[/C][C]0.991848132648317[/C][/ROW]
[ROW][C]54[/C][C]0.41[/C][C]0.413404719268407[/C][C]0.412916666666667[/C][C]1.00118196391945[/C][C]0.9917641983516[/C][/ROW]
[ROW][C]55[/C][C]0.41[/C][C]0.413582404728844[/C][C]0.412083333333333[/C][C]1.00363778700629[/C][C]0.991338111370592[/C][/ROW]
[ROW][C]56[/C][C]0.41[/C][C]0.413686223741585[/C][C]0.41125[/C][C]1.00592394830781[/C][C]0.991089324396047[/C][/ROW]
[ROW][C]57[/C][C]0.41[/C][C]0.413784422453742[/C][C]0.410416666666667[/C][C]1.00820569937968[/C][C]0.99085412053141[/C][/ROW]
[ROW][C]58[/C][C]0.41[/C][C]0.410637651027785[/C][C]0.41[/C][C]1.00155524640923[/C][C]0.998447168626187[/C][/ROW]
[ROW][C]59[/C][C]0.41[/C][C]0.411570107748058[/C][C]0.41[/C][C]1.00382953109282[/C][C]0.996185078268563[/C][/ROW]
[ROW][C]60[/C][C]0.41[/C][C]0.406991349184165[/C][C]0.41[/C][C]0.99266182727845[/C][C]1.00739241957321[/C][/ROW]
[ROW][C]61[/C][C]0.41[/C][C]0.409768434844133[/C][C]0.41[/C][C]0.999435206936909[/C][C]1.00056511223456[/C][/ROW]
[ROW][C]62[/C][C]0.41[/C][C]0.408790462245901[/C][C]0.41[/C][C]0.99704990791683[/C][C]1.00295882087721[/C][/ROW]
[ROW][C]63[/C][C]0.41[/C][C]0.407948153752465[/C][C]0.41[/C][C]0.994995496957232[/C][C]1.00502967406192[/C][/ROW]
[ROW][C]64[/C][C]0.41[/C][C]0.406901406008804[/C][C]0.41[/C][C]0.992442453680009[/C][C]1.00761509777415[/C][/ROW]
[ROW][C]65[/C][C]0.41[/C][C]0.409623181757268[/C][C]0.41[/C][C]0.999080931115287[/C][C]1.00091991434937[/C][/ROW]
[ROW][C]66[/C][C]0.41[/C][C]0.410484605206975[/C][C]0.41[/C][C]1.00118196391945[/C][C]0.998819431469955[/C][/ROW]
[ROW][C]67[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]1.00363778700629[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]1.00592394830781[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]1.00820569937968[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]1.00155524640923[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]1.00382953109282[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]0.41[/C][C]NA[/C][C]NA[/C][C]0.99266182727845[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76832&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76832&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
10.47NANA0.999435206936909NA
20.47NANA0.99704990791683NA
30.47NANA0.994995496957232NA
40.47NANA0.992442453680009NA
50.47NANA0.999080931115287NA
60.47NANA1.00118196391945NA
70.470.4704552126592010.468751.003637787006290.99903239958459
80.470.4706885808123610.4679166666666671.005923948307810.998537077718834
90.470.4704959930438490.4666666666666671.008205699379680.998945808144635
100.470.4657231895802920.4651.001555246409231.00918315968668
110.470.4655259450442970.463751.003829531092821.00961075317784
120.460.4595197042109820.4629166666666670.992661827278451.0010452126092
130.460.4618223518720970.4620833333333330.9994352069369090.996053998112674
140.460.4598892700266380.461250.997049907916831.00024077529218
150.450.4581125100573920.4604166666666670.9949954969572320.982291446141963
160.450.4552829756257040.458750.9924424536800090.988396281195352
170.460.455830674821350.456250.9990809311152871.00914665337142
180.460.4542863161284510.453751.001181963919451.01257727487863
190.460.4533097337978430.4516666666666671.003637787006291.01475870845769
200.460.4526657767385130.451.005923948307811.01620229237194
210.460.452432307596630.448751.008205699379681.01672668435986
220.440.4486132874541350.4479166666666671.001555246409230.98080019541326
230.440.4483771905547950.4466666666666671.003829531092820.981316644264554
240.430.441734513138910.4450.992661827278450.973435371722426
250.440.443082941742030.4433333333333330.9994352069369090.99304206627791
260.440.4403637093299340.4416666666666670.997049907916830.999174070609753
270.440.4377980186611820.440.9949954969572321.00502967406192
280.440.4358476442411370.4391666666666670.9924424536800091.00952708088188
290.440.438763042248130.4391666666666670.9990809311152871.00281919312422
300.440.4396857458212930.4391666666666671.001181963919451.0007147245088
310.440.4403460790490120.438751.003637787006290.99921407487093
320.440.4400917273846650.43751.005923948307810.999791572122452
330.440.4394096506463090.4358333333333331.008205699379681.00134350566225
340.440.4348419028160080.4341666666666671.001555246409231.01186200582462
350.440.4341562721976470.43251.003829531092821.01345996401888
360.430.4276718039191320.4308333333333330.992661827278451.00544388491253
370.430.4289242763104230.4291666666666670.9994352069369091.00250795711269
380.420.4262388356344450.42750.997049907916830.985363052089895
390.420.4237022491209540.4258333333333330.9949954969572320.991262144280245
400.420.4209610074359370.4241666666666670.9924424536800090.997717110566153
410.420.4221116933962090.42250.9990809311152870.99499731130588
420.420.4217479023010690.421251.001181963919450.995855575590223
430.420.4219460529538960.4204166666666671.003637787006290.995387910515402
440.420.4224880582892790.421.005923948307810.994110938189938
450.420.4234463937394640.421.008205699379680.991861086101056
460.420.4202358888058730.4195833333333331.001555246409230.999438675248458
470.420.420353616145120.418751.003829531092820.999158765069365
480.420.4148499219834520.4179166666666670.992661827278451.01241431598185
490.420.4168477675599360.4170833333333330.9994352069369091.00756207106138
500.420.4150220241703810.416250.997049907916831.01199448593016
510.420.4133377126943170.4154166666666670.9949954969572321.01611826625317
520.410.411450100588170.4145833333333330.9924424536800090.996475634381673
530.410.413369735248950.413750.9990809311152870.991848132648317
540.410.4134047192684070.4129166666666671.001181963919450.9917641983516
550.410.4135824047288440.4120833333333331.003637787006290.991338111370592
560.410.4136862237415850.411251.005923948307810.991089324396047
570.410.4137844224537420.4104166666666671.008205699379680.99085412053141
580.410.4106376510277850.411.001555246409230.998447168626187
590.410.4115701077480580.411.003829531092820.996185078268563
600.410.4069913491841650.410.992661827278451.00739241957321
610.410.4097684348441330.410.9994352069369091.00056511223456
620.410.4087904622459010.410.997049907916831.00295882087721
630.410.4079481537524650.410.9949954969572321.00502967406192
640.410.4069014060088040.410.9924424536800091.00761509777415
650.410.4096231817572680.410.9990809311152871.00091991434937
660.410.4104846052069750.411.001181963919450.998819431469955
670.41NANA1.00363778700629NA
680.41NANA1.00592394830781NA
690.41NANA1.00820569937968NA
700.41NANA1.00155524640923NA
710.41NANA1.00382953109282NA
720.41NANA0.99266182727845NA



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')