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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 13:16:36 -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/2013/Dec/12/t1386872235vrgcpmr2ayxbrhv.htm/, Retrieved Sun, 05 Dec 2021 16:37:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232264, Retrieved Sun, 05 Dec 2021 16:37:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact37
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 18:16:36] [2e53d6acb0d55ba82adefb1cb5f89cf8] [Current]
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Dataseries X:
5,53
5,53
5,53
5,53
5,53
5,53
5,53
5,53
5,53
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,67
5,89
5,89
5,89
5,89
5,89
5,89
5,89
5,89
5,89
5,89
5,89
5,89
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,08
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,28
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,31
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,48
6,5
6,5
6,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'George Udny Yule' @ yule.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 & 7 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232264&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232264&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232264&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 time7 seconds
R Server'George Udny Yule' @ yule.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
15.53NANA0.0323611NA
25.53NANA0.0191667NA
35.53NANA0.00597222NA
45.53NANA-0.00638889NA
55.53NANA-0.0179167NA
65.53NANA-0.0294444NA
75.535.524035.57083-0.04680560.00597222
85.535.52255.5825-0.060.0075
95.535.520975.59417-0.07319440.00902778
105.675.677785.605830.0719444-0.00777778
115.675.676255.61750.05875-0.00625
125.675.674725.629170.0455556-0.00472222
135.675.673195.640830.0323611-0.00319444
145.675.671675.65250.0191667-0.00166667
155.675.670145.664170.00597222-0.000138889
165.675.672785.67917-0.00638889-0.00277778
175.675.679585.6975-0.0179167-0.00958333
185.675.686395.71583-0.0294444-0.0163889
195.675.687365.73417-0.0468056-0.0173611
205.675.69255.7525-0.06-0.0225
215.675.697645.77083-0.0731944-0.0276389
225.895.861115.789170.07194440.0288889
235.895.866255.80750.058750.02375
245.895.871395.825830.04555560.0186111
255.895.876535.844170.03236110.0134722
265.895.881675.86250.01916670.00833333
275.895.886815.880830.005972220.00319444
285.895.891535.89792-0.00638889-0.00152778
295.895.895835.91375-0.0179167-0.00583333
305.895.900145.92958-0.0294444-0.0101389
315.895.898615.94542-0.0468056-0.00861111
325.895.901255.96125-0.06-0.01125
335.895.903895.97708-0.0731944-0.0138889
346.086.064865.992920.07194440.0151389
