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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 02 May 2012 05:18:38 -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/02/t1335950456ya4ws6qbjrcszgo.htm/, Retrieved Tue, 07 May 2024 14:40:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165884, Retrieved Tue, 07 May 2024 14:40:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [opgave 9: classic...] [2012-05-02 09:18:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1,78
1,79
1,8
1,82
1,82
1,83
1,84
1,84
1,83
1,83
1,83
1,84
1,86
1,85
1,85
1,85
1,84
1,85
1,85
1,83
1,82
1,84
1,85
1,88
1,91
1,93
1,91
1,9
1,9
1,89
1,88
1,88
1,92
1,98
2
2
2,02
2,01
2,05
2,07
2,07
2,04
2,05
2,05
2,04
2,03
2,04
2,04
2,1
2,09
2,1
2,09
2,08
2,1
2,11
2,08
2,09
2,1
2,09
2,09




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165884&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165884&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165884&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
11.78NANA0.0243836805555555NA
21.79NANA0.0165711805555555NA
31.8NANA0.0188628472222221NA
41.82NANA0.0133420138888887NA
51.82NANA0.0028211805555556NA
61.83NANA-0.00499131944444424NA
71.841.816362847222221.82416666666667-0.007803819444444290.0236371527777779
81.841.810737847222221.83-0.01926215277777770.0292621527777779
91.831.811571180555561.83458333333333-0.02301215277777770.0184288194444446
101.831.826467013888891.83791666666667-0.01144965277777770.00353298611111108
111.831.833029513888891.84-0.00697048611111116-0.00302951388888917
121.841.839175347222221.84166666666667-0.002491319444444620.00082465277777799
131.861.867300347222221.842916666666670.0243836805555555-0.00730034722222217
141.851.859487847222221.842916666666670.0165711805555555-0.0094878472222224
151.851.860946180555561.842083333333330.0188628472222221-0.0109461805555553
161.851.855425347222221.842083333333330.0133420138888887-0.00542534722222188
171.841.846154513888891.843333333333330.0028211805555556-0.00615451388888855
181.851.840842013888891.84583333333333-0.004991319444444240.00915798611111129
191.851.841779513888891.84958333333333-0.007803819444444290.0082204861111117
201.831.835737847222221.855-0.0192621527777777-0.00573784722222181
211.821.837821180555561.86083333333333-0.0230121527777777-0.0178211805555553
221.841.853967013888891.86541666666667-0.0114496527777777-0.0139670138888888
231.851.863029513888891.87-0.00697048611111116-0.0130295138888885
241.881.871675347222221.87416666666667-0.002491319444444620.00832465277777805
251.911.901467013888891.877083333333330.02438368055555550.0085329861111112
261.931.896987847222221.880416666666670.01657118055555550.033012152777778
271.911.905529513888891.886666666666670.01886284722222210.00447048611111112
281.91.910008680555561.896666666666670.0133420138888887-0.0100086805555553
291.91.911571180555561.908750.0028211805555556-0.0115711805555556
301.891.915008680555561.92-0.00499131944444424-0.0250086805555556
311.881.921779513888891.92958333333333-0.00780381944444429-0.041779513888889
321.881.918237847222221.9375-0.0192621527777777-0.0382378472222222
331.921.923654513888891.94666666666667-0.0230121527777777-0.00365451388888882
