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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 13 Jan 2009 10:52:00 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jan/13/t1231869145vk1c2f8n9paf4zg.htm/, Retrieved Tue, 30 Apr 2024 16:59:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36867, Retrieved Tue, 30 Apr 2024 16:59:52 +0000

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Estimated Impact

208

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Bananen - Waerlop...] [2009-01-13 17:52:00] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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1,83
1,89
1,9
2,01
2,04
2,04
2,03
2,04
1,87
1,85
1,82
1,79
1,88
2,01
1,9
1,96
1,94
1,92
1,79
1,77
1,74
1,75
1,86
1,84
1,77
1,98
1,94
1,85
1,84
1,82
1,83
1,91
1,85
1,81
1,83
1,79
1,8
1,82
1,88
2,01
1,97
1,92
1,98
2,02
1,9
1,94
1,96
1,84
1,87
1,84
2,07
2,08
2,14
2,15
2,05
2,05
1,95
2,02
2,02
1,88
1,96
1,93
2,03
2,1
1,95
2,07
2,09
2,01
1,92
1,99
2,11
2

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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36867&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36867&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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.83	NA	NA	0.967158914529167	NA
2	1.89	NA	NA	0.999850562201415	NA
3	1.9	NA	NA	1.02317220815810	NA
4	2.01	NA	NA	1.04078502043631	NA
5	2.04	NA	NA	1.02242221248224	NA
6	2.04	NA	NA	1.02368422896303	NA
7	2.03	1.94873016003037	1.92791666666667	1.01079584700084	1.04170399865334
8	2.04	1.97708122638363	1.935	1.02174740381583	1.03182407114929
9	1.87	1.88457881333095	1.94	0.971432378005643	0.992264153015082
10	1.85	1.89174957108678	1.93791666666667	0.976176944873847	0.977930709368264
11	1.82	1.91069702012302	1.93166666666667	0.98914427271252	0.952531971752812
12	1.79	1.83335368811349	1.9225	0.95363000682106	0.976352796301898
13	1.88	1.84485562946438	1.9075	0.967158914529167	1.01904992996434
14	2.01	1.88596812295242	1.88625	0.999850562201415	1.06576562749821
15	1.9	1.91290570750225	1.86958333333333	1.02317220815810	0.993253348844307
16	1.96	1.93586013801153	1.86	1.04078502043631	1.01246983783305
17	1.94	1.89914925968576	1.8575	1.02242221248224	1.02151002092432
18	1.92	1.90533227115744	1.86125	1.02368422896303	1.00769825245948
19	1.79	1.87881678061281	1.85875	1.01079584700084	0.952727279461577
20	1.77	1.89321279365375	1.85291666666667	1.02174740381583	0.934918676829793
21	1.74	1.80038800723712	1.85333333333333	0.971432378005643	0.966458337317079
22	1.75	1.80633408841031	1.85041666666667	0.976176944873847	0.968813029233207
23	1.86	1.82167403557889	1.84166666666667	0.98914427271252	1.02103887066103
24	1.84	1.74832167917194	1.83333333333333	0.95363000682106	1.05243790197207
25	1.77	1.77070677935048	1.83083333333333	0.967158914529167	0.999600849017621
26	1.98	1.83805861684693	1.83833333333333	0.999850562201415	1.07722353457724
27	1.94	1.89158961983229	1.84875	1.02317220815810	1.02559243276668
28	1.85	1.93152353375971	1.85583333333333	1.04078502043631	0.957793144978655
29	1.84	1.89872325043056	1.85708333333333	1.02242221248224	0.96907224345768
30	1.82	1.89765463944022	1.85375	1.02368422896303	0.959078623777862
31	1.83	1.87292047150530	1.85291666666667	1.01079584700084	0.97708366577316