356.086.06756.008750.058750.0125
366.086.070146.024580.04555560.00986111
376.086.072786.040420.03236110.00722222
386.086.075426.056250.01916670.00458333
396.086.078066.072080.005972220.00194444
406.086.081946.08833-0.00638889-0.00194444
416.086.087086.105-0.0179167-0.00708333
426.086.092226.12167-0.0294444-0.0122222
436.086.091536.13833-0.0468056-0.0115278
446.086.0956.155-0.06-0.015
456.086.098476.17167-0.0731944-0.0184722
466.286.260286.188330.07194440.0197222
476.286.263756.2050.058750.01625
486.286.267226.221670.04555560.0127778
496.286.270696.238330.03236110.00930556
506.286.274176.2550.01916670.00583333
516.286.277646.271670.005972220.00236111
526.286.274866.28125-0.006388890.00513889
536.286.265836.28375-0.01791670.0141667
546.286.256816.28625-0.02944440.0231944
556.286.241946.28875-0.04680560.0380556
566.286.231256.29125-0.060.04875
576.286.220566.29375-0.07319440.0594444
586.316.368196.296250.0719444-0.0581944
596.316.35756.298750.05875-0.0475
606.316.346816.301250.0455556-0.0368056
616.316.336116.303750.0323611-0.0261111
626.316.325426.306250.0191667-0.0154167
636.316.314726.308750.00597222-0.00472222
646.316.310696.31708-0.00638889-0.000694444
656.316.313336.33125-0.0179167-0.00333333
666.316.315976.34542-0.0294444-0.00597222
676.316.312786.35958-0.0468056-0.00277778
686.316.313756.37375-0.06-0.00375
696.316.314726.38792-0.0731944-0.00472222
706.486.474036.402080.07194440.00597222
716.486.4756.416250.058750.005
726.486.475976.430420.04555560.00402778
736.486.476946.444580.03236110.00305556
746.486.477926.458750.01916670.00208333
756.486.478896.472920.005972220.00111111
766.486.474446.48083-0.006388890.00555556
776.486.464586.4825-0.01791670.0154167
786.486.454726.48417-0.02944440.0252778
796.48NANA-0.0468056NA
806.48NANA-0.06NA
816.48NANA-0.0731944NA
826.5NANA0.0719444NA
836.5NANA0.05875NA
846.5NANA0.0455556NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 5.53 & NA & NA & 0.0323611 & NA \tabularnewline
2 & 5.53 & NA & NA & 0.0191667 & NA \tabularnewline
3 & 5.53 & NA & NA & 0.00597222 & NA \tabularnewline
4 & 5.53 & NA & NA & -0.00638889 & NA \tabularnewline
5 & 5.53 & NA & NA & -0.0179167 & NA \tabularnewline
6 & 5.53 & NA & NA & -0.0294444 & NA \tabularnewline
7 & 5.53 & 5.52403 & 5.57083 & -0.0468056 & 0.00597222 \tabularnewline
8 & 5.53 & 5.5225 & 5.5825 & -0.06 & 0.0075 \tabularnewline
9 & 5.53 & 5.52097 & 5.59417 & -0.0731944 & 0.00902778 \tabularnewline
10 & 5.67 & 5.67778 & 5.60583 & 0.0719444 & -0.00777778 \tabularnewline
11 & 5.67 & 5.67625 & 5.6175 & 0.05875 & -0.00625 \tabularnewline
12 & 5.67 & 5.67472 & 5.62917 & 0.0455556 & -0.00472222 \tabularnewline