341.981.948133680555561.95958333333333-0.01144965277777770.0318663194444446
3521.966779513888891.97375-0.006970486111111160.0332204861111114
3621.984592013888891.98708333333333-0.002491319444444620.0154079861111112
372.022.024800347222222.000416666666670.0243836805555555-0.00480034722222222
382.012.031154513888892.014583333333330.0165711805555555-0.0211545138888887
392.052.045529513888892.026666666666670.01886284722222210.00447048611111134
402.072.047092013888892.033750.01334201388888870.022907986111111
412.072.040321180555562.03750.00282118055555560.0296788194444444
422.042.035842013888892.04083333333333-0.004991319444444240.00415798611111118
432.052.038029513888892.04583333333333-0.007803819444444290.0119704861111112
442.052.033237847222222.0525-0.01926215277777770.0167621527777779
452.042.034904513888892.05791666666667-0.02301215277777770.00509548611111121
462.032.049383680555562.06083333333333-0.0114496527777777-0.0193836805555554
472.042.055112847222222.06208333333333-0.00697048611111116-0.0151128472222219
482.042.062508680555562.065-0.00249131944444462-0.0225086805555552
492.12.094383680555562.070.02438368055555550.00561631944444496
502.092.090321180555562.073750.0165711805555555-0.000321180555555411
512.12.095946180555562.077083333333330.01886284722222210.00405381944444461
522.092.095425347222222.082083333333330.0133420138888887-0.00542534722222232
532.082.089904513888892.087083333333330.0028211805555556-0.00990451388888891
542.12.086258680555562.09125-0.004991319444444240.0137413194444447
552.11NANA-0.00780381944444429NA
562.08NANA-0.0192621527777777NA
572.09NANA-0.0230121527777777NA
582.1NANA-0.0114496527777777NA
592.09NANA-0.00697048611111116NA
602.09NANA-0.00249131944444462NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.78 & NA & NA & 0.0243836805555555 & NA \tabularnewline
2 & 1.79 & NA & NA & 0.0165711805555555 & NA \tabularnewline
3 & 1.8 & NA & NA & 0.0188628472222221 & NA \tabularnewline
4 & 1.82 & NA & NA & 0.0133420138888887 & NA \tabularnewline
5 & 1.82 & NA & NA & 0.0028211805555556 & NA \tabularnewline
6 & 1.83 & NA & NA & -0.00499131944444424 & NA \tabularnewline
7 & 1.84 & 1.81636284722222 & 1.82416666666667 & -0.00780381944444429 & 0.0236371527777779 \tabularnewline
8 & 1.84 & 1.81073784722222 & 1.83 & -0.0192621527777777 & 0.0292621527777779 \tabularnewline
9 & 1.83 & 1.81157118055556 & 1.83458333333333 & -0.0230121527777777 & 0.0184288194444446 \tabularnewline
10 & 1.83 & 1.82646701388889 & 1.83791666666667 & -0.0114496527777777 & 0.00353298611111108 \tabularnewline
11 & 1.83 & 1.83302951388889 & 1.84 & -0.00697048611111116 & -0.00302951388888917 \tabularnewline
12 & 1.84 & 1.83917534722222 & 1.84166666666667 & -0.00249131944444462 & 0.00082465277777799 \tabularnewline
13 & 1.86 & 1.86730034722222 & 1.84291666666667 & 0.0243836805555555 & -0.00730034722222217 \tabularnewline
14 & 1.85 & 1.85948784722222 & 1.84291666666667 & 0.0165711805555555 & -0.0094878472222224 \tabularnewline
15 & 1.85 & 1.86094618055556 & 1.84208333333333 & 0.0188628472222221 & -0.0109461805555553 \tabularnewline
16 & 1.85 & 1.85542534722222 & 1.84208333333333 & 0.0133420138888887 & -0.00542534722222188 \tabularnewline