32	1.91	1.88767832854975	1.8475	1.02174740381583	1.01182493389507
33	1.85	1.78581652156704	1.83833333333333	0.971432378005643	1.03594069024327
34	1.81	1.79860602093006	1.8425	0.976176944873847	1.00633489432224
35	1.83	1.83445048243476	1.85458333333333	0.98914427271252	0.997573942454498
36	1.79	1.77772527104893	1.86416666666667	0.95363000682106	1.00690473896669
37	1.8	1.81301998186113	1.87458333333333	0.967158914529167	0.992818621972512
38	1.82	1.88513491415058	1.88541666666667	0.999850562201415	0.965448141848281
39	1.88	1.93592708218581	1.89208333333333	1.02317220815810	0.97111095624394
40	2.01	1.9770578784038	1.89958333333333	1.04078502043631	1.01666219383663
41	1.97	1.95325243509628	1.91041666666667	1.02242221248224	1.00857419379226
42	1.92	1.96334104413201	1.91791666666667	1.02368422896303	0.97792485199576
43	1.98	1.94367618079536	1.92291666666667	1.01079584700084	1.01868820514628
44	2.02	1.96856666468517	1.92666666666667	1.02174740381583	1.02612730177622
45	1.9	1.88012641493175	1.93541666666667	0.971432378005643	1.01057034511638
46	1.94	1.89988437896072	1.94625	0.976176944873847	1.02111476965836
47	1.96	1.93501348349387	1.95625	0.98914427271252	1.01291283844752
48	1.84	1.88143253429072	1.97291666666667	0.95363000682106	0.977978198242259
49	1.87	1.92021342822145	1.98541666666667	0.967158914529167	0.973850079640388
50	1.84	1.9892860143799	1.98958333333333	0.999850562201415	0.924954977162279
51	2.07	2.03909694650842	1.99291666666667	1.02317220815810	1.01515526446376
52	2.08	2.07983539917189	1.99833333333333	1.04078502043631	1.00007914127636
53	2.14	2.04910451751649	2.00416666666667	1.02242221248224	1.04435863651976
54	2.15	2.05589915983409	2.00833333333333	1.02368422896303	1.04577113605781
55	2.05	2.03549013689794	2.01375	1.01079584700084	1.00712843694943
56	2.05	2.06520693996275	2.02125	1.02174740381583	0.99263660233341
57	1.95	1.96553151149808	2.02333333333333	0.971432378005643	0.992098060291973
58	2.02	1.97431787100736	2.0225	0.976176944873847	1.02313818340171
59	2.02	1.99353785296269	2.01541666666667	0.98914427271252	1.01327396266792
60	1.88	1.91123347200387	2.00416666666667	0.95363000682106	0.983657950500874
61	1.96	1.93673572634466	2.0025	0.967158914529167	1.01201210538892
62	1.93	2.00220075080833	2.0025	0.999850562201415	0.96393930489778
63	2.03	2.04591809456281	1.99958333333333	1.02317220815810	0.9922195836651
64	2.1	2.07853441789634	1.99708333333333	1.04078502043631	1.01032726805909
65	1.95	2.04441841570928	1.99958333333333	1.02242221248224	0.953816491289764
66	2.07	2.05589915983409	2.00833333333333	1.02368422896303	1.00685872169287
67	2.09	NA	NA	1.01079584700084	NA
68	2.01	NA	NA	1.02174740381583	NA
69	1.92	NA	NA	0.971432378005643	NA
70	1.99	NA	NA	0.976176944873847	NA
71	2.11	NA	NA	0.98914427271252	NA
72	2	NA	NA	0.95363000682106	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.83 & NA & NA & 0.967158914529167 & NA \tabularnewline
2 & 1.89 & NA & NA & 0.999850562201415 & NA \tabularnewline
3 & 1.9 & NA & NA & 1.02317220815810 & NA \tabularnewline
4 & 2.01 & NA & NA & 1.04078502043631 & NA \tabularnewline
5 & 2.04 & NA & NA & 1.02242221248224 & NA \tabularnewline
6 & 2.04 & NA & NA & 1.02368422896303 & NA \tabularnewline
7 & 2.03 & 1.94873016003037 & 1.92791666666667 & 1.01079584700084 & 1.04170399865334 \tabularnewline