13 & 5.67 & 5.67319 & 5.64083 & 0.0323611 & -0.00319444 \tabularnewline
14 & 5.67 & 5.67167 & 5.6525 & 0.0191667 & -0.00166667 \tabularnewline
15 & 5.67 & 5.67014 & 5.66417 & 0.00597222 & -0.000138889 \tabularnewline
16 & 5.67 & 5.67278 & 5.67917 & -0.00638889 & -0.00277778 \tabularnewline
17 & 5.67 & 5.67958 & 5.6975 & -0.0179167 & -0.00958333 \tabularnewline
18 & 5.67 & 5.68639 & 5.71583 & -0.0294444 & -0.0163889 \tabularnewline
19 & 5.67 & 5.68736 & 5.73417 & -0.0468056 & -0.0173611 \tabularnewline
20 & 5.67 & 5.6925 & 5.7525 & -0.06 & -0.0225 \tabularnewline
21 & 5.67 & 5.69764 & 5.77083 & -0.0731944 & -0.0276389 \tabularnewline
22 & 5.89 & 5.86111 & 5.78917 & 0.0719444 & 0.0288889 \tabularnewline
23 & 5.89 & 5.86625 & 5.8075 & 0.05875 & 0.02375 \tabularnewline
24 & 5.89 & 5.87139 & 5.82583 & 0.0455556 & 0.0186111 \tabularnewline
25 & 5.89 & 5.87653 & 5.84417 & 0.0323611 & 0.0134722 \tabularnewline
26 & 5.89 & 5.88167 & 5.8625 & 0.0191667 & 0.00833333 \tabularnewline
27 & 5.89 & 5.88681 & 5.88083 & 0.00597222 & 0.00319444 \tabularnewline
28 & 5.89 & 5.89153 & 5.89792 & -0.00638889 & -0.00152778 \tabularnewline
29 & 5.89 & 5.89583 & 5.91375 & -0.0179167 & -0.00583333 \tabularnewline
30 & 5.89 & 5.90014 & 5.92958 & -0.0294444 & -0.0101389 \tabularnewline
31 & 5.89 & 5.89861 & 5.94542 & -0.0468056 & -0.00861111 \tabularnewline
32 & 5.89 & 5.90125 & 5.96125 & -0.06 & -0.01125 \tabularnewline
33 & 5.89 & 5.90389 & 5.97708 & -0.0731944 & -0.0138889 \tabularnewline
34 & 6.08 & 6.06486 & 5.99292 & 0.0719444 & 0.0151389 \tabularnewline
35 & 6.08 & 6.0675 & 6.00875 & 0.05875 & 0.0125 \tabularnewline
36 & 6.08 & 6.07014 & 6.02458 & 0.0455556 & 0.00986111 \tabularnewline
37 & 6.08 & 6.07278 & 6.04042 & 0.0323611 & 0.00722222 \tabularnewline
38 & 6.08 & 6.07542 & 6.05625 & 0.0191667 & 0.00458333 \tabularnewline
39 & 6.08 & 6.07806 & 6.07208 & 0.00597222 & 0.00194444 \tabularnewline
40 & 6.08 & 6.08194 & 6.08833 & -0.00638889 & -0.00194444 \tabularnewline
41 & 6.08 & 6.08708 & 6.105 & -0.0179167 & -0.00708333 \tabularnewline
42 & 6.08 & 6.09222 & 6.12167 & -0.0294444 & -0.0122222 \tabularnewline
43 & 6.08 & 6.09153 & 6.13833 & -0.0468056 & -0.0115278 \tabularnewline
44 & 6.08 & 6.095 & 6.155 & -0.06 & -0.015 \tabularnewline
45 & 6.08 & 6.09847 & 6.17167 & -0.0731944 & -0.0184722 \tabularnewline
46 & 6.28 & 6.26028 & 6.18833 & 0.0719444 & 0.0197222 \tabularnewline
47 & 6.28 & 6.26375 & 6.205 & 0.05875 & 0.01625 \tabularnewline
48 & 6.28 & 6.26722 & 6.22167 & 0.0455556 & 0.0127778 \tabularnewline
49 & 6.28 & 6.27069 & 6.23833 & 0.0323611 & 0.00930556 \tabularnewline
50 & 6.28 & 6.27417 & 6.255 & 0.0191667 & 0.00583333 \tabularnewline
