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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 15 Dec 2014 21:50:17 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418680280lxve0pufxl913l3.htm/, Retrieved Thu, 16 May 2024 13:58:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269061, Retrieved Thu, 16 May 2024 13:58:01 +0000

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-       [Classical Decomposition] [] [2014-12-15 21:50:17] [77e76d07a5b02a0482982fb19d5d5436] [Current]
- R PD    [Classical Decomposition] [] [2014-12-16 20:42:48] [8ae5f3921d0f515f24933d117e773272] 

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269061&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269061&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269061&T=0

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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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	21.94	NA	NA	1.00073	NA
2	21.95	NA	NA	0.996968	NA
3	21.96	NA	NA	0.997982	NA
4	22.1	NA	NA	0.997544	NA
5	22.13	NA	NA	0.99625	NA
6	22.18	NA	NA	0.997814	NA
7	22.18	22.091	22.1017	0.999517	1.00403
8	22.27	22.1727	22.1112	1.00278	1.00439
9	22.3	22.1995	22.1162	1.00376	1.00453
10	22.04	22.138	22.1138	1.0011	0.995571
11	22.05	22.1699	22.1087	1.00277	0.994591
12	22.06	22.1661	22.1046	1.00278	0.995213
13	22.06	22.1166	22.1004	1.00073	0.997439
14	22.06	22.0367	22.1037	0.996968	1.00106
15	21.97	22.0687	22.1133	0.997982	0.995527
16	22.03	22.0665	22.1208	0.997544	0.998346
17	22.08	22.0483	22.1312	0.99625	1.00144
18	22.13	22.0933	22.1417	0.997814	1.00166
19	22.13	22.1376	22.1483	0.999517	0.999655
20	22.4	22.2186	22.1571	1.00278	1.00816
21	22.4	22.2593	22.1758	1.00376	1.00632
22	22.12	22.2223	22.1979	1.0011	0.995396
23	22.22	22.2756	22.2142	1.00277	0.997503
24	22.14	22.2902	22.2283	1.00278	0.993261
25	22.14	22.258	22.2417	1.00073	0.994699
26	22.19	22.1763	22.2438	0.996968	1.00062
27	22.29	22.1897	22.2346	0.997982	1.00452
28	22.24	22.185	22.2396	0.997544	1.00248
29	22.26	22.1728	22.2562	0.99625	1.00393
30	22.29	22.2267	22.2754	0.997814	1.00285
31	22.29	22.2888	22.2996	0.999517	1.00005
32	22.29	22.3703	22.3083	1.00278	0.99641
33	22.29	22.3818	22.2979	1.00376	0.995897
34	22.35	22.3074	22.2829	1.0011	1.00191
35	22.39	22.3278	22.2663	1.00277	1.00278
36	22.43	22.3107	22.2488	1.00278	1.00535
37	22.43	22.2476	22.2313	1.00073	1.0082
38	22.11	22.1468	22.2142	0.996968	0.998338
39	22.12	22.1527	22.1975	0.997982	0.998524
40	22.05	22.1301	22.1846	0.997544	0.996381
41	22.05	22.091	22.1742	0.99625	0.998143
42	22.08	22.112	22.1604	0.997814	0.998554
