## 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 05:14:07 -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/t1386843475r5zpb7e63sww2cm.htm/, Retrieved Tue, 07 Dec 2021 11:54:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232241, Retrieved Tue, 07 Dec 2021 11:54:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [] [2013-12-09 11:05:02] [520d9ebc87bc557903715fb12897748b]
- R PD    [Classical Decomposition] [] [2013-12-12 10:14:07] [17e53cb7c94beab0adf1165deaf51c6f] [Current]
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Dataseries X:
3.43
3.43
3.43
3.43
3.43
3.43
3.43
3.43
3.5
3.52
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.53
3.58
3.58
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.59
3.61
3.71
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.83
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.92
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
3.98
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.09
4.21
4.21
4.21
4.21

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 5 seconds R Server 'Gertrude Mary Cox' @ cox.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 & 5 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232241&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232241&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232241&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 5 seconds R Server 'Gertrude Mary Cox' @ cox.wessa.net

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 3.43 NA NA 0.0163079 NA 2 3.43 NA NA 0.0071412 NA 3 3.43 NA NA -0.00237269 NA 4 3.43 NA NA -0.0120949 NA 5 3.43 NA NA -0.0216088 NA 6 3.43 NA NA -0.0310532 NA 7 3.43 3.42547 3.46417 -0.0386921 0.00452546 8 3.43 3.42797 3.4725 -0.0445255 0.00202546 9 3.5 3.50714 3.48083 0.0263079 -0.0071412 10 3.52 3.52964 3.48917 0.0404745 -0.0096412 11 3.53 3.53214 3.4975 0.0346412 -0.0021412 12 3.53 3.53131 3.50583 0.0254745 -0.00130787 13 3.53 3.53047 3.51417 0.0163079 -0.000474537 14 3.53 3.52964 3.5225 0.0071412 0.000358796 15 3.53 3.52763 3.53 -0.00237269 0.00237269 16 3.53 3.52374 3.53583 -0.0120949 0.00626157 17 3.53 3.51922 3.54083 -0.0216088 0.0107755 18 3.53 3.51478 3.54583 -0.0310532 0.0152199 19 3.53 3.51214 3.55083 -0.0386921 0.0178588 20 3.53 3.51131 3.55583 -0.0445255 0.0186921 21 3.58 3.58714 3.56083 0.0263079 -0.0071412 22 3.58 3.60631 3.56583 0.0404745 -0.0263079 23 3.59 3.60547 3.57083 0.0346412 -0.0154745 24 3.59 3.60131 3.57583 0.0254745 -0.0113079 25 3.59 3.59714 3.58083 0.0163079 -0.0071412 26 3.59 3.59381 3.58667 0.0071412 -0.00380787 27 3.59 3.59304 3.59542 -0.00237269 -0.00304398 28 3.59 3.59916 3.61125 -0.0120949 -0.00915509 29 3.59 3.61006 3.63167 -0.0216088 -0.0200579 30 3.59 3.62061 3.65167 -0.0310532 -0.0306134 31 3.59 3.63297 3.67167 -0.0386921 -0.0429745 32 3.61 3.64714 3.69167 -0.0445255 -0.0371412 33 3.71 3.73797 3.71167 0.0263079 -0.0279745 34 3.83 3.77214 3.73167 0.0404745 0.0578588 35 3.83 3.78631 3.75167 0.0346412 0.0436921 36 3.83 3.79714 3.77167 0.0254745 0.0328588 37 3.83 3.80797 3.79167 0.0163079 0.0220255 38 3.83 3.81797 3.81083 0.0071412 0.0120255 39 3.83 3.82638 3.82875 -0.00237269 0.00362269 40 3.83 3.82916 3.84125 -0.0120949 0.000844907 41 3.83 3.82714 3.84875 -0.0216088 0.0028588 42 3.83 3.8252 3.85625 -0.0310532 0.00480324 43 3.83 3.82506 3.86375 -0.0386921 0.00494213 44 3.83 3.82672 3.87125 -0.0445255 0.00327546 45 3.92 3.90506 3.87875 0.0263079 0.0149421 46 3.92 3.92672 3.88625 0.0404745 -0.00672454 47 3.92 3.92839 3.89375 0.0346412 -0.0083912 48 3.92 3.92672 3.90125 0.0254745 -0.00672454 49 3.92 3.92506 3.90875 0.0163079 -0.00505787 50 3.92 3.92339 3.91625 0.0071412 -0.0033912 51 3.92 3.92013 3.9225 -0.00237269 -0.000127315 52 3.92 3.91541 3.9275 -0.0120949 0.00459491 53 3.92 3.91089 3.9325 -0.0216088 0.0091088 54 3.92 3.90645 3.9375 -0.0310532 0.0135532 55 3.92 3.90381 3.9425 -0.0386921 0.0161921 56 3.92 3.90297 3.9475 -0.0445255 0.0170255 57 3.98 3.97881 3.9525 0.0263079 0.00119213 58 3.98 3.99797 3.9575 0.0404745 -0.0179745 59 3.98 3.99714 3.9625 0.0346412 -0.0171412 60 3.98 3.99297 3.9675 0.0254745 -0.0129745 61 3.98 3.98881 3.9725 0.0163079 -0.00880787 62 3.98 3.98464 3.9775 0.0071412 -0.0046412 63 3.98 3.98221 3.98458 -0.00237269 -0.00221065 64 3.98 3.98166 3.99375 -0.0120949 -0.00165509 65 3.98 3.98131 4.00292 -0.0216088 -0.00130787 66 3.98 3.98103 4.01208 -0.0310532 -0.00103009 67 3.98 3.98256 4.02125 -0.0386921 -0.00255787 68 3.98 3.98589 4.03042 -0.0445255 -0.0058912 69 4.09 4.06589 4.03958 0.0263079 0.0241088 70 4.09 4.08922 4.04875 0.0404745 0.000775463 71 4.09 4.09256 4.05792 0.0346412 -0.00255787 72 4.09 4.09256 4.06708 0.0254745 -0.00255787 73 4.09 4.09256 4.07625 0.0163079 -0.00255787 74 4.09 4.09256 4.08542 0.0071412 -0.00255787 75 4.09 4.09263 4.095 -0.00237269 -0.00262731 76 4.09 4.09291 4.105 -0.0120949 -0.00290509 77 4.09 4.09339 4.115 -0.0216088 -0.0033912 78 4.09 4.09395 4.125 -0.0310532 -0.00394676 79 4.09 NA NA -0.0386921 NA 80 4.09 NA NA -0.0445255 NA 81 4.21 NA NA 0.0263079 NA 82 4.21 NA NA 0.0404745 NA 83 4.21 NA NA 0.0346412 NA 84 4.21 NA NA 0.0254745 NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 3.43 & NA & NA & 0.0163079 & NA \tabularnewline
2 & 3.43 & NA & NA & 0.0071412 & NA \tabularnewline
3 & 3.43 & NA & NA & -0.00237269 & NA \tabularnewline
4 & 3.43 & NA & NA & -0.0120949 & NA \tabularnewline
5 & 3.43 & NA & NA & -0.0216088 & NA \tabularnewline
6 & 3.43 & NA & NA & -0.0310532 & NA \tabularnewline
7 & 3.43 & 3.42547 & 3.46417 & -0.0386921 & 0.00452546 \tabularnewline
8 & 3.43 & 3.42797 & 3.4725 & -0.0445255 & 0.00202546 \tabularnewline
9 & 3.5 & 3.50714 & 3.48083 & 0.0263079 & -0.0071412 \tabularnewline