51 & 6.28 & 6.27764 & 6.27167 & 0.00597222 & 0.00236111 \tabularnewline
52 & 6.28 & 6.27486 & 6.28125 & -0.00638889 & 0.00513889 \tabularnewline
53 & 6.28 & 6.26583 & 6.28375 & -0.0179167 & 0.0141667 \tabularnewline
54 & 6.28 & 6.25681 & 6.28625 & -0.0294444 & 0.0231944 \tabularnewline
55 & 6.28 & 6.24194 & 6.28875 & -0.0468056 & 0.0380556 \tabularnewline
56 & 6.28 & 6.23125 & 6.29125 & -0.06 & 0.04875 \tabularnewline
57 & 6.28 & 6.22056 & 6.29375 & -0.0731944 & 0.0594444 \tabularnewline
58 & 6.31 & 6.36819 & 6.29625 & 0.0719444 & -0.0581944 \tabularnewline
59 & 6.31 & 6.3575 & 6.29875 & 0.05875 & -0.0475 \tabularnewline
60 & 6.31 & 6.34681 & 6.30125 & 0.0455556 & -0.0368056 \tabularnewline
61 & 6.31 & 6.33611 & 6.30375 & 0.0323611 & -0.0261111 \tabularnewline
62 & 6.31 & 6.32542 & 6.30625 & 0.0191667 & -0.0154167 \tabularnewline
63 & 6.31 & 6.31472 & 6.30875 & 0.00597222 & -0.00472222 \tabularnewline
64 & 6.31 & 6.31069 & 6.31708 & -0.00638889 & -0.000694444 \tabularnewline
65 & 6.31 & 6.31333 & 6.33125 & -0.0179167 & -0.00333333 \tabularnewline
66 & 6.31 & 6.31597 & 6.34542 & -0.0294444 & -0.00597222 \tabularnewline
67 & 6.31 & 6.31278 & 6.35958 & -0.0468056 & -0.00277778 \tabularnewline
68 & 6.31 & 6.31375 & 6.37375 & -0.06 & -0.00375 \tabularnewline
69 & 6.31 & 6.31472 & 6.38792 & -0.0731944 & -0.00472222 \tabularnewline
70 & 6.48 & 6.47403 & 6.40208 & 0.0719444 & 0.00597222 \tabularnewline
71 & 6.48 & 6.475 & 6.41625 & 0.05875 & 0.005 \tabularnewline
72 & 6.48 & 6.47597 & 6.43042 & 0.0455556 & 0.00402778 \tabularnewline
73 & 6.48 & 6.47694 & 6.44458 & 0.0323611 & 0.00305556 \tabularnewline
74 & 6.48 & 6.47792 & 6.45875 & 0.0191667 & 0.00208333 \tabularnewline
75 & 6.48 & 6.47889 & 6.47292 & 0.00597222 & 0.00111111 \tabularnewline
76 & 6.48 & 6.47444 & 6.48083 & -0.00638889 & 0.00555556 \tabularnewline
77 & 6.48 & 6.46458 & 6.4825 & -0.0179167 & 0.0154167 \tabularnewline
78 & 6.48 & 6.45472 & 6.48417 & -0.0294444 & 0.0252778 \tabularnewline
79 & 6.48 & NA & NA & -0.0468056 & NA \tabularnewline
80 & 6.48 & NA & NA & -0.06 & NA \tabularnewline
81 & 6.48 & NA & NA & -0.0731944 & NA \tabularnewline
82 & 6.5 & NA & NA & 0.0719444 & NA \tabularnewline
83 & 6.5 & NA & NA & 0.05875 & NA \tabularnewline
84 & 6.5 & NA & NA & 0.0455556 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232264&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]5.53[/C][C]NA[/C][C]NA[/C][C]0.0323611[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5.53[/C][C]NA[/C][C]NA[/C][C]0.0191667[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.53[/C][C]NA[/C][C]NA[/C][C]0.00597222[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.53[/C][C]NA[/C][C]NA[/C][C]-0.00638889[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.53[/C][C]NA[/C][C]NA[/C][C]-0.0179167[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.53[/C][C]NA[/C][C]NA[/C][C]-0.0294444[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.53[/C][C]5.52403[/C][C]5.57083[/C][C]-0.0468056[/C][C]0.00597222[/C][/ROW]