8 & 2.04 & 1.97708122638363 & 1.935 & 1.02174740381583 & 1.03182407114929 \tabularnewline
9 & 1.87 & 1.88457881333095 & 1.94 & 0.971432378005643 & 0.992264153015082 \tabularnewline
10 & 1.85 & 1.89174957108678 & 1.93791666666667 & 0.976176944873847 & 0.977930709368264 \tabularnewline
11 & 1.82 & 1.91069702012302 & 1.93166666666667 & 0.98914427271252 & 0.952531971752812 \tabularnewline
12 & 1.79 & 1.83335368811349 & 1.9225 & 0.95363000682106 & 0.976352796301898 \tabularnewline
13 & 1.88 & 1.84485562946438 & 1.9075 & 0.967158914529167 & 1.01904992996434 \tabularnewline
14 & 2.01 & 1.88596812295242 & 1.88625 & 0.999850562201415 & 1.06576562749821 \tabularnewline
15 & 1.9 & 1.91290570750225 & 1.86958333333333 & 1.02317220815810 & 0.993253348844307 \tabularnewline
16 & 1.96 & 1.93586013801153 & 1.86 & 1.04078502043631 & 1.01246983783305 \tabularnewline
17 & 1.94 & 1.89914925968576 & 1.8575 & 1.02242221248224 & 1.02151002092432 \tabularnewline
18 & 1.92 & 1.90533227115744 & 1.86125 & 1.02368422896303 & 1.00769825245948 \tabularnewline
19 & 1.79 & 1.87881678061281 & 1.85875 & 1.01079584700084 & 0.952727279461577 \tabularnewline
20 & 1.77 & 1.89321279365375 & 1.85291666666667 & 1.02174740381583 & 0.934918676829793 \tabularnewline
21 & 1.74 & 1.80038800723712 & 1.85333333333333 & 0.971432378005643 & 0.966458337317079 \tabularnewline
22 & 1.75 & 1.80633408841031 & 1.85041666666667 & 0.976176944873847 & 0.968813029233207 \tabularnewline
23 & 1.86 & 1.82167403557889 & 1.84166666666667 & 0.98914427271252 & 1.02103887066103 \tabularnewline
24 & 1.84 & 1.74832167917194 & 1.83333333333333 & 0.95363000682106 & 1.05243790197207 \tabularnewline
25 & 1.77 & 1.77070677935048 & 1.83083333333333 & 0.967158914529167 & 0.999600849017621 \tabularnewline
26 & 1.98 & 1.83805861684693 & 1.83833333333333 & 0.999850562201415 & 1.07722353457724 \tabularnewline
27 & 1.94 & 1.89158961983229 & 1.84875 & 1.02317220815810 & 1.02559243276668 \tabularnewline
28 & 1.85 & 1.93152353375971 & 1.85583333333333 & 1.04078502043631 & 0.957793144978655 \tabularnewline
29 & 1.84 & 1.89872325043056 & 1.85708333333333 & 1.02242221248224 & 0.96907224345768 \tabularnewline
30 & 1.82 & 1.89765463944022 & 1.85375 & 1.02368422896303 & 0.959078623777862 \tabularnewline
31 & 1.83 & 1.87292047150530 & 1.85291666666667 & 1.01079584700084 & 0.97708366577316 \tabularnewline
32 & 1.91 & 1.88767832854975 & 1.8475 & 1.02174740381583 & 1.01182493389507 \tabularnewline
33 & 1.85 & 1.78581652156704 & 1.83833333333333 & 0.971432378005643 & 1.03594069024327 \tabularnewline
34 & 1.81 & 1.79860602093006 & 1.8425 & 0.976176944873847 & 1.00633489432224 \tabularnewline
35 & 1.83 & 1.83445048243476 & 1.85458333333333 & 0.98914427271252 & 0.997573942454498 \tabularnewline
36 & 1.79 & 1.77772527104893 & 1.86416666666667 & 0.95363000682106 & 1.00690473896669 \tabularnewline
37 & 1.8 & 1.81301998186113 & 1.87458333333333 & 0.967158914529167 & 0.992818621972512 \tabularnewline
38 & 1.82 & 1.88513491415058 & 1.88541666666667 & 0.999850562201415 & 0.965448141848281 \tabularnewline
39 & 1.88 & 1.93592708218581 & 1.89208333333333 & 1.02317220815810 & 0.97111095624394 \tabularnewline
40 & 2.01 & 1.9770578784038 & 1.89958333333333 & 1.04078502043631 & 1.01666219383663 \tabularnewline