17 & 1.84 & 1.84615451388889 & 1.84333333333333 & 0.0028211805555556 & -0.00615451388888855 \tabularnewline
18 & 1.85 & 1.84084201388889 & 1.84583333333333 & -0.00499131944444424 & 0.00915798611111129 \tabularnewline
19 & 1.85 & 1.84177951388889 & 1.84958333333333 & -0.00780381944444429 & 0.0082204861111117 \tabularnewline
20 & 1.83 & 1.83573784722222 & 1.855 & -0.0192621527777777 & -0.00573784722222181 \tabularnewline
21 & 1.82 & 1.83782118055556 & 1.86083333333333 & -0.0230121527777777 & -0.0178211805555553 \tabularnewline
22 & 1.84 & 1.85396701388889 & 1.86541666666667 & -0.0114496527777777 & -0.0139670138888888 \tabularnewline
23 & 1.85 & 1.86302951388889 & 1.87 & -0.00697048611111116 & -0.0130295138888885 \tabularnewline
24 & 1.88 & 1.87167534722222 & 1.87416666666667 & -0.00249131944444462 & 0.00832465277777805 \tabularnewline
25 & 1.91 & 1.90146701388889 & 1.87708333333333 & 0.0243836805555555 & 0.0085329861111112 \tabularnewline
26 & 1.93 & 1.89698784722222 & 1.88041666666667 & 0.0165711805555555 & 0.033012152777778 \tabularnewline
27 & 1.91 & 1.90552951388889 & 1.88666666666667 & 0.0188628472222221 & 0.00447048611111112 \tabularnewline
28 & 1.9 & 1.91000868055556 & 1.89666666666667 & 0.0133420138888887 & -0.0100086805555553 \tabularnewline
29 & 1.9 & 1.91157118055556 & 1.90875 & 0.0028211805555556 & -0.0115711805555556 \tabularnewline
30 & 1.89 & 1.91500868055556 & 1.92 & -0.00499131944444424 & -0.0250086805555556 \tabularnewline
31 & 1.88 & 1.92177951388889 & 1.92958333333333 & -0.00780381944444429 & -0.041779513888889 \tabularnewline
32 & 1.88 & 1.91823784722222 & 1.9375 & -0.0192621527777777 & -0.0382378472222222 \tabularnewline
33 & 1.92 & 1.92365451388889 & 1.94666666666667 & -0.0230121527777777 & -0.00365451388888882 \tabularnewline
34 & 1.98 & 1.94813368055556 & 1.95958333333333 & -0.0114496527777777 & 0.0318663194444446 \tabularnewline
35 & 2 & 1.96677951388889 & 1.97375 & -0.00697048611111116 & 0.0332204861111114 \tabularnewline
36 & 2 & 1.98459201388889 & 1.98708333333333 & -0.00249131944444462 & 0.0154079861111112 \tabularnewline
37 & 2.02 & 2.02480034722222 & 2.00041666666667 & 0.0243836805555555 & -0.00480034722222222 \tabularnewline
38 & 2.01 & 2.03115451388889 & 2.01458333333333 & 0.0165711805555555 & -0.0211545138888887 \tabularnewline
39 & 2.05 & 2.04552951388889 & 2.02666666666667 & 0.0188628472222221 & 0.00447048611111134 \tabularnewline
40 & 2.07 & 2.04709201388889 & 2.03375 & 0.0133420138888887 & 0.022907986111111 \tabularnewline
41 & 2.07 & 2.04032118055556 & 2.0375 & 0.0028211805555556 & 0.0296788194444444 \tabularnewline
42 & 2.04 & 2.03584201388889 & 2.04083333333333 & -0.00499131944444424 & 0.00415798611111118 \tabularnewline
43 & 2.05 & 2.03802951388889 & 2.04583333333333 & -0.00780381944444429 & 0.0119704861111112 \tabularnewline
44 & 2.05 & 2.03323784722222 & 2.0525 & -0.0192621527777777 & 0.0167621527777779 \tabularnewline
45 & 2.04 & 2.03490451388889 & 2.05791666666667 & -0.0230121527777777 & 0.00509548611111121 \tabularnewline
46 & 2.03 & 2.04938368055556 & 2.06083333333333 & -0.0114496527777777 & -0.0193836805555554 \tabularnewline