[ROW][C]8[/C][C]5.53[/C][C]5.5225[/C][C]5.5825[/C][C]-0.06[/C][C]0.0075[/C][/ROW]
[ROW][C]9[/C][C]5.53[/C][C]5.52097[/C][C]5.59417[/C][C]-0.0731944[/C][C]0.00902778[/C][/ROW]
[ROW][C]10[/C][C]5.67[/C][C]5.67778[/C][C]5.60583[/C][C]0.0719444[/C][C]-0.00777778[/C][/ROW]
[ROW][C]11[/C][C]5.67[/C][C]5.67625[/C][C]5.6175[/C][C]0.05875[/C][C]-0.00625[/C][/ROW]
[ROW][C]12[/C][C]5.67[/C][C]5.67472[/C][C]5.62917[/C][C]0.0455556[/C][C]-0.00472222[/C][/ROW]
[ROW][C]13[/C][C]5.67[/C][C]5.67319[/C][C]5.64083[/C][C]0.0323611[/C][C]-0.00319444[/C][/ROW]
[ROW][C]14[/C][C]5.67[/C][C]5.67167[/C][C]5.6525[/C][C]0.0191667[/C][C]-0.00166667[/C][/ROW]
[ROW][C]15[/C][C]5.67[/C][C]5.67014[/C][C]5.66417[/C][C]0.00597222[/C][C]-0.000138889[/C][/ROW]
[ROW][C]16[/C][C]5.67[/C][C]5.67278[/C][C]5.67917[/C][C]-0.00638889[/C][C]-0.00277778[/C][/ROW]
[ROW][C]17[/C][C]5.67[/C][C]5.67958[/C][C]5.6975[/C][C]-0.0179167[/C][C]-0.00958333[/C][/ROW]
[ROW][C]18[/C][C]5.67[/C][C]5.68639[/C][C]5.71583[/C][C]-0.0294444[/C][C]-0.0163889[/C][/ROW]
[ROW][C]19[/C][C]5.67[/C][C]5.68736[/C][C]5.73417[/C][C]-0.0468056[/C][C]-0.0173611[/C][/ROW]
[ROW][C]20[/C][C]5.67[/C][C]5.6925[/C][C]5.7525[/C][C]-0.06[/C][C]-0.0225[/C][/ROW]
[ROW][C]21[/C][C]5.67[/C][C]5.69764[/C][C]5.77083[/C][C]-0.0731944[/C][C]-0.0276389[/C][/ROW]
[ROW][C]22[/C][C]5.89[/C][C]5.86111[/C][C]5.78917[/C][C]0.0719444[/C][C]0.0288889[/C][/ROW]
[ROW][C]23[/C][C]5.89[/C][C]5.86625[/C][C]5.8075[/C][C]0.05875[/C][C]0.02375[/C][/ROW]
[ROW][C]24[/C][C]5.89[/C][C]5.87139[/C][C]5.82583[/C][C]0.0455556[/C][C]0.0186111[/C][/ROW]
[ROW][C]25[/C][C]5.89[/C][C]5.87653[/C][C]5.84417[/C][C]0.0323611[/C][C]0.0134722[/C][/ROW]
[ROW][C]26[/C][C]5.89[/C][C]5.88167[/C][C]5.8625[/C][C]0.0191667[/C][C]0.00833333[/C][/ROW]
[ROW][C]27[/C][C]5.89[/C][C]5.88681[/C][C]5.88083[/C][C]0.00597222[/C][C]0.00319444[/C][/ROW]
[ROW][C]28[/C][C]5.89[/C][C]5.89153[/C][C]5.89792[/C][C]-0.00638889[/C][C]-0.00152778[/C][/ROW]
[ROW][C]29[/C][C]5.89[/C][C]5.89583[/C][C]5.91375[/C][C]-0.0179167[/C][C]-0.00583333[/C][/ROW]
[ROW][C]30[/C][C]5.89[/C][C]5.90014[/C][C]5.92958[/C][C]-0.0294444[/C][C]-0.0101389[/C][/ROW]
[ROW][C]31[/C][C]5.89[/C][C]5.89861[/C][C]5.94542[/C][C]-0.0468056[/C][C]-0.00861111[/C][/ROW]
[ROW][C]32[/C][C]5.89[/C][C]5.90125[/C][C]5.96125[/C][C]-0.06[/C][C]-0.01125[/C][/ROW]