41 & 1.97 & 1.95325243509628 & 1.91041666666667 & 1.02242221248224 & 1.00857419379226 \tabularnewline
42 & 1.92 & 1.96334104413201 & 1.91791666666667 & 1.02368422896303 & 0.97792485199576 \tabularnewline
43 & 1.98 & 1.94367618079536 & 1.92291666666667 & 1.01079584700084 & 1.01868820514628 \tabularnewline
44 & 2.02 & 1.96856666468517 & 1.92666666666667 & 1.02174740381583 & 1.02612730177622 \tabularnewline
45 & 1.9 & 1.88012641493175 & 1.93541666666667 & 0.971432378005643 & 1.01057034511638 \tabularnewline
46 & 1.94 & 1.89988437896072 & 1.94625 & 0.976176944873847 & 1.02111476965836 \tabularnewline
47 & 1.96 & 1.93501348349387 & 1.95625 & 0.98914427271252 & 1.01291283844752 \tabularnewline
48 & 1.84 & 1.88143253429072 & 1.97291666666667 & 0.95363000682106 & 0.977978198242259 \tabularnewline
49 & 1.87 & 1.92021342822145 & 1.98541666666667 & 0.967158914529167 & 0.973850079640388 \tabularnewline
50 & 1.84 & 1.9892860143799 & 1.98958333333333 & 0.999850562201415 & 0.924954977162279 \tabularnewline
51 & 2.07 & 2.03909694650842 & 1.99291666666667 & 1.02317220815810 & 1.01515526446376 \tabularnewline
52 & 2.08 & 2.07983539917189 & 1.99833333333333 & 1.04078502043631 & 1.00007914127636 \tabularnewline
53 & 2.14 & 2.04910451751649 & 2.00416666666667 & 1.02242221248224 & 1.04435863651976 \tabularnewline
54 & 2.15 & 2.05589915983409 & 2.00833333333333 & 1.02368422896303 & 1.04577113605781 \tabularnewline
55 & 2.05 & 2.03549013689794 & 2.01375 & 1.01079584700084 & 1.00712843694943 \tabularnewline
56 & 2.05 & 2.06520693996275 & 2.02125 & 1.02174740381583 & 0.99263660233341 \tabularnewline
57 & 1.95 & 1.96553151149808 & 2.02333333333333 & 0.971432378005643 & 0.992098060291973 \tabularnewline
58 & 2.02 & 1.97431787100736 & 2.0225 & 0.976176944873847 & 1.02313818340171 \tabularnewline
59 & 2.02 & 1.99353785296269 & 2.01541666666667 & 0.98914427271252 & 1.01327396266792 \tabularnewline
60 & 1.88 & 1.91123347200387 & 2.00416666666667 & 0.95363000682106 & 0.983657950500874 \tabularnewline
61 & 1.96 & 1.93673572634466 & 2.0025 & 0.967158914529167 & 1.01201210538892 \tabularnewline
62 & 1.93 & 2.00220075080833 & 2.0025 & 0.999850562201415 & 0.96393930489778 \tabularnewline
63 & 2.03 & 2.04591809456281 & 1.99958333333333 & 1.02317220815810 & 0.9922195836651 \tabularnewline
64 & 2.1 & 2.07853441789634 & 1.99708333333333 & 1.04078502043631 & 1.01032726805909 \tabularnewline
65 & 1.95 & 2.04441841570928 & 1.99958333333333 & 1.02242221248224 & 0.953816491289764 \tabularnewline
66 & 2.07 & 2.05589915983409 & 2.00833333333333 & 1.02368422896303 & 1.00685872169287 \tabularnewline
67 & 2.09 & NA & NA & 1.01079584700084 & NA \tabularnewline
68 & 2.01 & NA & NA & 1.02174740381583 & NA \tabularnewline
69 & 1.92 & NA & NA & 0.971432378005643 & NA \tabularnewline
70 & 1.99 & NA & NA & 0.976176944873847 & NA \tabularnewline
71 & 2.11 & NA & NA & 0.98914427271252 & NA \tabularnewline
72 & 2 & NA & NA & 0.95363000682106 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36867&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]1.83[/C][C]NA[/C][C]NA[/C][C]0.967158914529167[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.89[/C][C]NA[/C][C]NA[/C][C]0.999850562201415[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.9[/C][C]NA[/C][C]NA[/C][C]1.02317220815810[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.01[/C][C]NA[/C][C]NA[/C][C]1.04078502043631[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.04[/C][C]NA[/C][C]NA[/C][C]1.02242221248224[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.04[/C][C]NA[/C][C]NA[/C][C]1.02368422896303[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.03[/C][C]1.94873016003037[/C][C]1.92791666666667[/C][C]1.01079584700084[/C][C]1.04170399865334[/C][/ROW]