10 & 3.52 & 3.52964 & 3.48917 & 0.0404745 & -0.0096412 \tabularnewline
11 & 3.53 & 3.53214 & 3.4975 & 0.0346412 & -0.0021412 \tabularnewline
12 & 3.53 & 3.53131 & 3.50583 & 0.0254745 & -0.00130787 \tabularnewline
13 & 3.53 & 3.53047 & 3.51417 & 0.0163079 & -0.000474537 \tabularnewline
14 & 3.53 & 3.52964 & 3.5225 & 0.0071412 & 0.000358796 \tabularnewline
15 & 3.53 & 3.52763 & 3.53 & -0.00237269 & 0.00237269 \tabularnewline
16 & 3.53 & 3.52374 & 3.53583 & -0.0120949 & 0.00626157 \tabularnewline
17 & 3.53 & 3.51922 & 3.54083 & -0.0216088 & 0.0107755 \tabularnewline
18 & 3.53 & 3.51478 & 3.54583 & -0.0310532 & 0.0152199 \tabularnewline
19 & 3.53 & 3.51214 & 3.55083 & -0.0386921 & 0.0178588 \tabularnewline
20 & 3.53 & 3.51131 & 3.55583 & -0.0445255 & 0.0186921 \tabularnewline
21 & 3.58 & 3.58714 & 3.56083 & 0.0263079 & -0.0071412 \tabularnewline
22 & 3.58 & 3.60631 & 3.56583 & 0.0404745 & -0.0263079 \tabularnewline
23 & 3.59 & 3.60547 & 3.57083 & 0.0346412 & -0.0154745 \tabularnewline
24 & 3.59 & 3.60131 & 3.57583 & 0.0254745 & -0.0113079 \tabularnewline
25 & 3.59 & 3.59714 & 3.58083 & 0.0163079 & -0.0071412 \tabularnewline
26 & 3.59 & 3.59381 & 3.58667 & 0.0071412 & -0.00380787 \tabularnewline
27 & 3.59 & 3.59304 & 3.59542 & -0.00237269 & -0.00304398 \tabularnewline
28 & 3.59 & 3.59916 & 3.61125 & -0.0120949 & -0.00915509 \tabularnewline
29 & 3.59 & 3.61006 & 3.63167 & -0.0216088 & -0.0200579 \tabularnewline
30 & 3.59 & 3.62061 & 3.65167 & -0.0310532 & -0.0306134 \tabularnewline
31 & 3.59 & 3.63297 & 3.67167 & -0.0386921 & -0.0429745 \tabularnewline
32 & 3.61 & 3.64714 & 3.69167 & -0.0445255 & -0.0371412 \tabularnewline
33 & 3.71 & 3.73797 & 3.71167 & 0.0263079 & -0.0279745 \tabularnewline
34 & 3.83 & 3.77214 & 3.73167 & 0.0404745 & 0.0578588 \tabularnewline
35 & 3.83 & 3.78631 & 3.75167 & 0.0346412 & 0.0436921 \tabularnewline
36 & 3.83 & 3.79714 & 3.77167 & 0.0254745 & 0.0328588 \tabularnewline
37 & 3.83 & 3.80797 & 3.79167 & 0.0163079 & 0.0220255 \tabularnewline
38 & 3.83 & 3.81797 & 3.81083 & 0.0071412 & 0.0120255 \tabularnewline
39 & 3.83 & 3.82638 & 3.82875 & -0.00237269 & 0.00362269 \tabularnewline
40 & 3.83 & 3.82916 & 3.84125 & -0.0120949 & 0.000844907 \tabularnewline
41 & 3.83 & 3.82714 & 3.84875 & -0.0216088 & 0.0028588 \tabularnewline
42 & 3.83 & 3.8252 & 3.85625 & -0.0310532 & 0.00480324 \tabularnewline
43 & 3.83 & 3.82506 & 3.86375 & -0.0386921 & 0.00494213 \tabularnewline
44 & 3.83 & 3.82672 & 3.87125 & -0.0445255 & 0.00327546 \tabularnewline
45 & 3.92 & 3.90506 & 3.87875 & 0.0263079 & 0.0149421 \tabularnewline
46 & 3.92 & 3.92672 & 3.88625 & 0.0404745 & -0.00672454 \tabularnewline
47 & 3.92 & 3.92839 & 3.89375 & 0.0346412 & -0.0083912 \tabularnewline
48 & 3.92 & 3.92672 & 3.90125 & 0.0254745 & -0.00672454 \tabularnewline