[ROW][C]33[/C][C]5.89[/C][C]5.90389[/C][C]5.97708[/C][C]-0.0731944[/C][C]-0.0138889[/C][/ROW]
[ROW][C]34[/C][C]6.08[/C][C]6.06486[/C][C]5.99292[/C][C]0.0719444[/C][C]0.0151389[/C][/ROW]
[ROW][C]35[/C][C]6.08[/C][C]6.0675[/C][C]6.00875[/C][C]0.05875[/C][C]0.0125[/C][/ROW]
[ROW][C]36[/C][C]6.08[/C][C]6.07014[/C][C]6.02458[/C][C]0.0455556[/C][C]0.00986111[/C][/ROW]
[ROW][C]37[/C][C]6.08[/C][C]6.07278[/C][C]6.04042[/C][C]0.0323611[/C][C]0.00722222[/C][/ROW]
[ROW][C]38[/C][C]6.08[/C][C]6.07542[/C][C]6.05625[/C][C]0.0191667[/C][C]0.00458333[/C][/ROW]
[ROW][C]39[/C][C]6.08[/C][C]6.07806[/C][C]6.07208[/C][C]0.00597222[/C][C]0.00194444[/C][/ROW]
[ROW][C]40[/C][C]6.08[/C][C]6.08194[/C][C]6.08833[/C][C]-0.00638889[/C][C]-0.00194444[/C][/ROW]
[ROW][C]41[/C][C]6.08[/C][C]6.08708[/C][C]6.105[/C][C]-0.0179167[/C][C]-0.00708333[/C][/ROW]
[ROW][C]42[/C][C]6.08[/C][C]6.09222[/C][C]6.12167[/C][C]-0.0294444[/C][C]-0.0122222[/C][/ROW]
[ROW][C]43[/C][C]6.08[/C][C]6.09153[/C][C]6.13833[/C][C]-0.0468056[/C][C]-0.0115278[/C][/ROW]
[ROW][C]44[/C][C]6.08[/C][C]6.095[/C][C]6.155[/C][C]-0.06[/C][C]-0.015[/C][/ROW]
[ROW][C]45[/C][C]6.08[/C][C]6.09847[/C][C]6.17167[/C][C]-0.0731944[/C][C]-0.0184722[/C][/ROW]
[ROW][C]46[/C][C]6.28[/C][C]6.26028[/C][C]6.18833[/C][C]0.0719444[/C][C]0.0197222[/C][/ROW]
[ROW][C]47[/C][C]6.28[/C][C]6.26375[/C][C]6.205[/C][C]0.05875[/C][C]0.01625[/C][/ROW]
[ROW][C]48[/C][C]6.28[/C][C]6.26722[/C][C]6.22167[/C][C]0.0455556[/C][C]0.0127778[/C][/ROW]
[ROW][C]49[/C][C]6.28[/C][C]6.27069[/C][C]6.23833[/C][C]0.0323611[/C][C]0.00930556[/C][/ROW]
[ROW][C]50[/C][C]6.28[/C][C]6.27417[/C][C]6.255[/C][C]0.0191667[/C][C]0.00583333[/C][/ROW]
[ROW][C]51[/C][C]6.28[/C][C]6.27764[/C][C]6.27167[/C][C]0.00597222[/C][C]0.00236111[/C][/ROW]
[ROW][C]52[/C][C]6.28[/C][C]6.27486[/C][C]6.28125[/C][C]-0.00638889[/C][C]0.00513889[/C][/ROW]
[ROW][C]53[/C][C]6.28[/C][C]6.26583[/C][C]6.28375[/C][C]-0.0179167[/C][C]0.0141667[/C][/ROW]
[ROW][C]54[/C][C]6.28[/C][C]6.25681[/C][C]6.28625[/C][C]-0.0294444[/C][C]0.0231944[/C][/ROW]
[ROW][C]55[/C][C]6.28[/C][C]6.24194[/C][C]6.28875[/C][C]-0.0468056[/C][C]0.0380556[/C][/ROW]
[ROW][C]56[/C][C]6.28[/C][C]6.23125[/C][C]6.29125[/C][C]-0.06[/C][C]0.04875[/C][/ROW]
[ROW][C]57[/C][C]6.28[/C][C]6.22056[/C][C]6.29375[/C][C]-0.0731944[/C][C]0.0594444[/C][/ROW]
[ROW][C]58[/C][C]6.31[/C][C]6.36819[/C][C]6.29625[/C][C]0.0719444[/C][C]-0.0581944[/C][/ROW]
[ROW][C]59[/C][C]6.31[/C][C]6.3575[/C][C]6.29875[/C][C]0.05875[/C][C]-0.0475[/C][/ROW]
[ROW][C]60[/C][C]6.31[/C][C]6.34681[/C][C]6.30125[/C][C]0.0455556[/C][C]-0.0368056[/C][/ROW]
[ROW][C]61[/C][C]6.31[/C][C]6.33611[/C][C]6.30375[/C][C]0.0323611[/C][C]-0.0261111[/C][/ROW]