47 & 2.04 & 2.05511284722222 & 2.06208333333333 & -0.00697048611111116 & -0.0151128472222219 \tabularnewline
48 & 2.04 & 2.06250868055556 & 2.065 & -0.00249131944444462 & -0.0225086805555552 \tabularnewline
49 & 2.1 & 2.09438368055556 & 2.07 & 0.0243836805555555 & 0.00561631944444496 \tabularnewline
50 & 2.09 & 2.09032118055556 & 2.07375 & 0.0165711805555555 & -0.000321180555555411 \tabularnewline
51 & 2.1 & 2.09594618055556 & 2.07708333333333 & 0.0188628472222221 & 0.00405381944444461 \tabularnewline
52 & 2.09 & 2.09542534722222 & 2.08208333333333 & 0.0133420138888887 & -0.00542534722222232 \tabularnewline
53 & 2.08 & 2.08990451388889 & 2.08708333333333 & 0.0028211805555556 & -0.00990451388888891 \tabularnewline
54 & 2.1 & 2.08625868055556 & 2.09125 & -0.00499131944444424 & 0.0137413194444447 \tabularnewline
55 & 2.11 & NA & NA & -0.00780381944444429 & NA \tabularnewline
56 & 2.08 & NA & NA & -0.0192621527777777 & NA \tabularnewline
57 & 2.09 & NA & NA & -0.0230121527777777 & NA \tabularnewline
58 & 2.1 & NA & NA & -0.0114496527777777 & NA \tabularnewline
59 & 2.09 & NA & NA & -0.00697048611111116 & NA \tabularnewline
60 & 2.09 & NA & NA & -0.00249131944444462 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165884&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]1.78[/C][C]NA[/C][C]NA[/C][C]0.0243836805555555[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.79[/C][C]NA[/C][C]NA[/C][C]0.0165711805555555[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]0.0188628472222221[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.82[/C][C]NA[/C][C]NA[/C][C]0.0133420138888887[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.82[/C][C]NA[/C][C]NA[/C][C]0.0028211805555556[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.83[/C][C]NA[/C][C]NA[/C][C]-0.00499131944444424[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.84[/C][C]1.81636284722222[/C][C]1.82416666666667[/C][C]-0.00780381944444429[/C][C]0.0236371527777779[/C][/ROW]
[ROW][C]8[/C][C]1.84[/C][C]1.81073784722222[/C][C]1.83[/C][C]-0.0192621527777777[/C][C]0.0292621527777779[/C][/ROW]
[ROW][C]9[/C][C]1.83[/C][C]1.81157118055556[/C][C]1.83458333333333[/C][C]-0.0230121527777777[/C][C]0.0184288194444446[/C][/ROW]
[ROW][C]10[/C][C]1.83[/C][C]1.82646701388889[/C][C]1.83791666666667[/C][C]-0.0114496527777777[/C][C]0.00353298611111108[/C][/ROW]
[ROW][C]11[/C][C]1.83[/C][C]1.83302951388889[/C][C]1.84[/C][C]-0.00697048611111116[/C][C]-0.00302951388888917[/C][/ROW]
[ROW][C]12[/C][C]1.84[/C][C]1.83917534722222[/C][C]1.84166666666667[/C][C]-0.00249131944444462[/C][C]0.00082465277777799[/C][/ROW]
[ROW][C]13[/C][C]1.86[/C][C]1.86730034722222[/C][C]1.84291666666667[/C][C]0.0243836805555555[/C][C]-0.00730034722222217[/C][/ROW]
[ROW][C]14[/C][C]1.85[/C][C]1.85948784722222[/C][C]1.84291666666667[/C][C]0.0165711805555555[/C][C]-0.0094878472222224[/C][/ROW]
[ROW][C]15[/C][C]1.85[/C][C]1.86094618055556[/C][C]1.84208333333333[/C][C]0.0188628472222221[/C][C]-0.0109461805555553[/C][/ROW]
[ROW][C]16[/C][C]1.85[/C][C]1.85542534722222[/C][C]1.84208333333333[/C][C]0.0133420138888887[/C][C]-0.00542534722222188[/C][/ROW]