49 & 3.92 & 3.92506 & 3.90875 & 0.0163079 & -0.00505787 \tabularnewline
50 & 3.92 & 3.92339 & 3.91625 & 0.0071412 & -0.0033912 \tabularnewline
51 & 3.92 & 3.92013 & 3.9225 & -0.00237269 & -0.000127315 \tabularnewline
52 & 3.92 & 3.91541 & 3.9275 & -0.0120949 & 0.00459491 \tabularnewline
53 & 3.92 & 3.91089 & 3.9325 & -0.0216088 & 0.0091088 \tabularnewline
54 & 3.92 & 3.90645 & 3.9375 & -0.0310532 & 0.0135532 \tabularnewline
55 & 3.92 & 3.90381 & 3.9425 & -0.0386921 & 0.0161921 \tabularnewline
56 & 3.92 & 3.90297 & 3.9475 & -0.0445255 & 0.0170255 \tabularnewline
57 & 3.98 & 3.97881 & 3.9525 & 0.0263079 & 0.00119213 \tabularnewline
58 & 3.98 & 3.99797 & 3.9575 & 0.0404745 & -0.0179745 \tabularnewline
59 & 3.98 & 3.99714 & 3.9625 & 0.0346412 & -0.0171412 \tabularnewline
60 & 3.98 & 3.99297 & 3.9675 & 0.0254745 & -0.0129745 \tabularnewline
61 & 3.98 & 3.98881 & 3.9725 & 0.0163079 & -0.00880787 \tabularnewline
62 & 3.98 & 3.98464 & 3.9775 & 0.0071412 & -0.0046412 \tabularnewline
63 & 3.98 & 3.98221 & 3.98458 & -0.00237269 & -0.00221065 \tabularnewline
64 & 3.98 & 3.98166 & 3.99375 & -0.0120949 & -0.00165509 \tabularnewline
65 & 3.98 & 3.98131 & 4.00292 & -0.0216088 & -0.00130787 \tabularnewline
66 & 3.98 & 3.98103 & 4.01208 & -0.0310532 & -0.00103009 \tabularnewline
67 & 3.98 & 3.98256 & 4.02125 & -0.0386921 & -0.00255787 \tabularnewline
68 & 3.98 & 3.98589 & 4.03042 & -0.0445255 & -0.0058912 \tabularnewline
69 & 4.09 & 4.06589 & 4.03958 & 0.0263079 & 0.0241088 \tabularnewline
70 & 4.09 & 4.08922 & 4.04875 & 0.0404745 & 0.000775463 \tabularnewline
71 & 4.09 & 4.09256 & 4.05792 & 0.0346412 & -0.00255787 \tabularnewline
72 & 4.09 & 4.09256 & 4.06708 & 0.0254745 & -0.00255787 \tabularnewline
73 & 4.09 & 4.09256 & 4.07625 & 0.0163079 & -0.00255787 \tabularnewline
74 & 4.09 & 4.09256 & 4.08542 & 0.0071412 & -0.00255787 \tabularnewline
75 & 4.09 & 4.09263 & 4.095 & -0.00237269 & -0.00262731 \tabularnewline
76 & 4.09 & 4.09291 & 4.105 & -0.0120949 & -0.00290509 \tabularnewline
77 & 4.09 & 4.09339 & 4.115 & -0.0216088 & -0.0033912 \tabularnewline
78 & 4.09 & 4.09395 & 4.125 & -0.0310532 & -0.00394676 \tabularnewline
79 & 4.09 & NA & NA & -0.0386921 & NA \tabularnewline
80 & 4.09 & NA & NA & -0.0445255 & NA \tabularnewline
81 & 4.21 & NA & NA & 0.0263079 & NA \tabularnewline
82 & 4.21 & NA & NA & 0.0404745 & NA \tabularnewline
83 & 4.21 & NA & NA & 0.0346412 & NA \tabularnewline
84 & 4.21 & NA & NA & 0.0254745 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232241&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]3.43[/C][C]NA[/C][C]NA[/C][C]0.0163079[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3.43[/C][C]NA[/C][C]NA[/C][C]0.0071412[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.43[/C][C]NA[/C][C]NA[/C][C]-0.00237269[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3.43[/C][C]NA[/C][C]NA[/C][C]-0.0120949[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3.43[/C][C]NA[/C][C]NA[/C][C]-0.0216088[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3.43[/C][C]NA[/C][C]NA[/C][C]-0.0310532[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3.43[/C][C]3.42547[/C][C]3.46417[/C][C]-0.0386921[/C][C]0.00452546[/C][/ROW]