[ROW][C]62[/C][C]6.31[/C][C]6.32542[/C][C]6.30625[/C][C]0.0191667[/C][C]-0.0154167[/C][/ROW]
[ROW][C]63[/C][C]6.31[/C][C]6.31472[/C][C]6.30875[/C][C]0.00597222[/C][C]-0.00472222[/C][/ROW]
[ROW][C]64[/C][C]6.31[/C][C]6.31069[/C][C]6.31708[/C][C]-0.00638889[/C][C]-0.000694444[/C][/ROW]
[ROW][C]65[/C][C]6.31[/C][C]6.31333[/C][C]6.33125[/C][C]-0.0179167[/C][C]-0.00333333[/C][/ROW]
[ROW][C]66[/C][C]6.31[/C][C]6.31597[/C][C]6.34542[/C][C]-0.0294444[/C][C]-0.00597222[/C][/ROW]
[ROW][C]67[/C][C]6.31[/C][C]6.31278[/C][C]6.35958[/C][C]-0.0468056[/C][C]-0.00277778[/C][/ROW]
[ROW][C]68[/C][C]6.31[/C][C]6.31375[/C][C]6.37375[/C][C]-0.06[/C][C]-0.00375[/C][/ROW]
[ROW][C]69[/C][C]6.31[/C][C]6.31472[/C][C]6.38792[/C][C]-0.0731944[/C][C]-0.00472222[/C][/ROW]
[ROW][C]70[/C][C]6.48[/C][C]6.47403[/C][C]6.40208[/C][C]0.0719444[/C][C]0.00597222[/C][/ROW]
[ROW][C]71[/C][C]6.48[/C][C]6.475[/C][C]6.41625[/C][C]0.05875[/C][C]0.005[/C][/ROW]
[ROW][C]72[/C][C]6.48[/C][C]6.47597[/C][C]6.43042[/C][C]0.0455556[/C][C]0.00402778[/C][/ROW]
[ROW][C]73[/C][C]6.48[/C][C]6.47694[/C][C]6.44458[/C][C]0.0323611[/C][C]0.00305556[/C][/ROW]
[ROW][C]74[/C][C]6.48[/C][C]6.47792[/C][C]6.45875[/C][C]0.0191667[/C][C]0.00208333[/C][/ROW]
[ROW][C]75[/C][C]6.48[/C][C]6.47889[/C][C]6.47292[/C][C]0.00597222[/C][C]0.00111111[/C][/ROW]
[ROW][C]76[/C][C]6.48[/C][C]6.47444[/C][C]6.48083[/C][C]-0.00638889[/C][C]0.00555556[/C][/ROW]
[ROW][C]77[/C][C]6.48[/C][C]6.46458[/C][C]6.4825[/C][C]-0.0179167[/C][C]0.0154167[/C][/ROW]
[ROW][C]78[/C][C]6.48[/C][C]6.45472[/C][C]6.48417[/C][C]-0.0294444[/C][C]0.0252778[/C][/ROW]
[ROW][C]79[/C][C]6.48[/C][C]NA[/C][C]NA[/C][C]-0.0468056[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]6.48[/C][C]NA[/C][C]NA[/C][C]-0.06[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]6.48[/C][C]NA[/C][C]NA[/C][C]-0.0731944[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]0.0719444[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]0.05875[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]0.0455556[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232264&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232264&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
15.53NANA0.0323611NA
25.53NANA0.0191667NA
35.53NANA0.00597222NA
45.53NANA-0.00638889NA
55.53NANA-0.0179167NA
65.53NANA-0.0294444NA
75.535.524035.57083-0.04680560.00597222
85.535.52255.5825-0.060.0075
95.535.520975.59417-0.07319440.00902778
105.675.677785.605830.0719444-0.00777778
115.675.676255.61750.05875-0.00625
125.675.674725.629170.0455556-0.00472222
135.675.673195.640830.0323611-0.00319444
145.675.671675.65250.0191667-0.00166667
155.675.670145.664170.00597222-0.000138889
165.675.672785.67917-0.00638889-0.00277778
