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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 22 Dec 2014 15:28:55 +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/22/t141926221742m7svo1xh4t3xm.htm/, Retrieved Thu, 16 May 2024 06:00:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271402, Retrieved Thu, 16 May 2024 06:00:24 +0000

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148

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-       [Classical Decomposition] [] [2014-12-22 15:28:55] [d4b037465b17855a5e62fa4428b30753] [Current]

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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	'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271402&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271402&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271402&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	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.464	NA	NA	-0.0291687	NA
2	1.474	NA	NA	-0.00525208	NA
3	1.479	NA	NA	0.0176562	NA
4	1.517	NA	NA	0.0366313	NA
5	1.575	NA	NA	0.0235729	NA
6	1.627	NA	NA	0.0128229	NA
7	1.613	1.49464	1.46679	0.0278479	0.11836
8	1.558	1.47437	1.44883	0.0255396	0.0836271
9	1.545	1.45626	1.43233	0.0239312	0.0887354
10	1.406	1.39837	1.41554	-0.0171688	0.00762708
11	1.269	1.3467	1.39817	-0.0514688	-0.0776979
12	1.191	1.31572	1.38067	-0.0649438	-0.124723
13	1.231	1.33287	1.36204	-0.0291687	-0.101873
14	1.276	1.34116	1.34642	-0.00525208	-0.0651646
15	1.281	1.35145	1.33379	0.0176562	-0.0704479
16	1.312	1.36238	1.32575	0.0366313	-0.0503813
17	1.363	1.35407	1.3305	0.0235729	0.00892708
18	1.419	1.35778	1.34496	0.0128229	0.0612188
19	1.374	1.39035	1.3625	0.0278479	-0.0163479
20	1.422	1.40429	1.37875	0.0255396	0.0177104
21	1.378	1.41939	1.39546	0.0239312	-0.0413896
22	1.38	1.39679	1.41396	-0.0171688	-0.0167896
23	1.409	1.37832	1.42979	-0.0514688	0.0306771
24	1.398	1.37576	1.44071	-0.0649438	0.0222354
25	1.445	1.42096	1.45012	-0.0291687	0.0240437
26	1.452	1.45296	1.45821	-0.00525208	-0.00095625
27	1.506	1.48366	1.466	0.0176562	0.0223438
28	1.531	1.51226	1.47562	0.0366313	0.0187437
29	1.524	1.50799	1.48442	0.0235729	0.0160104
30	1.52	1.50845	1.49562	0.0128229	0.0115521
31	1.499	1.53676	1.50892	0.0278479	-0.0377646
32	1.491	1.54666	1.52112	0.0255396	-0.0556646
33	1.496	1.55639	1.53246	0.0239312	-0.0603896
34	1.493	1.52704	1.54421	-0.0171688	-0.0340396
35	1.507	1.50582	1.55729	-0.0514688	0.00117708
36	1.569	1.50422	1.56917	-0.0649438	0.0647771
37	1.593	1.55187	1.58104	-0.0291687	0.0411271
38	1.597	1.58846	1.59371	-0.00525208	0.00854375
39	1.633	1.62466	1.607	0.0176562	0.00834375
40	1.686	1.65676	1.62012	0.0366313	0.0292438
41	1.683	1.6542	1.63062	0.0235729	0.0288021