[ROW][C]8[/C][C]3.43[/C][C]3.42797[/C][C]3.4725[/C][C]-0.0445255[/C][C]0.00202546[/C][/ROW]
[ROW][C]9[/C][C]3.5[/C][C]3.50714[/C][C]3.48083[/C][C]0.0263079[/C][C]-0.0071412[/C][/ROW]
[ROW][C]10[/C][C]3.52[/C][C]3.52964[/C][C]3.48917[/C][C]0.0404745[/C][C]-0.0096412[/C][/ROW]
[ROW][C]11[/C][C]3.53[/C][C]3.53214[/C][C]3.4975[/C][C]0.0346412[/C][C]-0.0021412[/C][/ROW]
[ROW][C]12[/C][C]3.53[/C][C]3.53131[/C][C]3.50583[/C][C]0.0254745[/C][C]-0.00130787[/C][/ROW]
[ROW][C]13[/C][C]3.53[/C][C]3.53047[/C][C]3.51417[/C][C]0.0163079[/C][C]-0.000474537[/C][/ROW]
[ROW][C]14[/C][C]3.53[/C][C]3.52964[/C][C]3.5225[/C][C]0.0071412[/C][C]0.000358796[/C][/ROW]
[ROW][C]15[/C][C]3.53[/C][C]3.52763[/C][C]3.53[/C][C]-0.00237269[/C][C]0.00237269[/C][/ROW]
[ROW][C]16[/C][C]3.53[/C][C]3.52374[/C][C]3.53583[/C][C]-0.0120949[/C][C]0.00626157[/C][/ROW]
[ROW][C]17[/C][C]3.53[/C][C]3.51922[/C][C]3.54083[/C][C]-0.0216088[/C][C]0.0107755[/C][/ROW]
[ROW][C]18[/C][C]3.53[/C][C]3.51478[/C][C]3.54583[/C][C]-0.0310532[/C][C]0.0152199[/C][/ROW]
[ROW][C]19[/C][C]3.53[/C][C]3.51214[/C][C]3.55083[/C][C]-0.0386921[/C][C]0.0178588[/C][/ROW]
[ROW][C]20[/C][C]3.53[/C][C]3.51131[/C][C]3.55583[/C][C]-0.0445255[/C][C]0.0186921[/C][/ROW]
[ROW][C]21[/C][C]3.58[/C][C]3.58714[/C][C]3.56083[/C][C]0.0263079[/C][C]-0.0071412[/C][/ROW]
[ROW][C]22[/C][C]3.58[/C][C]3.60631[/C][C]3.56583[/C][C]0.0404745[/C][C]-0.0263079[/C][/ROW]
[ROW][C]23[/C][C]3.59[/C][C]3.60547[/C][C]3.57083[/C][C]0.0346412[/C][C]-0.0154745[/C][/ROW]
[ROW][C]24[/C][C]3.59[/C][C]3.60131[/C][C]3.57583[/C][C]0.0254745[/C][C]-0.0113079[/C][/ROW]
[ROW][C]25[/C][C]3.59[/C][C]3.59714[/C][C]3.58083[/C][C]0.0163079[/C][C]-0.0071412[/C][/ROW]
[ROW][C]26[/C][C]3.59[/C][C]3.59381[/C][C]3.58667[/C][C]0.0071412[/C][C]-0.00380787[/C][/ROW]
[ROW][C]27[/C][C]3.59[/C][C]3.59304[/C][C]3.59542[/C][C]-0.00237269[/C][C]-0.00304398[/C][/ROW]
[ROW][C]28[/C][C]3.59[/C][C]3.59916[/C][C]3.61125[/C][C]-0.0120949[/C][C]-0.00915509[/C][/ROW]
[ROW][C]29[/C][C]3.59[/C][C]3.61006[/C][C]3.63167[/C][C]-0.0216088[/C][C]-0.0200579[/C][/ROW]
[ROW][C]30[/C][C]3.59[/C][C]3.62061[/C][C]3.65167[/C][C]-0.0310532[/C][C]-0.0306134[/C][/ROW]
[ROW][C]31[/C][C]3.59[/C][C]3.63297[/C][C]3.67167[/C][C]-0.0386921[/C][C]-0.0429745[/C][/ROW]
[ROW][C]32[/C][C]3.61[/C][C]3.64714[/C][C]3.69167[/C][C]-0.0445255[/C][C]-0.0371412[/C][/ROW]
[ROW][C]33[/C][C]3.71[/C][C]3.73797[/C][C]3.71167[/C][C]0.0263079[/C][C]-0.0279745[/C][/ROW]