43	22.08	22.1339	22.1446	0.999517	0.997565
44	22.09	22.204	22.1425	1.00278	0.994865
45	22.09	22.2384	22.155	1.00376	0.993328
46	22.24	22.1935	22.1692	1.0011	1.00209
47	22.25	22.248	22.1867	1.00277	1.00009
48	22.24	22.2681	22.2062	1.00278	0.99874
49	22.24	22.2417	22.2254	1.00073	0.999922
50	22.25	22.1767	22.2442	0.996968	1.0033
51	22.28	22.2209	22.2658	0.997982	1.00266
52	22.23	22.2311	22.2858	0.997544	0.999951
53	22.29	22.2168	22.3004	0.99625	1.0033
54	22.31	22.2662	22.315	0.997814	1.00197
55	22.31	22.308	22.3187	0.999517	1.00009
56	22.31	22.3645	22.3025	1.00278	0.997565
57	22.39	22.3605	22.2767	1.00376	1.00132
58	22.42	22.277	22.2525	1.0011	1.00642
59	22.42	22.2769	22.2154	1.00277	1.00643
60	22.42	22.2238	22.1621	1.00278	1.00883
61	22.15	22.125	22.1088	1.00073	1.00113
62	21.95	21.9923	22.0592	0.996968	0.998077
63	21.96	21.9564	22.0008	0.997982	1.00016
64	21.97	21.8774	21.9312	0.997544	1.00423
65	21.66	21.778	21.86	0.99625	0.994581
66	21.66	21.739	21.7867	0.997814	0.996364
67	21.68	NA	NA	0.999517	NA
68	21.75	NA	NA	1.00278	NA
69	21.55	NA	NA	1.00376	NA
70	21.59	NA	NA	1.0011	NA
71	21.54	NA	NA	1.00277	NA
72	21.54	NA	NA	1.00278	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 21.94 & NA & NA & 1.00073 & NA \tabularnewline
2 & 21.95 & NA & NA & 0.996968 & NA \tabularnewline
3 & 21.96 & NA & NA & 0.997982 & NA \tabularnewline
4 & 22.1 & NA & NA & 0.997544 & NA \tabularnewline
5 & 22.13 & NA & NA & 0.99625 & NA \tabularnewline
6 & 22.18 & NA & NA & 0.997814 & NA \tabularnewline
7 & 22.18 & 22.091 & 22.1017 & 0.999517 & 1.00403 \tabularnewline
8 & 22.27 & 22.1727 & 22.1112 & 1.00278 & 1.00439 \tabularnewline
9 & 22.3 & 22.1995 & 22.1162 & 1.00376 & 1.00453 \tabularnewline
10 & 22.04 & 22.138 & 22.1138 & 1.0011 & 0.995571 \tabularnewline
11 & 22.05 & 22.1699 & 22.1087 & 1.00277 & 0.994591 \tabularnewline
12 & 22.06 & 22.1661 & 22.1046 & 1.00278 & 0.995213 \tabularnewline
13 & 22.06 & 22.1166 & 22.1004 & 1.00073 & 0.997439 \tabularnewline
14 & 22.06 & 22.0367 & 22.1037 & 0.996968 & 1.00106 \tabularnewline
15 & 21.97 & 22.0687 & 22.1133 & 0.997982 & 0.995527 \tabularnewline
16 & 22.03 & 22.0665 & 22.1208 & 0.997544 & 0.998346 \tabularnewline
17 & 22.08 & 22.0483 & 22.1312 & 0.99625 & 1.00144 \tabularnewline
18 & 22.13 & 22.0933 & 22.1417 & 0.997814 & 1.00166 \tabularnewline
19 & 22.13 & 22.1376 & 22.1483 & 0.999517 & 0.999655 \tabularnewline
20 & 22.4 & 22.2186 & 22.1571 & 1.00278 & 1.00816 \tabularnewline
21 & 22.4 & 22.2593 & 22.1758 & 1.00376 & 1.00632 \tabularnewline
22 & 22.12 & 22.2223 & 22.1979 & 1.0011 & 0.995396 \tabularnewline