[ROW][C]17[/C][C]1.84[/C][C]1.84615451388889[/C][C]1.84333333333333[/C][C]0.0028211805555556[/C][C]-0.00615451388888855[/C][/ROW]
[ROW][C]18[/C][C]1.85[/C][C]1.84084201388889[/C][C]1.84583333333333[/C][C]-0.00499131944444424[/C][C]0.00915798611111129[/C][/ROW]
[ROW][C]19[/C][C]1.85[/C][C]1.84177951388889[/C][C]1.84958333333333[/C][C]-0.00780381944444429[/C][C]0.0082204861111117[/C][/ROW]
[ROW][C]20[/C][C]1.83[/C][C]1.83573784722222[/C][C]1.855[/C][C]-0.0192621527777777[/C][C]-0.00573784722222181[/C][/ROW]
[ROW][C]21[/C][C]1.82[/C][C]1.83782118055556[/C][C]1.86083333333333[/C][C]-0.0230121527777777[/C][C]-0.0178211805555553[/C][/ROW]
[ROW][C]22[/C][C]1.84[/C][C]1.85396701388889[/C][C]1.86541666666667[/C][C]-0.0114496527777777[/C][C]-0.0139670138888888[/C][/ROW]
[ROW][C]23[/C][C]1.85[/C][C]1.86302951388889[/C][C]1.87[/C][C]-0.00697048611111116[/C][C]-0.0130295138888885[/C][/ROW]
[ROW][C]24[/C][C]1.88[/C][C]1.87167534722222[/C][C]1.87416666666667[/C][C]-0.00249131944444462[/C][C]0.00832465277777805[/C][/ROW]
[ROW][C]25[/C][C]1.91[/C][C]1.90146701388889[/C][C]1.87708333333333[/C][C]0.0243836805555555[/C][C]0.0085329861111112[/C][/ROW]
[ROW][C]26[/C][C]1.93[/C][C]1.89698784722222[/C][C]1.88041666666667[/C][C]0.0165711805555555[/C][C]0.033012152777778[/C][/ROW]
[ROW][C]27[/C][C]1.91[/C][C]1.90552951388889[/C][C]1.88666666666667[/C][C]0.0188628472222221[/C][C]0.00447048611111112[/C][/ROW]
[ROW][C]28[/C][C]1.9[/C][C]1.91000868055556[/C][C]1.89666666666667[/C][C]0.0133420138888887[/C][C]-0.0100086805555553[/C][/ROW]
[ROW][C]29[/C][C]1.9[/C][C]1.91157118055556[/C][C]1.90875[/C][C]0.0028211805555556[/C][C]-0.0115711805555556[/C][/ROW]
[ROW][C]30[/C][C]1.89[/C][C]1.91500868055556[/C][C]1.92[/C][C]-0.00499131944444424[/C][C]-0.0250086805555556[/C][/ROW]
[ROW][C]31[/C][C]1.88[/C][C]1.92177951388889[/C][C]1.92958333333333[/C][C]-0.00780381944444429[/C][C]-0.041779513888889[/C][/ROW]
[ROW][C]32[/C][C]1.88[/C][C]1.91823784722222[/C][C]1.9375[/C][C]-0.0192621527777777[/C][C]-0.0382378472222222[/C][/ROW]
[ROW][C]33[/C][C]1.92[/C][C]1.92365451388889[/C][C]1.94666666666667[/C][C]-0.0230121527777777[/C][C]-0.00365451388888882[/C][/ROW]
[ROW][C]34[/C][C]1.98[/C][C]1.94813368055556[/C][C]1.95958333333333[/C][C]-0.0114496527777777[/C][C]0.0318663194444446[/C][/ROW]
[ROW][C]35[/C][C]2[/C][C]1.96677951388889[/C][C]1.97375[/C][C]-0.00697048611111116[/C][C]0.0332204861111114[/C][/ROW]
[ROW][C]36[/C][C]2[/C][C]1.98459201388889[/C][C]1.98708333333333[/C][C]-0.00249131944444462[/C][C]0.0154079861111112[/C][/ROW]
[ROW][C]37[/C][C]2.02[/C][C]2.02480034722222[/C][C]2.00041666666667[/C][C]0.0243836805555555[/C][C]-0.00480034722222222[/C][/ROW]
[ROW][C]38[/C][C]2.01[/C][C]2.03115451388889[/C][C]2.01458333333333[/C][C]0.0165711805555555[/C][C]-0.0211545138888887[/C][/ROW]
[ROW][C]39[/C][C]2.05[/C][C]2.04552951388889[/C][C]2.02666666666667[/C][C]0.0188628472222221[/C][C]0.00447048611111134[/C][/ROW]
[ROW][C]40[/C][C]2.07[/C][C]2.04709201388889[/C][C]2.03375[/C][C]0.0133420138888887[/C][C]0.022907986111111[/C][/ROW]
[ROW][C]41[/C][C]2.07[/C][C]2.04032118055556[/C][C]2.0375[/C][C]0.0028211805555556[/C][C]0.0296788194444444[/C][/ROW]