[ROW][C]34[/C][C]3.83[/C][C]3.77214[/C][C]3.73167[/C][C]0.0404745[/C][C]0.0578588[/C][/ROW]
[ROW][C]35[/C][C]3.83[/C][C]3.78631[/C][C]3.75167[/C][C]0.0346412[/C][C]0.0436921[/C][/ROW]
[ROW][C]36[/C][C]3.83[/C][C]3.79714[/C][C]3.77167[/C][C]0.0254745[/C][C]0.0328588[/C][/ROW]
[ROW][C]37[/C][C]3.83[/C][C]3.80797[/C][C]3.79167[/C][C]0.0163079[/C][C]0.0220255[/C][/ROW]
[ROW][C]38[/C][C]3.83[/C][C]3.81797[/C][C]3.81083[/C][C]0.0071412[/C][C]0.0120255[/C][/ROW]
[ROW][C]39[/C][C]3.83[/C][C]3.82638[/C][C]3.82875[/C][C]-0.00237269[/C][C]0.00362269[/C][/ROW]
[ROW][C]40[/C][C]3.83[/C][C]3.82916[/C][C]3.84125[/C][C]-0.0120949[/C][C]0.000844907[/C][/ROW]
[ROW][C]41[/C][C]3.83[/C][C]3.82714[/C][C]3.84875[/C][C]-0.0216088[/C][C]0.0028588[/C][/ROW]
[ROW][C]42[/C][C]3.83[/C][C]3.8252[/C][C]3.85625[/C][C]-0.0310532[/C][C]0.00480324[/C][/ROW]
[ROW][C]43[/C][C]3.83[/C][C]3.82506[/C][C]3.86375[/C][C]-0.0386921[/C][C]0.00494213[/C][/ROW]
[ROW][C]44[/C][C]3.83[/C][C]3.82672[/C][C]3.87125[/C][C]-0.0445255[/C][C]0.00327546[/C][/ROW]
[ROW][C]45[/C][C]3.92[/C][C]3.90506[/C][C]3.87875[/C][C]0.0263079[/C][C]0.0149421[/C][/ROW]
[ROW][C]46[/C][C]3.92[/C][C]3.92672[/C][C]3.88625[/C][C]0.0404745[/C][C]-0.00672454[/C][/ROW]
[ROW][C]47[/C][C]3.92[/C][C]3.92839[/C][C]3.89375[/C][C]0.0346412[/C][C]-0.0083912[/C][/ROW]
[ROW][C]48[/C][C]3.92[/C][C]3.92672[/C][C]3.90125[/C][C]0.0254745[/C][C]-0.00672454[/C][/ROW]
[ROW][C]49[/C][C]3.92[/C][C]3.92506[/C][C]3.90875[/C][C]0.0163079[/C][C]-0.00505787[/C][/ROW]
[ROW][C]50[/C][C]3.92[/C][C]3.92339[/C][C]3.91625[/C][C]0.0071412[/C][C]-0.0033912[/C][/ROW]
[ROW][C]51[/C][C]3.92[/C][C]3.92013[/C][C]3.9225[/C][C]-0.00237269[/C][C]-0.000127315[/C][/ROW]
[ROW][C]52[/C][C]3.92[/C][C]3.91541[/C][C]3.9275[/C][C]-0.0120949[/C][C]0.00459491[/C][/ROW]
[ROW][C]53[/C][C]3.92[/C][C]3.91089[/C][C]3.9325[/C][C]-0.0216088[/C][C]0.0091088[/C][/ROW]
[ROW][C]54[/C][C]3.92[/C][C]3.90645[/C][C]3.9375[/C][C]-0.0310532[/C][C]0.0135532[/C][/ROW]
[ROW][C]55[/C][C]3.92[/C][C]3.90381[/C][C]3.9425[/C][C]-0.0386921[/C][C]0.0161921[/C][/ROW]
[ROW][C]56[/C][C]3.92[/C][C]3.90297[/C][C]3.9475[/C][C]-0.0445255[/C][C]0.0170255[/C][/ROW]
[ROW][C]57[/C][C]3.98[/C][C]3.97881[/C][C]3.9525[/C][C]0.0263079[/C][C]0.00119213[/C][/ROW]
[ROW][C]58[/C][C]3.98[/C][C]3.99797[/C][C]3.9575[/C][C]0.0404745[/C][C]-0.0179745[/C][/ROW]
[ROW][C]59[/C][C]3.98[/C][C]3.99714[/C][C]3.9625[/C][C]0.0346412[/C][C]-0.0171412[/C][/ROW]
[ROW][C]60[/C][C]3.98[/C][C]3.99297[/C][C]3.9675[/C][C]0.0254745[/C][C]-0.0129745[/C][/ROW]
[ROW][C]61[/C][C]3.98[/C][C]3.98881[/C][C]3.9725[/C][C]0.0163079[/C][C]-0.00880787[/C][/ROW]
[ROW][C]62[/C][C]3.98[/C][C]3.98464[/C][C]3.9775[/C][C]0.0071412[/C][C]-0.0046412[/C][/ROW]
[ROW][C]63[/C][C]3.98[/C][C]3.98221[/C][C]3.98458[/C][C]-0.00237269[/C][C]-0.00221065[/C][/ROW]
[ROW][C]64[/C][C]3.98[/C][C]3.98166[/C][C]3.99375[/C][C]-0.0120949[/C][C]-0.00165509[/C][/ROW]