23 & 22.22 & 22.2756 & 22.2142 & 1.00277 & 0.997503 \tabularnewline
24 & 22.14 & 22.2902 & 22.2283 & 1.00278 & 0.993261 \tabularnewline
25 & 22.14 & 22.258 & 22.2417 & 1.00073 & 0.994699 \tabularnewline
26 & 22.19 & 22.1763 & 22.2438 & 0.996968 & 1.00062 \tabularnewline
27 & 22.29 & 22.1897 & 22.2346 & 0.997982 & 1.00452 \tabularnewline
28 & 22.24 & 22.185 & 22.2396 & 0.997544 & 1.00248 \tabularnewline
29 & 22.26 & 22.1728 & 22.2562 & 0.99625 & 1.00393 \tabularnewline
30 & 22.29 & 22.2267 & 22.2754 & 0.997814 & 1.00285 \tabularnewline
31 & 22.29 & 22.2888 & 22.2996 & 0.999517 & 1.00005 \tabularnewline
32 & 22.29 & 22.3703 & 22.3083 & 1.00278 & 0.99641 \tabularnewline
33 & 22.29 & 22.3818 & 22.2979 & 1.00376 & 0.995897 \tabularnewline
34 & 22.35 & 22.3074 & 22.2829 & 1.0011 & 1.00191 \tabularnewline
35 & 22.39 & 22.3278 & 22.2663 & 1.00277 & 1.00278 \tabularnewline
36 & 22.43 & 22.3107 & 22.2488 & 1.00278 & 1.00535 \tabularnewline
37 & 22.43 & 22.2476 & 22.2313 & 1.00073 & 1.0082 \tabularnewline
38 & 22.11 & 22.1468 & 22.2142 & 0.996968 & 0.998338 \tabularnewline
39 & 22.12 & 22.1527 & 22.1975 & 0.997982 & 0.998524 \tabularnewline
40 & 22.05 & 22.1301 & 22.1846 & 0.997544 & 0.996381 \tabularnewline
41 & 22.05 & 22.091 & 22.1742 & 0.99625 & 0.998143 \tabularnewline
42 & 22.08 & 22.112 & 22.1604 & 0.997814 & 0.998554 \tabularnewline
43 & 22.08 & 22.1339 & 22.1446 & 0.999517 & 0.997565 \tabularnewline
44 & 22.09 & 22.204 & 22.1425 & 1.00278 & 0.994865 \tabularnewline
45 & 22.09 & 22.2384 & 22.155 & 1.00376 & 0.993328 \tabularnewline
46 & 22.24 & 22.1935 & 22.1692 & 1.0011 & 1.00209 \tabularnewline
47 & 22.25 & 22.248 & 22.1867 & 1.00277 & 1.00009 \tabularnewline
48 & 22.24 & 22.2681 & 22.2062 & 1.00278 & 0.99874 \tabularnewline
49 & 22.24 & 22.2417 & 22.2254 & 1.00073 & 0.999922 \tabularnewline
50 & 22.25 & 22.1767 & 22.2442 & 0.996968 & 1.0033 \tabularnewline
51 & 22.28 & 22.2209 & 22.2658 & 0.997982 & 1.00266 \tabularnewline
52 & 22.23 & 22.2311 & 22.2858 & 0.997544 & 0.999951 \tabularnewline
53 & 22.29 & 22.2168 & 22.3004 & 0.99625 & 1.0033 \tabularnewline
54 & 22.31 & 22.2662 & 22.315 & 0.997814 & 1.00197 \tabularnewline
55 & 22.31 & 22.308 & 22.3187 & 0.999517 & 1.00009 \tabularnewline
56 & 22.31 & 22.3645 & 22.3025 & 1.00278 & 0.997565 \tabularnewline
57 & 22.39 & 22.3605 & 22.2767 & 1.00376 & 1.00132 \tabularnewline
58 & 22.42 & 22.277 & 22.2525 & 1.0011 & 1.00642 \tabularnewline
59 & 22.42 & 22.2769 & 22.2154 & 1.00277 & 1.00643 \tabularnewline
60 & 22.42 & 22.2238 & 22.1621 & 1.00278 & 1.00883 \tabularnewline