42	1.646	1.65028	1.63746	0.0128229	-0.00428125
43	1.658	1.67147	1.64362	0.0278479	-0.0134729
44	1.636	1.67837	1.65283	0.0255396	-0.0423729
45	1.67	1.68797	1.66404	0.0239312	-0.0179729
46	1.634	1.65796	1.67512	-0.0171688	-0.0239563
47	1.618	1.63174	1.68321	-0.0514688	-0.0137396
48	1.622	1.62406	1.689	-0.0649438	-0.00205625
49	1.688	1.66579	1.69496	-0.0291687	0.0222104
50	1.723	1.69896	1.70421	-0.00525208	0.0240437
51	1.776	1.73416	1.7165	0.0176562	0.0418437
52	1.809	1.76663	1.73	0.0366313	0.0423687
53	1.754	1.76699	1.74342	0.0235729	-0.0129896
54	1.714	1.76682	1.754	0.0128229	-0.0528229
55	1.733	1.7886	1.76075	0.0278479	-0.0555979
56	1.783	1.79112	1.76558	0.0255396	-0.00812292
57	1.818	1.79181	1.76788	0.0239312	0.0261938
58	1.81	1.74766	1.76483	-0.0171688	0.0623354
59	1.764	1.70924	1.76071	-0.0514688	0.0547604
60	1.73	1.69506	1.76	-0.0649438	0.0349438
61	1.742	1.73233	1.7615	-0.0291687	0.00966875
62	1.785	1.75629	1.76154	-0.00525208	0.0287104
63	1.769	1.77591	1.75825	0.0176562	-0.00690625
64	1.743	1.7878	1.75117	0.0366313	-0.0447979
65	1.721	1.76657	1.743	0.0235729	-0.0455729
66	1.73	1.75049	1.73767	0.0128229	-0.0204896
67	1.753	NA	NA	0.0278479	NA
68	1.764	NA	NA	0.0255396	NA
69	1.758	NA	NA	0.0239312	NA
70	1.7	NA	NA	-0.0171688	NA
71	1.678	NA	NA	-0.0514688	NA
72	1.688	NA	NA	-0.0649438	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.464 & NA & NA & -0.0291687 & NA \tabularnewline
2 & 1.474 & NA & NA & -0.00525208 & NA \tabularnewline
3 & 1.479 & NA & NA & 0.0176562 & NA \tabularnewline
4 & 1.517 & NA & NA & 0.0366313 & NA \tabularnewline
5 & 1.575 & NA & NA & 0.0235729 & NA \tabularnewline
6 & 1.627 & NA & NA & 0.0128229 & NA \tabularnewline
7 & 1.613 & 1.49464 & 1.46679 & 0.0278479 & 0.11836 \tabularnewline
8 & 1.558 & 1.47437 & 1.44883 & 0.0255396 & 0.0836271 \tabularnewline
9 & 1.545 & 1.45626 & 1.43233 & 0.0239312 & 0.0887354 \tabularnewline
10 & 1.406 & 1.39837 & 1.41554 & -0.0171688 & 0.00762708 \tabularnewline
11 & 1.269 & 1.3467 & 1.39817 & -0.0514688 & -0.0776979 \tabularnewline
12 & 1.191 & 1.31572 & 1.38067 & -0.0649438 & -0.124723 \tabularnewline
13 & 1.231 & 1.33287 & 1.36204 & -0.0291687 & -0.101873 \tabularnewline
14 & 1.276 & 1.34116 & 1.34642 & -0.00525208 & -0.0651646 \tabularnewline
15 & 1.281 & 1.35145 & 1.33379 & 0.0176562 & -0.0704479 \tabularnewline
16 & 1.312 & 1.36238 & 1.32575 & 0.0366313 & -0.0503813 \tabularnewline
17 & 1.363 & 1.35407 & 1.3305 & 0.0235729 & 0.00892708 \tabularnewline
18 & 1.419 & 1.35778 & 1.34496 & 0.0128229 & 0.0612188 \tabularnewline
19 & 1.374 & 1.39035 & 1.3625 & 0.0278479 & -0.0163479 \tabularnewline
20 & 1.422 & 1.40429 & 1.37875 & 0.0255396 & 0.0177104 \tabularnewline
21 & 1.378 & 1.41939 & 1.39546 & 0.0239312 & -0.0413896 \tabularnewline