[ROW][C]65[/C][C]3.98[/C][C]3.98131[/C][C]4.00292[/C][C]-0.0216088[/C][C]-0.00130787[/C][/ROW]
[ROW][C]66[/C][C]3.98[/C][C]3.98103[/C][C]4.01208[/C][C]-0.0310532[/C][C]-0.00103009[/C][/ROW]
[ROW][C]67[/C][C]3.98[/C][C]3.98256[/C][C]4.02125[/C][C]-0.0386921[/C][C]-0.00255787[/C][/ROW]
[ROW][C]68[/C][C]3.98[/C][C]3.98589[/C][C]4.03042[/C][C]-0.0445255[/C][C]-0.0058912[/C][/ROW]
[ROW][C]69[/C][C]4.09[/C][C]4.06589[/C][C]4.03958[/C][C]0.0263079[/C][C]0.0241088[/C][/ROW]
[ROW][C]70[/C][C]4.09[/C][C]4.08922[/C][C]4.04875[/C][C]0.0404745[/C][C]0.000775463[/C][/ROW]
[ROW][C]71[/C][C]4.09[/C][C]4.09256[/C][C]4.05792[/C][C]0.0346412[/C][C]-0.00255787[/C][/ROW]
[ROW][C]72[/C][C]4.09[/C][C]4.09256[/C][C]4.06708[/C][C]0.0254745[/C][C]-0.00255787[/C][/ROW]
[ROW][C]73[/C][C]4.09[/C][C]4.09256[/C][C]4.07625[/C][C]0.0163079[/C][C]-0.00255787[/C][/ROW]
[ROW][C]74[/C][C]4.09[/C][C]4.09256[/C][C]4.08542[/C][C]0.0071412[/C][C]-0.00255787[/C][/ROW]
[ROW][C]75[/C][C]4.09[/C][C]4.09263[/C][C]4.095[/C][C]-0.00237269[/C][C]-0.00262731[/C][/ROW]
[ROW][C]76[/C][C]4.09[/C][C]4.09291[/C][C]4.105[/C][C]-0.0120949[/C][C]-0.00290509[/C][/ROW]
[ROW][C]77[/C][C]4.09[/C][C]4.09339[/C][C]4.115[/C][C]-0.0216088[/C][C]-0.0033912[/C][/ROW]
[ROW][C]78[/C][C]4.09[/C][C]4.09395[/C][C]4.125[/C][C]-0.0310532[/C][C]-0.00394676[/C][/ROW]
[ROW][C]79[/C][C]4.09[/C][C]NA[/C][C]NA[/C][C]-0.0386921[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]4.09[/C][C]NA[/C][C]NA[/C][C]-0.0445255[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]0.0263079[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]0.0404745[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]0.0346412[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]4.21[/C][C]NA[/C][C]NA[/C][C]0.0254745[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232241&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232241&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 3.43 NA NA 0.0163079 NA 2 3.43 NA NA 0.0071412 NA 3 3.43 NA NA -0.00237269 NA 4 3.43 NA NA -0.0120949 NA 5 3.43 NA NA -0.0216088 NA 6 3.43 NA NA -0.0310532 NA 7 3.43 3.42547 3.46417 -0.0386921 0.00452546 8 3.43 3.42797 3.4725 -0.0445255 0.00202546 9 3.5 3.50714 3.48083 0.0263079 -0.0071412 10 3.52 3.52964 3.48917 0.0404745 -0.0096412 11 3.53 3.53214 3.4975 0.0346412 -0.0021412 12 3.53 3.53131 3.50583 0.0254745 -0.00130787 13 3.53 3.53047 3.51417 0.0163079 -0.000474537 14 3.53 3.52964 3.5225 0.0071412 0.000358796 15 3.53 3.52763 3.53 -0.00237269 0.00237269 16 3.53 3.52374 3.53583 -0.0120949 0.00626157 17 3.53 3.51922 3.54083 -0.0216088 0.0107755 18 3.53 3.51478 3.54583 -0.0310532 0.0152199 19 3.53 3.51214 3.55083 -0.0386921 0.0178588 20 3.53 3.51131 3.55583 -0.0445255 0.0186921 21 3.58 3.58714 3.56083 0.0263079 -0.0071412 22 3.58 3.60631 3.56583 