61 & 22.15 & 22.125 & 22.1088 & 1.00073 & 1.00113 \tabularnewline
62 & 21.95 & 21.9923 & 22.0592 & 0.996968 & 0.998077 \tabularnewline
63 & 21.96 & 21.9564 & 22.0008 & 0.997982 & 1.00016 \tabularnewline
64 & 21.97 & 21.8774 & 21.9312 & 0.997544 & 1.00423 \tabularnewline
65 & 21.66 & 21.778 & 21.86 & 0.99625 & 0.994581 \tabularnewline
66 & 21.66 & 21.739 & 21.7867 & 0.997814 & 0.996364 \tabularnewline
67 & 21.68 & NA & NA & 0.999517 & NA \tabularnewline
68 & 21.75 & NA & NA & 1.00278 & NA \tabularnewline
69 & 21.55 & NA & NA & 1.00376 & NA \tabularnewline
70 & 21.59 & NA & NA & 1.0011 & NA \tabularnewline
71 & 21.54 & NA & NA & 1.00277 & NA \tabularnewline
72 & 21.54 & NA & NA & 1.00278 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269061&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]21.94[/C][C]NA[/C][C]NA[/C][C]1.00073[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]21.95[/C][C]NA[/C][C]NA[/C][C]0.996968[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]21.96[/C][C]NA[/C][C]NA[/C][C]0.997982[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]22.1[/C][C]NA[/C][C]NA[/C][C]0.997544[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]22.13[/C][C]NA[/C][C]NA[/C][C]0.99625[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]22.18[/C][C]NA[/C][C]NA[/C][C]0.997814[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]22.18[/C][C]22.091[/C][C]22.1017[/C][C]0.999517[/C][C]1.00403[/C][/ROW]
[ROW][C]8[/C][C]22.27[/C][C]22.1727[/C][C]22.1112[/C][C]1.00278[/C][C]1.00439[/C][/ROW]
[ROW][C]9[/C][C]22.3[/C][C]22.1995[/C][C]22.1162[/C][C]1.00376[/C][C]1.00453[/C][/ROW]
[ROW][C]10[/C][C]22.04[/C][C]22.138[/C][C]22.1138[/C][C]1.0011[/C][C]0.995571[/C][/ROW]
[ROW][C]11[/C][C]22.05[/C][C]22.1699[/C][C]22.1087[/C][C]1.00277[/C][C]0.994591[/C][/ROW]
[ROW][C]12[/C][C]22.06[/C][C]22.1661[/C][C]22.1046[/C][C]1.00278[/C][C]0.995213[/C][/ROW]
[ROW][C]13[/C][C]22.06[/C][C]22.1166[/C][C]22.1004[/C][C]1.00073[/C][C]0.997439[/C][/ROW]
[ROW][C]14[/C][C]22.06[/C][C]22.0367[/C][C]22.1037[/C][C]0.996968[/C][C]1.00106[/C][/ROW]
[ROW][C]15[/C][C]21.97[/C][C]22.0687[/C][C]22.1133[/C][C]0.997982[/C][C]0.995527[/C][/ROW]
[ROW][C]16[/C][C]22.03[/C][C]22.0665[/C][C]22.1208[/C][C]0.997544[/C][C]0.998346[/C][/ROW]
[ROW][C]17[/C][C]22.08[/C][C]22.0483[/C][C]22.1312[/C][C]0.99625[/C][C]1.00144[/C][/ROW]
[ROW][C]18[/C][C]22.13[/C][C]22.0933[/C][C]22.1417[/C][C]0.997814[/C][C]1.00166[/C][/ROW]
[ROW][C]19[/C][C]22.13[/C][C]22.1376[/C][C]22.1483[/C][C]0.999517[/C][C]0.999655[/C][/ROW]
[ROW][C]20[/C][C]22.4[/C][C]22.2186[/C][C]22.1571[/C][C]1.00278[/C][C]1.00816[/C][/ROW]