22 & 1.38 & 1.39679 & 1.41396 & -0.0171688 & -0.0167896 \tabularnewline
23 & 1.409 & 1.37832 & 1.42979 & -0.0514688 & 0.0306771 \tabularnewline
24 & 1.398 & 1.37576 & 1.44071 & -0.0649438 & 0.0222354 \tabularnewline
25 & 1.445 & 1.42096 & 1.45012 & -0.0291687 & 0.0240437 \tabularnewline
26 & 1.452 & 1.45296 & 1.45821 & -0.00525208 & -0.00095625 \tabularnewline
27 & 1.506 & 1.48366 & 1.466 & 0.0176562 & 0.0223438 \tabularnewline
28 & 1.531 & 1.51226 & 1.47562 & 0.0366313 & 0.0187437 \tabularnewline
29 & 1.524 & 1.50799 & 1.48442 & 0.0235729 & 0.0160104 \tabularnewline
30 & 1.52 & 1.50845 & 1.49562 & 0.0128229 & 0.0115521 \tabularnewline
31 & 1.499 & 1.53676 & 1.50892 & 0.0278479 & -0.0377646 \tabularnewline
32 & 1.491 & 1.54666 & 1.52112 & 0.0255396 & -0.0556646 \tabularnewline
33 & 1.496 & 1.55639 & 1.53246 & 0.0239312 & -0.0603896 \tabularnewline
34 & 1.493 & 1.52704 & 1.54421 & -0.0171688 & -0.0340396 \tabularnewline
35 & 1.507 & 1.50582 & 1.55729 & -0.0514688 & 0.00117708 \tabularnewline
36 & 1.569 & 1.50422 & 1.56917 & -0.0649438 & 0.0647771 \tabularnewline
37 & 1.593 & 1.55187 & 1.58104 & -0.0291687 & 0.0411271 \tabularnewline
38 & 1.597 & 1.58846 & 1.59371 & -0.00525208 & 0.00854375 \tabularnewline
39 & 1.633 & 1.62466 & 1.607 & 0.0176562 & 0.00834375 \tabularnewline
40 & 1.686 & 1.65676 & 1.62012 & 0.0366313 & 0.0292438 \tabularnewline
41 & 1.683 & 1.6542 & 1.63062 & 0.0235729 & 0.0288021 \tabularnewline
42 & 1.646 & 1.65028 & 1.63746 & 0.0128229 & -0.00428125 \tabularnewline
43 & 1.658 & 1.67147 & 1.64362 & 0.0278479 & -0.0134729 \tabularnewline
44 & 1.636 & 1.67837 & 1.65283 & 0.0255396 & -0.0423729 \tabularnewline
45 & 1.67 & 1.68797 & 1.66404 & 0.0239312 & -0.0179729 \tabularnewline
46 & 1.634 & 1.65796 & 1.67512 & -0.0171688 & -0.0239563 \tabularnewline
47 & 1.618 & 1.63174 & 1.68321 & -0.0514688 & -0.0137396 \tabularnewline
48 & 1.622 & 1.62406 & 1.689 & -0.0649438 & -0.00205625 \tabularnewline
49 & 1.688 & 1.66579 & 1.69496 & -0.0291687 & 0.0222104 \tabularnewline
50 & 1.723 & 1.69896 & 1.70421 & -0.00525208 & 0.0240437 \tabularnewline
51 & 1.776 & 1.73416 & 1.7165 & 0.0176562 & 0.0418437 \tabularnewline
52 & 1.809 & 1.76663 & 1.73 & 0.0366313 & 0.0423687 \tabularnewline
53 & 1.754 & 1.76699 & 1.74342 & 0.0235729 & -0.0129896 \tabularnewline
54 & 1.714 & 1.76682 & 1.754 & 0.0128229 & -0.0528229 \tabularnewline
55 & 1.733 & 1.7886 & 1.76075 & 0.0278479 & -0.0555979 \tabularnewline
56 & 1.783 & 1.79112 & 1.76558 & 0.0255396 & -0.00812292 \tabularnewline
57 & 1.818 & 1.79181 & 1.76788 & 0.0239312 & 0.0261938 \tabularnewline
58 & 1.81 & 1.74766 & 1.76483 & -0.0171688 & 0.0623354 \tabularnewline
59 & 1.764 & 1.70924 & 1.76071 & -0.0514688 & 0.0547604 \tabularnewline