[ROW][C]8[/C][C]2.04[/C][C]1.97708122638363[/C][C]1.935[/C][C]1.02174740381583[/C][C]1.03182407114929[/C][/ROW]
[ROW][C]9[/C][C]1.87[/C][C]1.88457881333095[/C][C]1.94[/C][C]0.971432378005643[/C][C]0.992264153015082[/C][/ROW]
[ROW][C]10[/C][C]1.85[/C][C]1.89174957108678[/C][C]1.93791666666667[/C][C]0.976176944873847[/C][C]0.977930709368264[/C][/ROW]
[ROW][C]11[/C][C]1.82[/C][C]1.91069702012302[/C][C]1.93166666666667[/C][C]0.98914427271252[/C][C]0.952531971752812[/C][/ROW]
[ROW][C]12[/C][C]1.79[/C][C]1.83335368811349[/C][C]1.9225[/C][C]0.95363000682106[/C][C]0.976352796301898[/C][/ROW]
[ROW][C]13[/C][C]1.88[/C][C]1.84485562946438[/C][C]1.9075[/C][C]0.967158914529167[/C][C]1.01904992996434[/C][/ROW]
[ROW][C]14[/C][C]2.01[/C][C]1.88596812295242[/C][C]1.88625[/C][C]0.999850562201415[/C][C]1.06576562749821[/C][/ROW]
[ROW][C]15[/C][C]1.9[/C][C]1.91290570750225[/C][C]1.86958333333333[/C][C]1.02317220815810[/C][C]0.993253348844307[/C][/ROW]
[ROW][C]16[/C][C]1.96[/C][C]1.93586013801153[/C][C]1.86[/C][C]1.04078502043631[/C][C]1.01246983783305[/C][/ROW]
[ROW][C]17[/C][C]1.94[/C][C]1.89914925968576[/C][C]1.8575[/C][C]1.02242221248224[/C][C]1.02151002092432[/C][/ROW]
[ROW][C]18[/C][C]1.92[/C][C]1.90533227115744[/C][C]1.86125[/C][C]1.02368422896303[/C][C]1.00769825245948[/C][/ROW]
[ROW][C]19[/C][C]1.79[/C][C]1.87881678061281[/C][C]1.85875[/C][C]1.01079584700084[/C][C]0.952727279461577[/C][/ROW]
[ROW][C]20[/C][C]1.77[/C][C]1.89321279365375[/C][C]1.85291666666667[/C][C]1.02174740381583[/C][C]0.934918676829793[/C][/ROW]
[ROW][C]21[/C][C]1.74[/C][C]1.80038800723712[/C][C]1.85333333333333[/C][C]0.971432378005643[/C][C]0.966458337317079[/C][/ROW]
[ROW][C]22[/C][C]1.75[/C][C]1.80633408841031[/C][C]1.85041666666667[/C][C]0.976176944873847[/C][C]0.968813029233207[/C][/ROW]
[ROW][C]23[/C][C]1.86[/C][C]1.82167403557889[/C][C]1.84166666666667[/C][C]0.98914427271252[/C][C]1.02103887066103[/C][/ROW]
[ROW][C]24[/C][C]1.84[/C][C]1.74832167917194[/C][C]1.83333333333333[/C][C]0.95363000682106[/C][C]1.05243790197207[/C][/ROW]
[ROW][C]25[/C][C]1.77[/C][C]1.77070677935048[/C][C]1.83083333333333[/C][C]0.967158914529167[/C][C]0.999600849017621[/C][/ROW]
[ROW][C]26[/C][C]1.98[/C][C]1.83805861684693[/C][C]1.83833333333333[/C][C]0.999850562201415[/C][C]1.07722353457724[/C][/ROW]
[ROW][C]27[/C][C]1.94[/C][C]1.89158961983229[/C][C]1.84875[/C][C]1.02317220815810[/C][C]1.02559243276668[/C][/ROW]
[ROW][C]28[/C][C]1.85[/C][C]1.93152353375971[/C][C]1.85583333333333[/C][C]1.04078502043631[/C][C]0.957793144978655[/C][/ROW]
[ROW][C]29[/C][C]1.84[/C][C]1.89872325043056[/C][C]1.85708333333333[/C][C]1.02242221248224[/C][C]0.96907224345768[/C][/ROW]
[ROW][C]30[/C][C]1.82[/C][C]1.89765463944022[/C][C]1.85375[/C][C]1.02368422896303[/C][C]0.959078623777862[/C][/ROW]
[ROW][C]31[/C][C]1.83[/C][C]1.87292047150530[/C][C]1.85291666666667[/C][C]1.01079584700084[/C][C]0.97708366577316[/C][/ROW]