[ROW][C]21[/C][C]22.4[/C][C]22.2593[/C][C]22.1758[/C][C]1.00376[/C][C]1.00632[/C][/ROW]
[ROW][C]22[/C][C]22.12[/C][C]22.2223[/C][C]22.1979[/C][C]1.0011[/C][C]0.995396[/C][/ROW]
[ROW][C]23[/C][C]22.22[/C][C]22.2756[/C][C]22.2142[/C][C]1.00277[/C][C]0.997503[/C][/ROW]
[ROW][C]24[/C][C]22.14[/C][C]22.2902[/C][C]22.2283[/C][C]1.00278[/C][C]0.993261[/C][/ROW]
[ROW][C]25[/C][C]22.14[/C][C]22.258[/C][C]22.2417[/C][C]1.00073[/C][C]0.994699[/C][/ROW]
[ROW][C]26[/C][C]22.19[/C][C]22.1763[/C][C]22.2438[/C][C]0.996968[/C][C]1.00062[/C][/ROW]
[ROW][C]27[/C][C]22.29[/C][C]22.1897[/C][C]22.2346[/C][C]0.997982[/C][C]1.00452[/C][/ROW]
[ROW][C]28[/C][C]22.24[/C][C]22.185[/C][C]22.2396[/C][C]0.997544[/C][C]1.00248[/C][/ROW]
[ROW][C]29[/C][C]22.26[/C][C]22.1728[/C][C]22.2562[/C][C]0.99625[/C][C]1.00393[/C][/ROW]
[ROW][C]30[/C][C]22.29[/C][C]22.2267[/C][C]22.2754[/C][C]0.997814[/C][C]1.00285[/C][/ROW]
[ROW][C]31[/C][C]22.29[/C][C]22.2888[/C][C]22.2996[/C][C]0.999517[/C][C]1.00005[/C][/ROW]
[ROW][C]32[/C][C]22.29[/C][C]22.3703[/C][C]22.3083[/C][C]1.00278[/C][C]0.99641[/C][/ROW]
[ROW][C]33[/C][C]22.29[/C][C]22.3818[/C][C]22.2979[/C][C]1.00376[/C][C]0.995897[/C][/ROW]
[ROW][C]34[/C][C]22.35[/C][C]22.3074[/C][C]22.2829[/C][C]1.0011[/C][C]1.00191[/C][/ROW]
[ROW][C]35[/C][C]22.39[/C][C]22.3278[/C][C]22.2663[/C][C]1.00277[/C][C]1.00278[/C][/ROW]
[ROW][C]36[/C][C]22.43[/C][C]22.3107[/C][C]22.2488[/C][C]1.00278[/C][C]1.00535[/C][/ROW]
[ROW][C]37[/C][C]22.43[/C][C]22.2476[/C][C]22.2313[/C][C]1.00073[/C][C]1.0082[/C][/ROW]
[ROW][C]38[/C][C]22.11[/C][C]22.1468[/C][C]22.2142[/C][C]0.996968[/C][C]0.998338[/C][/ROW]
[ROW][C]39[/C][C]22.12[/C][C]22.1527[/C][C]22.1975[/C][C]0.997982[/C][C]0.998524[/C][/ROW]
[ROW][C]40[/C][C]22.05[/C][C]22.1301[/C][C]22.1846[/C][C]0.997544[/C][C]0.996381[/C][/ROW]
[ROW][C]41[/C][C]22.05[/C][C]22.091[/C][C]22.1742[/C][C]0.99625[/C][C]0.998143[/C][/ROW]
[ROW][C]42[/C][C]22.08[/C][C]22.112[/C][C]22.1604[/C][C]0.997814[/C][C]0.998554[/C][/ROW]
[ROW][C]43[/C][C]22.08[/C][C]22.1339[/C][C]22.1446[/C][C]0.999517[/C][C]0.997565[/C][/ROW]
[ROW][C]44[/C][C]22.09[/C][C]22.204[/C][C]22.1425[/C][C]1.00278[/C][C]0.994865[/C][/ROW]
[ROW][C]45[/C][C]22.09[/C][C]22.2384[/C][C]22.155[/C][C]1.00376[/C][C]0.993328[/C][/ROW]
[ROW][C]46[/C][C]22.24[/C][C]22.1935[/C][C]22.1692[/C][C]1.0011[/C][C]1.00209[/C][/ROW]
[ROW][C]47[/C][C]22.25[/C][C]22.248[/C][C]22.1867[/C][C]1.00277[/C][C]1.00009[/C][/ROW]
[ROW][C]48[/C][C]22.24[/C][C]22.2681[/C][C]22.2062[/C][C]1.00278[/C][C]0.99874[/C][/ROW]