[ROW][C]42[/C][C]2.04[/C][C]2.03584201388889[/C][C]2.04083333333333[/C][C]-0.00499131944444424[/C][C]0.00415798611111118[/C][/ROW]
[ROW][C]43[/C][C]2.05[/C][C]2.03802951388889[/C][C]2.04583333333333[/C][C]-0.00780381944444429[/C][C]0.0119704861111112[/C][/ROW]
[ROW][C]44[/C][C]2.05[/C][C]2.03323784722222[/C][C]2.0525[/C][C]-0.0192621527777777[/C][C]0.0167621527777779[/C][/ROW]
[ROW][C]45[/C][C]2.04[/C][C]2.03490451388889[/C][C]2.05791666666667[/C][C]-0.0230121527777777[/C][C]0.00509548611111121[/C][/ROW]
[ROW][C]46[/C][C]2.03[/C][C]2.04938368055556[/C][C]2.06083333333333[/C][C]-0.0114496527777777[/C][C]-0.0193836805555554[/C][/ROW]
[ROW][C]47[/C][C]2.04[/C][C]2.05511284722222[/C][C]2.06208333333333[/C][C]-0.00697048611111116[/C][C]-0.0151128472222219[/C][/ROW]
[ROW][C]48[/C][C]2.04[/C][C]2.06250868055556[/C][C]2.065[/C][C]-0.00249131944444462[/C][C]-0.0225086805555552[/C][/ROW]
[ROW][C]49[/C][C]2.1[/C][C]2.09438368055556[/C][C]2.07[/C][C]0.0243836805555555[/C][C]0.00561631944444496[/C][/ROW]
[ROW][C]50[/C][C]2.09[/C][C]2.09032118055556[/C][C]2.07375[/C][C]0.0165711805555555[/C][C]-0.000321180555555411[/C][/ROW]
[ROW][C]51[/C][C]2.1[/C][C]2.09594618055556[/C][C]2.07708333333333[/C][C]0.0188628472222221[/C][C]0.00405381944444461[/C][/ROW]
[ROW][C]52[/C][C]2.09[/C][C]2.09542534722222[/C][C]2.08208333333333[/C][C]0.0133420138888887[/C][C]-0.00542534722222232[/C][/ROW]
[ROW][C]53[/C][C]2.08[/C][C]2.08990451388889[/C][C]2.08708333333333[/C][C]0.0028211805555556[/C][C]-0.00990451388888891[/C][/ROW]
[ROW][C]54[/C][C]2.1[/C][C]2.08625868055556[/C][C]2.09125[/C][C]-0.00499131944444424[/C][C]0.0137413194444447[/C][/ROW]
[ROW][C]55[/C][C]2.11[/C][C]NA[/C][C]NA[/C][C]-0.00780381944444429[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]2.08[/C][C]NA[/C][C]NA[/C][C]-0.0192621527777777[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]2.09[/C][C]NA[/C][C]NA[/C][C]-0.0230121527777777[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]2.1[/C][C]NA[/C][C]NA[/C][C]-0.0114496527777777[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]2.09[/C][C]NA[/C][C]NA[/C][C]-0.00697048611111116[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]2.09[/C][C]NA[/C][C]NA[/C][C]-0.00249131944444462[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165884&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165884&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
11.78NANA0.0243836805555555NA
21.79NANA0.0165711805555555NA
31.8NANA0.0188628472222221NA
41.82NANA0.0133420138888887NA
51.82NANA0.0028211805555556NA
61.83NANA-0.00499131944444424NA
71.841.816362847222221.82416666666667-0.007803819444444290.0236371527777779
81.841.810737847222221.83-0.01926215277777770.0292621527777779
91.831.811571180555561.83458333333333-0.02301215277777770.0184288194444446
101.831.826467013888891.83791666666667-0.01144965277777770.00353298611111108
111.831.833029513888891.84-0.00697048611111116-0.00302951388888917
121.841.839175347222221.84166666666667-0.002491319444444620.00082465277777799
131.861.867300347222221.842916666666670.0243836805555555-0.00730034722222217
141.851.859487847222221.842916666666670.0165711805555555-0.0094878472222224
151.851.860946180555561.842083333333330.0188628472222221-0.0109461805555553