[ROW][C]32[/C][C]1.91[/C][C]1.88767832854975[/C][C]1.8475[/C][C]1.02174740381583[/C][C]1.01182493389507[/C][/ROW]
[ROW][C]33[/C][C]1.85[/C][C]1.78581652156704[/C][C]1.83833333333333[/C][C]0.971432378005643[/C][C]1.03594069024327[/C][/ROW]
[ROW][C]34[/C][C]1.81[/C][C]1.79860602093006[/C][C]1.8425[/C][C]0.976176944873847[/C][C]1.00633489432224[/C][/ROW]
[ROW][C]35[/C][C]1.83[/C][C]1.83445048243476[/C][C]1.85458333333333[/C][C]0.98914427271252[/C][C]0.997573942454498[/C][/ROW]
[ROW][C]36[/C][C]1.79[/C][C]1.77772527104893[/C][C]1.86416666666667[/C][C]0.95363000682106[/C][C]1.00690473896669[/C][/ROW]
[ROW][C]37[/C][C]1.8[/C][C]1.81301998186113[/C][C]1.87458333333333[/C][C]0.967158914529167[/C][C]0.992818621972512[/C][/ROW]
[ROW][C]38[/C][C]1.82[/C][C]1.88513491415058[/C][C]1.88541666666667[/C][C]0.999850562201415[/C][C]0.965448141848281[/C][/ROW]
[ROW][C]39[/C][C]1.88[/C][C]1.93592708218581[/C][C]1.89208333333333[/C][C]1.02317220815810[/C][C]0.97111095624394[/C][/ROW]
[ROW][C]40[/C][C]2.01[/C][C]1.9770578784038[/C][C]1.89958333333333[/C][C]1.04078502043631[/C][C]1.01666219383663[/C][/ROW]
[ROW][C]41[/C][C]1.97[/C][C]1.95325243509628[/C][C]1.91041666666667[/C][C]1.02242221248224[/C][C]1.00857419379226[/C][/ROW]
[ROW][C]42[/C][C]1.92[/C][C]1.96334104413201[/C][C]1.91791666666667[/C][C]1.02368422896303[/C][C]0.97792485199576[/C][/ROW]
[ROW][C]43[/C][C]1.98[/C][C]1.94367618079536[/C][C]1.92291666666667[/C][C]1.01079584700084[/C][C]1.01868820514628[/C][/ROW]
[ROW][C]44[/C][C]2.02[/C][C]1.96856666468517[/C][C]1.92666666666667[/C][C]1.02174740381583[/C][C]1.02612730177622[/C][/ROW]
[ROW][C]45[/C][C]1.9[/C][C]1.88012641493175[/C][C]1.93541666666667[/C][C]0.971432378005643[/C][C]1.01057034511638[/C][/ROW]
[ROW][C]46[/C][C]1.94[/C][C]1.89988437896072[/C][C]1.94625[/C][C]0.976176944873847[/C][C]1.02111476965836[/C][/ROW]
[ROW][C]47[/C][C]1.96[/C][C]1.93501348349387[/C][C]1.95625[/C][C]0.98914427271252[/C][C]1.01291283844752[/C][/ROW]
[ROW][C]48[/C][C]1.84[/C][C]1.88143253429072[/C][C]1.97291666666667[/C][C]0.95363000682106[/C][C]0.977978198242259[/C][/ROW]
[ROW][C]49[/C][C]1.87[/C][C]1.92021342822145[/C][C]1.98541666666667[/C][C]0.967158914529167[/C][C]0.973850079640388[/C][/ROW]
[ROW][C]50[/C][C]1.84[/C][C]1.9892860143799[/C][C]1.98958333333333[/C][C]0.999850562201415[/C][C]0.924954977162279[/C][/ROW]
[ROW][C]51[/C][C]2.07[/C][C]2.03909694650842[/C][C]1.99291666666667[/C][C]1.02317220815810[/C][C]1.01515526446376[/C][/ROW]
[ROW][C]52[/C][C]2.08[/C][C]2.07983539917189[/C][C]1.99833333333333[/C][C]1.04078502043631[/C][C]1.00007914127636[/C][/ROW]
[ROW][C]53[/C][C]2.14[/C][C]2.04910451751649[/C][C]2.00416666666667[/C][C]1.02242221248224[/C][C]1.04435863651976[/C][/ROW]
[ROW][C]54[/C][C]2.15[/C][C]2.05589915983409[/C][C]2.00833333333333[/C][C]1.02368422896303[/C][C]1.04577113605781[/C][/ROW]
[ROW][C]55[/C][C]2.05[/C][C]2.03549013689794[/C][C]2.01375[/C][C]1.01079584700084[/C][C]1.00712843694943[/C][/ROW]
[ROW][C]56[/C][C]2.05[/C][C]2.06520693996275[/C][C]2.02125[/C][C]1.02174740381583[/C][C]0.99263660233341[/C][/ROW]
[ROW][C]57[/C][C]1.95[/C][C]1.96553151149808[/C][C]2.02333333333333[/C][C]0.971432378005643[/C][C]0.992098060291973[/C][/ROW]
[ROW][C]58[/C][C]2.02[/C][C]1.97431787100736[/C][C]2.0225[/C][C]0.976176944873847[/C][C]1.02313818340171[/C][/ROW]