60 & 1.73 & 1.69506 & 1.76 & -0.0649438 & 0.0349438 \tabularnewline
61 & 1.742 & 1.73233 & 1.7615 & -0.0291687 & 0.00966875 \tabularnewline
62 & 1.785 & 1.75629 & 1.76154 & -0.00525208 & 0.0287104 \tabularnewline
63 & 1.769 & 1.77591 & 1.75825 & 0.0176562 & -0.00690625 \tabularnewline
64 & 1.743 & 1.7878 & 1.75117 & 0.0366313 & -0.0447979 \tabularnewline
65 & 1.721 & 1.76657 & 1.743 & 0.0235729 & -0.0455729 \tabularnewline
66 & 1.73 & 1.75049 & 1.73767 & 0.0128229 & -0.0204896 \tabularnewline
67 & 1.753 & NA & NA & 0.0278479 & NA \tabularnewline
68 & 1.764 & NA & NA & 0.0255396 & NA \tabularnewline
69 & 1.758 & NA & NA & 0.0239312 & NA \tabularnewline
70 & 1.7 & NA & NA & -0.0171688 & NA \tabularnewline
71 & 1.678 & NA & NA & -0.0514688 & NA \tabularnewline
72 & 1.688 & NA & NA & -0.0649438 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271402&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]1.464[/C][C]NA[/C][C]NA[/C][C]-0.0291687[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.474[/C][C]NA[/C][C]NA[/C][C]-0.00525208[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.479[/C][C]NA[/C][C]NA[/C][C]0.0176562[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.517[/C][C]NA[/C][C]NA[/C][C]0.0366313[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.575[/C][C]NA[/C][C]NA[/C][C]0.0235729[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.627[/C][C]NA[/C][C]NA[/C][C]0.0128229[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.613[/C][C]1.49464[/C][C]1.46679[/C][C]0.0278479[/C][C]0.11836[/C][/ROW]
[ROW][C]8[/C][C]1.558[/C][C]1.47437[/C][C]1.44883[/C][C]0.0255396[/C][C]0.0836271[/C][/ROW]
[ROW][C]9[/C][C]1.545[/C][C]1.45626[/C][C]1.43233[/C][C]0.0239312[/C][C]0.0887354[/C][/ROW]
[ROW][C]10[/C][C]1.406[/C][C]1.39837[/C][C]1.41554[/C][C]-0.0171688[/C][C]0.00762708[/C][/ROW]
[ROW][C]11[/C][C]1.269[/C][C]1.3467[/C][C]1.39817[/C][C]-0.0514688[/C][C]-0.0776979[/C][/ROW]
[ROW][C]12[/C][C]1.191[/C][C]1.31572[/C][C]1.38067[/C][C]-0.0649438[/C][C]-0.124723[/C][/ROW]
[ROW][C]13[/C][C]1.231[/C][C]1.33287[/C][C]1.36204[/C][C]-0.0291687[/C][C]-0.101873[/C][/ROW]
[ROW][C]14[/C][C]1.276[/C][C]1.34116[/C][C]1.34642[/C][C]-0.00525208[/C][C]-0.0651646[/C][/ROW]
[ROW][C]15[/C][C]1.281[/C][C]1.35145[/C][C]1.33379[/C][C]0.0176562[/C][C]-0.0704479[/C][/ROW]
[ROW][C]16[/C][C]1.312[/C][C]1.36238[/C][C]1.32575[/C][C]0.0366313[/C][C]-0.0503813[/C][/ROW]
[ROW][C]17[/C][C]1.363[/C][C]1.35407[/C][C]1.3305[/C][C]0.0235729[/C][C]0.00892708[/C][/ROW]
[ROW][C]18[/C][C]1.419[/C][C]1.35778[/C][C]1.34496[/C][C]0.0128229[/C][C]0.0612188[/C][/ROW]
[ROW][C]19[/C][C]1.374[/C][C]1.39035[/C][C]1.3625[/C][C]0.0278479[/C][C]-0.0163479[/C][/ROW]
[ROW][C]20[/C][C]1.422[/C][C]1.40429[/C][C]1.37875[/C][C]0.0255396[/C][C]0.0177104[/C][/ROW]
