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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 12 Dec 2013 13:16:36 -0500

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Statistical 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 Thu, 18 Apr 2024 17:19:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232264, Retrieved Thu, 18 Apr 2024 17:19:48 +0000

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-       [Classical Decomposition] [] [2013-12-12 18:16:36] [2e53d6acb0d55ba82adefb1cb5f89cf8] [Current]

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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

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code