175.675.679585.6975-0.0179167-0.00958333
185.675.686395.71583-0.0294444-0.0163889
195.675.687365.73417-0.0468056-0.0173611
205.675.69255.7525-0.06-0.0225
215.675.697645.77083-0.0731944-0.0276389
225.895.861115.789170.07194440.0288889
235.895.866255.80750.058750.02375
245.895.871395.825830.04555560.0186111
255.895.876535.844170.03236110.0134722
265.895.881675.86250.01916670.00833333
275.895.886815.880830.005972220.00319444
285.895.891535.89792-0.00638889-0.00152778
295.895.895835.91375-0.0179167-0.00583333
305.895.900145.92958-0.0294444-0.0101389
315.895.898615.94542-0.0468056-0.00861111
325.895.901255.96125-0.06-0.01125
335.895.903895.97708-0.0731944-0.0138889
346.086.064865.992920.07194440.0151389
356.086.06756.008750.058750.0125
366.086.070146.024580.04555560.00986111
376.086.072786.040420.03236110.00722222
386.086.075426.056250.01916670.00458333
396.086.078066.072080.005972220.00194444
406.086.081946.08833-0.00638889-0.00194444
416.086.087086.105-0.0179167-0.00708333
426.086.092226.12167-0.0294444-0.0122222
436.086.091536.13833-0.0468056-0.0115278
446.086.0956.155-0.06-0.015
456.086.098476.17167-0.0731944-0.0184722
466.286.260286.188330.07194440.0197222
476.286.263756.2050.058750.01625
486.286.267226.221670.04555560.0127778
496.286.270696.238330.03236110.00930556
506.286.274176.2550.01916670.00583333
516.286.277646.271670.005972220.00236111
526.286.274866.28125-0.006388890.00513889
536.286.265836.28375-0.01791670.0141667
546.286.256816.28625-0.02944440.0231944
556.286.241946.28875-0.04680560.0380556
566.286.231256.29125-0.060.04875
576.286.220566.29375-0.07319440.0594444
586.316.368196.296250.0719444-0.0581944
596.316.35756.298750.05875-0.0475
606.316.346816.301250.0455556-0.0368056
616.316.336116.303750.0323611-0.0261111
626.316.325426.306250.0191667-0.0154167
636.316.314726.308750.00597222-0.00472222
646.316.310696.31708-0.00638889-0.000694444
656.316.313336.33125-0.0179167-0.00333333
666.316.315976.34542-0.0294444-0.00597222
676.316.312786.35958-0.0468056-0.00277778
686.316.313756.37375-0.06-0.00375
696.316.314726.38792-0.0731944-0.00472222
706.486.474036.402080.07194440.00597222
716.486.4756.416250.058750.005
726.486.475976.430420.04555560.00402778
736.486.476946.444580.03236110.00305556
746.486.477926.458750.01916670.00208333
756.486.478896.472920.005972220.00111111
766.486.474446.48083-0.006388890.00555556
776.486.464586.4825-0.01791670.0154167
786.486.454726.48417-0.02944440.0252778
796.48NANA-0.0468056NA
806.48NANA-0.06NA
816.48NANA-0.0731944NA
826.5NANA0.0719444NA
836.5NANA0.05875NA
846.5NANA0.0455556NA



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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')