[ROW][C]21[/C][C]1.378[/C][C]1.41939[/C][C]1.39546[/C][C]0.0239312[/C][C]-0.0413896[/C][/ROW]
[ROW][C]22[/C][C]1.38[/C][C]1.39679[/C][C]1.41396[/C][C]-0.0171688[/C][C]-0.0167896[/C][/ROW]
[ROW][C]23[/C][C]1.409[/C][C]1.37832[/C][C]1.42979[/C][C]-0.0514688[/C][C]0.0306771[/C][/ROW]
[ROW][C]24[/C][C]1.398[/C][C]1.37576[/C][C]1.44071[/C][C]-0.0649438[/C][C]0.0222354[/C][/ROW]
[ROW][C]25[/C][C]1.445[/C][C]1.42096[/C][C]1.45012[/C][C]-0.0291687[/C][C]0.0240437[/C][/ROW]
[ROW][C]26[/C][C]1.452[/C][C]1.45296[/C][C]1.45821[/C][C]-0.00525208[/C][C]-0.00095625[/C][/ROW]
[ROW][C]27[/C][C]1.506[/C][C]1.48366[/C][C]1.466[/C][C]0.0176562[/C][C]0.0223438[/C][/ROW]
[ROW][C]28[/C][C]1.531[/C][C]1.51226[/C][C]1.47562[/C][C]0.0366313[/C][C]0.0187437[/C][/ROW]
[ROW][C]29[/C][C]1.524[/C][C]1.50799[/C][C]1.48442[/C][C]0.0235729[/C][C]0.0160104[/C][/ROW]
[ROW][C]30[/C][C]1.52[/C][C]1.50845[/C][C]1.49562[/C][C]0.0128229[/C][C]0.0115521[/C][/ROW]
[ROW][C]31[/C][C]1.499[/C][C]1.53676[/C][C]1.50892[/C][C]0.0278479[/C][C]-0.0377646[/C][/ROW]
[ROW][C]32[/C][C]1.491[/C][C]1.54666[/C][C]1.52112[/C][C]0.0255396[/C][C]-0.0556646[/C][/ROW]
[ROW][C]33[/C][C]1.496[/C][C]1.55639[/C][C]1.53246[/C][C]0.0239312[/C][C]-0.0603896[/C][/ROW]
[ROW][C]34[/C][C]1.493[/C][C]1.52704[/C][C]1.54421[/C][C]-0.0171688[/C][C]-0.0340396[/C][/ROW]
[ROW][C]35[/C][C]1.507[/C][C]1.50582[/C][C]1.55729[/C][C]-0.0514688[/C][C]0.00117708[/C][/ROW]
[ROW][C]36[/C][C]1.569[/C][C]1.50422[/C][C]1.56917[/C][C]-0.0649438[/C][C]0.0647771[/C][/ROW]
[ROW][C]37[/C][C]1.593[/C][C]1.55187[/C][C]1.58104[/C][C]-0.0291687[/C][C]0.0411271[/C][/ROW]
[ROW][C]38[/C][C]1.597[/C][C]1.58846[/C][C]1.59371[/C][C]-0.00525208[/C][C]0.00854375[/C][/ROW]
[ROW][C]39[/C][C]1.633[/C][C]1.62466[/C][C]1.607[/C][C]0.0176562[/C][C]0.00834375[/C][/ROW]
[ROW][C]40[/C][C]1.686[/C][C]1.65676[/C][C]1.62012[/C][C]0.0366313[/C][C]0.0292438[/C][/ROW]
[ROW][C]41[/C][C]1.683[/C][C]1.6542[/C][C]1.63062[/C][C]0.0235729[/C][C]0.0288021[/C][/ROW]
[ROW][C]42[/C][C]1.646[/C][C]1.65028[/C][C]1.63746[/C][C]0.0128229[/C][C]-0.00428125[/C][/ROW]
[ROW][C]43[/C][C]1.658[/C][C]1.67147[/C][C]1.64362[/C][C]0.0278479[/C][C]-0.0134729[/C][/ROW]
[ROW][C]44[/C][C]1.636[/C][C]1.67837[/C][C]1.65283[/C][C]0.0255396[/C][C]-0.0423729[/C][/ROW]
[ROW][C]45[/C][C]1.67[/C][C]1.68797[/C][C]1.66404[/C][C]0.0239312[/C][C]-0.0179729[/C][/ROW]
[ROW][C]46[/C][C]1.634[/C][C]1.65796[/C][C]1.67512[/C][C]-0.0171688[/C][C]-0.0239563[/C][/ROW]
[ROW][C]47[/C][C]1.618[/C][C]1.63174[/C][C]1.68321[/C][C]-0.0514688[/C][C]-0.0137396[/C][/ROW]
[ROW][C]48[/C][C]1.622[/C][C]1.62406[/C][C]1.689[/C][C]-0.0649438[/C][C]-0.00205625[/C][/ROW]
[ROW][C]49[/C][C]1.688[/C][C]1.66579[/C][C]1.69496[/C][C]-0.0291687[/C][C]0.0222104[/C][/ROW]