[ROW][C]59[/C][C]2.02[/C][C]1.99353785296269[/C][C]2.01541666666667[/C][C]0.98914427271252[/C][C]1.01327396266792[/C][/ROW]
[ROW][C]60[/C][C]1.88[/C][C]1.91123347200387[/C][C]2.00416666666667[/C][C]0.95363000682106[/C][C]0.983657950500874[/C][/ROW]
[ROW][C]61[/C][C]1.96[/C][C]1.93673572634466[/C][C]2.0025[/C][C]0.967158914529167[/C][C]1.01201210538892[/C][/ROW]
[ROW][C]62[/C][C]1.93[/C][C]2.00220075080833[/C][C]2.0025[/C][C]0.999850562201415[/C][C]0.96393930489778[/C][/ROW]
[ROW][C]63[/C][C]2.03[/C][C]2.04591809456281[/C][C]1.99958333333333[/C][C]1.02317220815810[/C][C]0.9922195836651[/C][/ROW]
[ROW][C]64[/C][C]2.1[/C][C]2.07853441789634[/C][C]1.99708333333333[/C][C]1.04078502043631[/C][C]1.01032726805909[/C][/ROW]
[ROW][C]65[/C][C]1.95[/C][C]2.04441841570928[/C][C]1.99958333333333[/C][C]1.02242221248224[/C][C]0.953816491289764[/C][/ROW]
[ROW][C]66[/C][C]2.07[/C][C]2.05589915983409[/C][C]2.00833333333333[/C][C]1.02368422896303[/C][C]1.00685872169287[/C][/ROW]
[ROW][C]67[/C][C]2.09[/C][C]NA[/C][C]NA[/C][C]1.01079584700084[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]2.01[/C][C]NA[/C][C]NA[/C][C]1.02174740381583[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.92[/C][C]NA[/C][C]NA[/C][C]0.971432378005643[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.99[/C][C]NA[/C][C]NA[/C][C]0.976176944873847[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]2.11[/C][C]NA[/C][C]NA[/C][C]0.98914427271252[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]2[/C][C]NA[/C][C]NA[/C][C]0.95363000682106[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36867&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	1.83	NA	NA	0.967158914529167	NA
2	1.89	NA	NA	0.999850562201415	NA
3	1.9	NA	NA	1.02317220815810	NA
4	2.01	NA	NA	1.04078502043631	NA
5	2.04	NA	NA	1.02242221248224	NA
6	2.04	NA	NA	1.02368422896303	NA
7	2.03	1.94873016003037	1.92791666666667	1.01079584700084	1.04170399865334
8	2.04	1.97708122638363	1.935	1.02174740381583	1.03182407114929
9	1.87	1.88457881333095	1.94	0.971432378005643	0.992264153015082
10	1.85	1.89174957108678	1.93791666666667	0.976176944873847	0.977930709368264
11	1.82	1.91069702012302	1.93166666666667	0.98914427271252	0.952531971752812
12	1.79	1.83335368811349	1.9225	0.95363000682106	0.976352796301898
13	1.88	1.84485562946438	1.9075	0.967158914529167	1.01904992996434
14	2.01	1.88596812295242	1.88625	0.999850562201415	1.06576562749821
15	1.9	1.91290570750225	1.86958333333333	1.02317220815810	0.993253348844307
16	1.96	1.93586013801153	1.86	1.04078502043631	1.01246983783305
17	1.94	1.89914925968576	1.8575	1.02242221248224	1.02151002092432
18	1.92	1.90533227115744	1.86125	1.02368422896303	1.00769825245948
19	1.79	1.87881678061281	1.85875	1.01079584700084	0.952727279461577
20	1.77	1.89321279365375	1.85291666666667	1.02174740381583	0.934918676829793
21	1.74	1.80038800723712	1.85333333333333	0.971432378005643	0.966458337317079
22	1.75	1.80633408841031	1.85041666666667	0.976176944873847	0.968813029233207
23	1.86	1.82167403557889	1.84166666666667	0.98914427271252	1.02103887066103
24	1.84	1.74832167917194	1.83333333333333	0.95363000682106	1.05243790197207
25	1.77	1.77070677935048	1.83083333333333	0.967158914529167	0.999600849017621
26	1.98	1.83805861684693	1.83833333333333	0.999850562201415	1.07722353457724