[ROW][C]49[/C][C]22.24[/C][C]22.2417[/C][C]22.2254[/C][C]1.00073[/C][C]0.999922[/C][/ROW]
[ROW][C]50[/C][C]22.25[/C][C]22.1767[/C][C]22.2442[/C][C]0.996968[/C][C]1.0033[/C][/ROW]
[ROW][C]51[/C][C]22.28[/C][C]22.2209[/C][C]22.2658[/C][C]0.997982[/C][C]1.00266[/C][/ROW]
[ROW][C]52[/C][C]22.23[/C][C]22.2311[/C][C]22.2858[/C][C]0.997544[/C][C]0.999951[/C][/ROW]
[ROW][C]53[/C][C]22.29[/C][C]22.2168[/C][C]22.3004[/C][C]0.99625[/C][C]1.0033[/C][/ROW]
[ROW][C]54[/C][C]22.31[/C][C]22.2662[/C][C]22.315[/C][C]0.997814[/C][C]1.00197[/C][/ROW]
[ROW][C]55[/C][C]22.31[/C][C]22.308[/C][C]22.3187[/C][C]0.999517[/C][C]1.00009[/C][/ROW]
[ROW][C]56[/C][C]22.31[/C][C]22.3645[/C][C]22.3025[/C][C]1.00278[/C][C]0.997565[/C][/ROW]
[ROW][C]57[/C][C]22.39[/C][C]22.3605[/C][C]22.2767[/C][C]1.00376[/C][C]1.00132[/C][/ROW]
[ROW][C]58[/C][C]22.42[/C][C]22.277[/C][C]22.2525[/C][C]1.0011[/C][C]1.00642[/C][/ROW]
[ROW][C]59[/C][C]22.42[/C][C]22.2769[/C][C]22.2154[/C][C]1.00277[/C][C]1.00643[/C][/ROW]
[ROW][C]60[/C][C]22.42[/C][C]22.2238[/C][C]22.1621[/C][C]1.00278[/C][C]1.00883[/C][/ROW]
[ROW][C]61[/C][C]22.15[/C][C]22.125[/C][C]22.1088[/C][C]1.00073[/C][C]1.00113[/C][/ROW]
[ROW][C]62[/C][C]21.95[/C][C]21.9923[/C][C]22.0592[/C][C]0.996968[/C][C]0.998077[/C][/ROW]
[ROW][C]63[/C][C]21.96[/C][C]21.9564[/C][C]22.0008[/C][C]0.997982[/C][C]1.00016[/C][/ROW]
[ROW][C]64[/C][C]21.97[/C][C]21.8774[/C][C]21.9312[/C][C]0.997544[/C][C]1.00423[/C][/ROW]
[ROW][C]65[/C][C]21.66[/C][C]21.778[/C][C]21.86[/C][C]0.99625[/C][C]0.994581[/C][/ROW]
[ROW][C]66[/C][C]21.66[/C][C]21.739[/C][C]21.7867[/C][C]0.997814[/C][C]0.996364[/C][/ROW]
[ROW][C]67[/C][C]21.68[/C][C]NA[/C][C]NA[/C][C]0.999517[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]21.75[/C][C]NA[/C][C]NA[/C][C]1.00278[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]21.55[/C][C]NA[/C][C]NA[/C][C]1.00376[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]21.59[/C][C]NA[/C][C]NA[/C][C]1.0011[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]21.54[/C][C]NA[/C][C]NA[/C][C]1.00277[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]21.54[/C][C]NA[/C][C]NA[/C][C]1.00278[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269061&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269061&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	21.94	NA	NA	1.00073	NA
2	21.95	NA	NA	0.996968	NA
3	21.96	NA	NA	0.997982	NA
4	22.1	NA	NA	0.997544	NA
5	22.13	NA	NA	0.99625	NA
6	22.18	NA	NA	0.997814	NA
7	22.18	22.091	22.1017	0.999517	1.00403
8	22.27	22.1727	22.1112	1.00278	1.00439
9	22.3	22.1995	22.1162	1.00376	1.00453
10	22.04	22.138	22.1138	1.0011	0.995571