[ROW][C]50[/C][C]1.723[/C][C]1.69896[/C][C]1.70421[/C][C]-0.00525208[/C][C]0.0240437[/C][/ROW]
[ROW][C]51[/C][C]1.776[/C][C]1.73416[/C][C]1.7165[/C][C]0.0176562[/C][C]0.0418437[/C][/ROW]
[ROW][C]52[/C][C]1.809[/C][C]1.76663[/C][C]1.73[/C][C]0.0366313[/C][C]0.0423687[/C][/ROW]
[ROW][C]53[/C][C]1.754[/C][C]1.76699[/C][C]1.74342[/C][C]0.0235729[/C][C]-0.0129896[/C][/ROW]
[ROW][C]54[/C][C]1.714[/C][C]1.76682[/C][C]1.754[/C][C]0.0128229[/C][C]-0.0528229[/C][/ROW]
[ROW][C]55[/C][C]1.733[/C][C]1.7886[/C][C]1.76075[/C][C]0.0278479[/C][C]-0.0555979[/C][/ROW]
[ROW][C]56[/C][C]1.783[/C][C]1.79112[/C][C]1.76558[/C][C]0.0255396[/C][C]-0.00812292[/C][/ROW]
[ROW][C]57[/C][C]1.818[/C][C]1.79181[/C][C]1.76788[/C][C]0.0239312[/C][C]0.0261938[/C][/ROW]
[ROW][C]58[/C][C]1.81[/C][C]1.74766[/C][C]1.76483[/C][C]-0.0171688[/C][C]0.0623354[/C][/ROW]
[ROW][C]59[/C][C]1.764[/C][C]1.70924[/C][C]1.76071[/C][C]-0.0514688[/C][C]0.0547604[/C][/ROW]
[ROW][C]60[/C][C]1.73[/C][C]1.69506[/C][C]1.76[/C][C]-0.0649438[/C][C]0.0349438[/C][/ROW]
[ROW][C]61[/C][C]1.742[/C][C]1.73233[/C][C]1.7615[/C][C]-0.0291687[/C][C]0.00966875[/C][/ROW]
[ROW][C]62[/C][C]1.785[/C][C]1.75629[/C][C]1.76154[/C][C]-0.00525208[/C][C]0.0287104[/C][/ROW]
[ROW][C]63[/C][C]1.769[/C][C]1.77591[/C][C]1.75825[/C][C]0.0176562[/C][C]-0.00690625[/C][/ROW]
[ROW][C]64[/C][C]1.743[/C][C]1.7878[/C][C]1.75117[/C][C]0.0366313[/C][C]-0.0447979[/C][/ROW]
[ROW][C]65[/C][C]1.721[/C][C]1.76657[/C][C]1.743[/C][C]0.0235729[/C][C]-0.0455729[/C][/ROW]
[ROW][C]66[/C][C]1.73[/C][C]1.75049[/C][C]1.73767[/C][C]0.0128229[/C][C]-0.0204896[/C][/ROW]
[ROW][C]67[/C][C]1.753[/C][C]NA[/C][C]NA[/C][C]0.0278479[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.764[/C][C]NA[/C][C]NA[/C][C]0.0255396[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.758[/C][C]NA[/C][C]NA[/C][C]0.0239312[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.7[/C][C]NA[/C][C]NA[/C][C]-0.0171688[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.678[/C][C]NA[/C][C]NA[/C][C]-0.0514688[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.688[/C][C]NA[/C][C]NA[/C][C]-0.0649438[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271402&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271402&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	1.464	NA	NA	-0.0291687	NA
2	1.474	NA	NA	-0.00525208	NA
3	1.479	NA	NA	0.0176562	NA
4	1.517	NA	NA	0.0366313	NA
5	1.575	NA	NA	0.0235729	NA
6	1.627	NA	NA	0.0128229	NA
7	1.613	1.49464	1.46679	0.0278479	0.11836
8	1.558	1.47437	1.44883	0.0255396	0.0836271
9	1.545	1.45626	1.43233	0.0239312	0.0887354
10	1.406	1.39837	1.41554	-0.0171688	0.00762708
11	1.269	1.3467	1.39817	-0.0514688	-0.0776979
12	1.191	1.31572	1.38067	-0.0649438	-0.124723
13	1.231	1.33287	1.36204	-0.0291687	-0.101873