0.0404745 -0.0263079 23 3.59 3.60547 3.57083 0.0346412 -0.0154745 24 3.59 3.60131 3.57583 0.0254745 -0.0113079 25 3.59 3.59714 3.58083 0.0163079 -0.0071412 26 3.59 3.59381 3.58667 0.0071412 -0.00380787 27 3.59 3.59304 3.59542 -0.00237269 -0.00304398 28 3.59 3.59916 3.61125 -0.0120949 -0.00915509 29 3.59 3.61006 3.63167 -0.0216088 -0.0200579 30 3.59 3.62061 3.65167 -0.0310532 -0.0306134 31 3.59 3.63297 3.67167 -0.0386921 -0.0429745 32 3.61 3.64714 3.69167 -0.0445255 -0.0371412 33 3.71 3.73797 3.71167 0.0263079 -0.0279745 34 3.83 3.77214 3.73167 0.0404745 0.0578588 35 3.83 3.78631 3.75167 0.0346412 0.0436921 36 3.83 3.79714 3.77167 0.0254745 0.0328588 37 3.83 3.80797 3.79167 0.0163079 0.0220255 38 3.83 3.81797 3.81083 0.0071412 0.0120255 39 3.83 3.82638 3.82875 -0.00237269 0.00362269 40 3.83 3.82916 3.84125 -0.0120949 0.000844907 41 3.83 3.82714 3.84875 -0.0216088 0.0028588 42 3.83 3.8252 3.85625 -0.0310532 0.00480324 43 3.83 3.82506 3.86375 -0.0386921 0.00494213 44 3.83 3.82672 3.87125 -0.0445255 0.00327546 45 3.92 3.90506 3.87875 0.0263079 0.0149421 46 3.92 3.92672 3.88625 0.0404745 -0.00672454 47 3.92 3.92839 3.89375 0.0346412 -0.0083912 48 3.92 3.92672 3.90125 0.0254745 -0.00672454 49 3.92 3.92506 3.90875 0.0163079 -0.00505787 50 3.92 3.92339 3.91625 0.0071412 -0.0033912 51 3.92 3.92013 3.9225 -0.00237269 -0.000127315 52 3.92 3.91541 3.9275 -0.0120949 0.00459491 53 3.92 3.91089 3.9325 -0.0216088 0.0091088 54 3.92 3.90645 3.9375 -0.0310532 0.0135532 55 3.92 3.90381 3.9425 -0.0386921 0.0161921 56 3.92 3.90297 3.9475 -0.0445255 0.0170255 57 3.98 3.97881 3.9525 0.0263079 0.00119213 58 3.98 3.99797 3.9575 0.0404745 -0.0179745 59 3.98 3.99714 3.9625 0.0346412 -0.0171412 60 3.98 3.99297 3.9675 0.0254745 -0.0129745 61 3.98 3.98881 3.9725 0.0163079 -0.00880787 62 3.98 3.98464 3.9775 0.0071412 -0.0046412 63 3.98 3.98221 3.98458 -0.00237269 -0.00221065 64 3.98 3.98166 3.99375 -0.0120949 -0.00165509 65 3.98 3.98131 4.00292 -0.0216088 -0.00130787 66 3.98 3.98103 4.01208 -0.0310532 -0.00103009 67 3.98 3.98256 4.02125 -0.0386921 -0.00255787 68 3.98 3.98589 4.03042 -0.0445255 -0.0058912 69 4.09 4.06589 4.03958 0.0263079 0.0241088 70 4.09 4.08922 4.04875 0.0404745 0.000775463 71 4.09 4.09256 4.05792 0.0346412 -0.00255787 72 4.09 4.09256 4.06708 0.0254745 -0.00255787 73 4.09 4.09256 4.07625 0.0163079 -0.00255787 74 4.09 4.09256 4.08542 0.0071412 -0.00255787 75 4.09 4.09263 4.095 -0.00237269 -0.00262731 76 4.09 4.09291 4.105 -0.0120949 -0.00290509 77 4.09 4.09339 4.115 -0.0216088 -0.0033912 78 4.09 4.09395 4.125 -0.0310532 -0.00394676 79 4.09 NA NA -0.0386921 NA 80 4.09 NA NA -0.0445255 NA 81 4.21 NA NA 0.0263079 NA 82 4.21 NA NA 0.0404745 NA 83 4.21 NA NA 0.0346412 NA 84 4.21 NA NA 0.0254745 NA

par2 <- '12'par1 <- 'additive'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')