11	22.05	22.1699	22.1087	1.00277	0.994591
12	22.06	22.1661	22.1046	1.00278	0.995213
13	22.06	22.1166	22.1004	1.00073	0.997439
14	22.06	22.0367	22.1037	0.996968	1.00106
15	21.97	22.0687	22.1133	0.997982	0.995527
16	22.03	22.0665	22.1208	0.997544	0.998346
17	22.08	22.0483	22.1312	0.99625	1.00144
18	22.13	22.0933	22.1417	0.997814	1.00166
19	22.13	22.1376	22.1483	0.999517	0.999655
20	22.4	22.2186	22.1571	1.00278	1.00816
21	22.4	22.2593	22.1758	1.00376	1.00632
22	22.12	22.2223	22.1979	1.0011	0.995396
23	22.22	22.2756	22.2142	1.00277	0.997503
24	22.14	22.2902	22.2283	1.00278	0.993261
25	22.14	22.258	22.2417	1.00073	0.994699
26	22.19	22.1763	22.2438	0.996968	1.00062
27	22.29	22.1897	22.2346	0.997982	1.00452
28	22.24	22.185	22.2396	0.997544	1.00248
29	22.26	22.1728	22.2562	0.99625	1.00393
30	22.29	22.2267	22.2754	0.997814	1.00285
31	22.29	22.2888	22.2996	0.999517	1.00005
32	22.29	22.3703	22.3083	1.00278	0.99641
33	22.29	22.3818	22.2979	1.00376	0.995897
34	22.35	22.3074	22.2829	1.0011	1.00191
35	22.39	22.3278	22.2663	1.00277	1.00278
36	22.43	22.3107	22.2488	1.00278	1.00535
37	22.43	22.2476	22.2313	1.00073	1.0082
38	22.11	22.1468	22.2142	0.996968	0.998338
39	22.12	22.1527	22.1975	0.997982	0.998524
40	22.05	22.1301	22.1846	0.997544	0.996381
41	22.05	22.091	22.1742	0.99625	0.998143
42	22.08	22.112	22.1604	0.997814	0.998554
43	22.08	22.1339	22.1446	0.999517	0.997565
44	22.09	22.204	22.1425	1.00278	0.994865
45	22.09	22.2384	22.155	1.00376	0.993328
46	22.24	22.1935	22.1692	1.0011	1.00209
47	22.25	22.248	22.1867	1.00277	1.00009
48	22.24	22.2681	22.2062	1.00278	0.99874
49	22.24	22.2417	22.2254	1.00073	0.999922
50	22.25	22.1767	22.2442	0.996968	1.0033
51	22.28	22.2209	22.2658	0.997982	1.00266
52	22.23	22.2311	22.2858	0.997544	0.999951
53	22.29	22.2168	22.3004	0.99625	1.0033
54	22.31	22.2662	22.315	0.997814	1.00197
55	22.31	22.308	22.3187	0.999517	1.00009
56	22.31	22.3645	22.3025	1.00278	0.997565
57	22.39	22.3605	22.2767	1.00376	1.00132
58	22.42	22.277	22.2525	1.0011	1.00642
59	22.42	22.2769	22.2154	1.00277	1.00643
60	22.42	22.2238	22.1621	1.00278	1.00883
61	22.15	22.125	22.1088	1.00073	1.00113
62	21.95	21.9923	22.0592	0.996968	0.998077
63	21.96	21.9564	22.0008	0.997982	1.00016
64	21.97	21.8774	21.9312	0.997544	1.00423
65	21.66	21.778	21.86	0.99625	0.994581
66	21.66	21.739	21.7867	0.997814	0.996364
67	21.68	NA	NA	0.999517	NA
68	21.75	NA	NA	1.00278	NA
69	21.55	NA	NA	1.00376	NA
70	21.59	NA	NA	1.0011	NA
71	21.54	NA	NA	1.00277	NA
72	21.54	NA	NA	1.00278	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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