14	1.276	1.34116	1.34642	-0.00525208	-0.0651646
15	1.281	1.35145	1.33379	0.0176562	-0.0704479
16	1.312	1.36238	1.32575	0.0366313	-0.0503813
17	1.363	1.35407	1.3305	0.0235729	0.00892708
18	1.419	1.35778	1.34496	0.0128229	0.0612188
19	1.374	1.39035	1.3625	0.0278479	-0.0163479
20	1.422	1.40429	1.37875	0.0255396	0.0177104
21	1.378	1.41939	1.39546	0.0239312	-0.0413896
22	1.38	1.39679	1.41396	-0.0171688	-0.0167896
23	1.409	1.37832	1.42979	-0.0514688	0.0306771
24	1.398	1.37576	1.44071	-0.0649438	0.0222354
25	1.445	1.42096	1.45012	-0.0291687	0.0240437
26	1.452	1.45296	1.45821	-0.00525208	-0.00095625
27	1.506	1.48366	1.466	0.0176562	0.0223438
28	1.531	1.51226	1.47562	0.0366313	0.0187437
29	1.524	1.50799	1.48442	0.0235729	0.0160104
30	1.52	1.50845	1.49562	0.0128229	0.0115521
31	1.499	1.53676	1.50892	0.0278479	-0.0377646
32	1.491	1.54666	1.52112	0.0255396	-0.0556646
33	1.496	1.55639	1.53246	0.0239312	-0.0603896
34	1.493	1.52704	1.54421	-0.0171688	-0.0340396
35	1.507	1.50582	1.55729	-0.0514688	0.00117708
36	1.569	1.50422	1.56917	-0.0649438	0.0647771
37	1.593	1.55187	1.58104	-0.0291687	0.0411271
38	1.597	1.58846	1.59371	-0.00525208	0.00854375
39	1.633	1.62466	1.607	0.0176562	0.00834375
40	1.686	1.65676	1.62012	0.0366313	0.0292438
41	1.683	1.6542	1.63062	0.0235729	0.0288021
42	1.646	1.65028	1.63746	0.0128229	-0.00428125
43	1.658	1.67147	1.64362	0.0278479	-0.0134729
44	1.636	1.67837	1.65283	0.0255396	-0.0423729
45	1.67	1.68797	1.66404	0.0239312	-0.0179729
46	1.634	1.65796	1.67512	-0.0171688	-0.0239563
47	1.618	1.63174	1.68321	-0.0514688	-0.0137396
48	1.622	1.62406	1.689	-0.0649438	-0.00205625
49	1.688	1.66579	1.69496	-0.0291687	0.0222104
50	1.723	1.69896	1.70421	-0.00525208	0.0240437
51	1.776	1.73416	1.7165	0.0176562	0.0418437
52	1.809	1.76663	1.73	0.0366313	0.0423687
53	1.754	1.76699	1.74342	0.0235729	-0.0129896
54	1.714	1.76682	1.754	0.0128229	-0.0528229
55	1.733	1.7886	1.76075	0.0278479	-0.0555979
56	1.783	1.79112	1.76558	0.0255396	-0.00812292
57	1.818	1.79181	1.76788	0.0239312	0.0261938
58	1.81	1.74766	1.76483	-0.0171688	0.0623354
59	1.764	1.70924	1.76071	-0.0514688	0.0547604
60	1.73	1.69506	1.76	-0.0649438	0.0349438
61	1.742	1.73233	1.7615	-0.0291687	0.00966875
62	1.785	1.75629	1.76154	-0.00525208	0.0287104
63	1.769	1.77591	1.75825	0.0176562	-0.00690625
64	1.743	1.7878	1.75117	0.0366313	-0.0447979
65	1.721	1.76657	1.743	0.0235729	-0.0455729
66	1.73	1.75049	1.73767	0.0128229	-0.0204896
67	1.753	NA	NA	0.0278479	NA
68	1.764	NA	NA	0.0255396	NA
69	1.758	NA	NA	0.0239312	NA
70	1.7	NA	NA	-0.0171688	NA
71	1.678	NA	NA	-0.0514688	NA
72	1.688	NA	NA	-0.0649438	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 <- '12'
par1 <- 'multiplicative'
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