161.851.855425347222221.842083333333330.0133420138888887-0.00542534722222188
171.841.846154513888891.843333333333330.0028211805555556-0.00615451388888855
181.851.840842013888891.84583333333333-0.004991319444444240.00915798611111129
191.851.841779513888891.84958333333333-0.007803819444444290.0082204861111117
201.831.835737847222221.855-0.0192621527777777-0.00573784722222181
211.821.837821180555561.86083333333333-0.0230121527777777-0.0178211805555553
221.841.853967013888891.86541666666667-0.0114496527777777-0.0139670138888888
231.851.863029513888891.87-0.00697048611111116-0.0130295138888885
241.881.871675347222221.87416666666667-0.002491319444444620.00832465277777805
251.911.901467013888891.877083333333330.02438368055555550.0085329861111112
261.931.896987847222221.880416666666670.01657118055555550.033012152777778
271.911.905529513888891.886666666666670.01886284722222210.00447048611111112
281.91.910008680555561.896666666666670.0133420138888887-0.0100086805555553
291.91.911571180555561.908750.0028211805555556-0.0115711805555556
301.891.915008680555561.92-0.00499131944444424-0.0250086805555556
311.881.921779513888891.92958333333333-0.00780381944444429-0.041779513888889
321.881.918237847222221.9375-0.0192621527777777-0.0382378472222222
331.921.923654513888891.94666666666667-0.0230121527777777-0.00365451388888882
341.981.948133680555561.95958333333333-0.01144965277777770.0318663194444446
3521.966779513888891.97375-0.006970486111111160.0332204861111114
3621.984592013888891.98708333333333-0.002491319444444620.0154079861111112
372.022.024800347222222.000416666666670.0243836805555555-0.00480034722222222
382.012.031154513888892.014583333333330.0165711805555555-0.0211545138888887
392.052.045529513888892.026666666666670.01886284722222210.00447048611111134
402.072.047092013888892.033750.01334201388888870.022907986111111
412.072.040321180555562.03750.00282118055555560.0296788194444444
422.042.035842013888892.04083333333333-0.004991319444444240.00415798611111118
432.052.038029513888892.04583333333333-0.007803819444444290.0119704861111112
442.052.033237847222222.0525-0.01926215277777770.0167621527777779
452.042.034904513888892.05791666666667-0.02301215277777770.00509548611111121
462.032.049383680555562.06083333333333-0.0114496527777777-0.0193836805555554
472.042.055112847222222.06208333333333-0.00697048611111116-0.0151128472222219
482.042.062508680555562.065-0.00249131944444462-0.0225086805555552
492.12.094383680555562.070.02438368055555550.00561631944444496
502.092.090321180555562.073750.0165711805555555-0.000321180555555411
512.12.095946180555562.077083333333330.01886284722222210.00405381944444461
522.092.095425347222222.082083333333330.0133420138888887-0.00542534722222232
532.082.089904513888892.087083333333330.0028211805555556-0.00990451388888891
542.12.086258680555562.09125-0.004991319444444240.0137413194444447
552.11NANA-0.00780381944444429NA
562.08NANA-0.0192621527777777NA
572.09NANA-0.0230121527777777NA
582.1NANA-0.0114496527777777NA
592.09NANA-0.00697048611111116NA
602.09NANA-0.00249131944444462NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; 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')