## Free Statistics

of Irreproducible Research!

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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 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 Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 seconds R Server 'George Udny Yule' @ yule.wessa.net

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

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

par2 <- as.numeric(par2)x <- ts(x,freq=par2)m <- decompose(x,type=par1)m$figurebitmap(file='test1.png')plot(m)dev.off()mylagmax <- length(x)/2bitmap(file='test2.png')op <- par(mfrow = c(2,2))acf(as.numeric(x),lag.max = mylagmax,main='Observed')acf(as.numeric(m$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')