27	1.94	1.89158961983229	1.84875	1.02317220815810	1.02559243276668
28	1.85	1.93152353375971	1.85583333333333	1.04078502043631	0.957793144978655
29	1.84	1.89872325043056	1.85708333333333	1.02242221248224	0.96907224345768
30	1.82	1.89765463944022	1.85375	1.02368422896303	0.959078623777862
31	1.83	1.87292047150530	1.85291666666667	1.01079584700084	0.97708366577316
32	1.91	1.88767832854975	1.8475	1.02174740381583	1.01182493389507
33	1.85	1.78581652156704	1.83833333333333	0.971432378005643	1.03594069024327
34	1.81	1.79860602093006	1.8425	0.976176944873847	1.00633489432224
35	1.83	1.83445048243476	1.85458333333333	0.98914427271252	0.997573942454498
36	1.79	1.77772527104893	1.86416666666667	0.95363000682106	1.00690473896669
37	1.8	1.81301998186113	1.87458333333333	0.967158914529167	0.992818621972512
38	1.82	1.88513491415058	1.88541666666667	0.999850562201415	0.965448141848281
39	1.88	1.93592708218581	1.89208333333333	1.02317220815810	0.97111095624394
40	2.01	1.9770578784038	1.89958333333333	1.04078502043631	1.01666219383663
41	1.97	1.95325243509628	1.91041666666667	1.02242221248224	1.00857419379226
42	1.92	1.96334104413201	1.91791666666667	1.02368422896303	0.97792485199576
43	1.98	1.94367618079536	1.92291666666667	1.01079584700084	1.01868820514628
44	2.02	1.96856666468517	1.92666666666667	1.02174740381583	1.02612730177622
45	1.9	1.88012641493175	1.93541666666667	0.971432378005643	1.01057034511638
46	1.94	1.89988437896072	1.94625	0.976176944873847	1.02111476965836
47	1.96	1.93501348349387	1.95625	0.98914427271252	1.01291283844752
48	1.84	1.88143253429072	1.97291666666667	0.95363000682106	0.977978198242259
49	1.87	1.92021342822145	1.98541666666667	0.967158914529167	0.973850079640388
50	1.84	1.9892860143799	1.98958333333333	0.999850562201415	0.924954977162279
51	2.07	2.03909694650842	1.99291666666667	1.02317220815810	1.01515526446376
52	2.08	2.07983539917189	1.99833333333333	1.04078502043631	1.00007914127636
53	2.14	2.04910451751649	2.00416666666667	1.02242221248224	1.04435863651976
54	2.15	2.05589915983409	2.00833333333333	1.02368422896303	1.04577113605781
55	2.05	2.03549013689794	2.01375	1.01079584700084	1.00712843694943
56	2.05	2.06520693996275	2.02125	1.02174740381583	0.99263660233341
57	1.95	1.96553151149808	2.02333333333333	0.971432378005643	0.992098060291973
58	2.02	1.97431787100736	2.0225	0.976176944873847	1.02313818340171
59	2.02	1.99353785296269	2.01541666666667	0.98914427271252	1.01327396266792
60	1.88	1.91123347200387	2.00416666666667	0.95363000682106	0.983657950500874
61	1.96	1.93673572634466	2.0025	0.967158914529167	1.01201210538892
62	1.93	2.00220075080833	2.0025	0.999850562201415	0.96393930489778
63	2.03	2.04591809456281	1.99958333333333	1.02317220815810	0.9922195836651
64	2.1	2.07853441789634	1.99708333333333	1.04078502043631	1.01032726805909
65	1.95	2.04441841570928	1.99958333333333	1.02242221248224	0.953816491289764
66	2.07	2.05589915983409	2.00833333333333	1.02368422896303	1.00685872169287
67	2.09	NA	NA	1.01079584700084	NA
68	2.01	NA	NA	1.02174740381583	NA
69	1.92	NA	NA	0.971432378005643	NA
70	1.99	NA	NA	0.976176944873847	NA
71	2.11	NA	NA	0.98914427271252	NA
72	2	NA	NA	0.95363000682106	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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