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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 29 Nov 2015 13:10:57 +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/2015/Nov/29/t1448802688find29c43u5x7r6.htm/, Retrieved Wed, 15 May 2024 13:34:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284427, Retrieved Wed, 15 May 2024 13:34:13 +0000

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-       [Classical Decomposition] [] [2015-11-29 13:10:57] [822b7cc50e4a16589bd43fa8379da378] [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	'Sir Maurice George Kendall' @ kendall.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 Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284427&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284427&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284427&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.71	NA	NA	0.418979	NA
2	100.46	NA	NA	-0.0698542	NA
3	100.46	NA	NA	-0.0435208	NA
4	100.67	NA	NA	-0.480604	NA
5	100.01	NA	NA	0.0679792	NA
6	100.01	NA	NA	0.288146	NA
7	99.99	99.6439	99.3862	0.257646	0.346104
8	99.98	99.3856	99.1396	0.246063	0.594354
9	99.87	98.8585	98.8146	0.0438958	1.01152
10	99.91	98.6311	98.4896	0.141563	1.27885
11	96.59	97.6926	98.16	-0.467354	-1.10265
12	96.99	97.4866	97.8896	-0.402938	-0.496646
13	96.68	98.0998	97.6808	0.418979	-1.41981
14	96.57	97.4051	97.475	-0.0698542	-0.835146
15	96.55	97.2394	97.2829	-0.0435208	-0.689396
16	96.78	96.6169	97.0975	-0.480604	0.163104
17	95.99	97.1188	97.0508	0.0679792	-1.12881
18	97.54	97.4494	97.1612	0.288146	0.0906042
19	97.45	97.5739	97.3162	0.257646	-0.123896
20	97.58	97.7094	97.4633	0.246063	-0.129396
21	97.66	97.6201	97.5762	0.0438958	0.0398542
22	97.67	97.8245	97.6829	0.141563	-0.154479
23	97.71	97.3476	97.815	-0.467354	0.362354
24	98.52	97.5125	97.9154	-0.402938	1.00752
25	98.87	98.3577	97.9388	0.418979	0.512271
26	97.91	97.8739	97.9437	-0.0698542	0.0361042
27	97.92	97.8598	97.9033	-0.0435208	0.0601875
28	97.97	97.3431	97.8237	-0.480604	0.626854
29	97.97	97.8109	97.7429	0.0679792	0.159104
30	97.97	97.9156	97.6275	0.288146	0.0543542
31	97.58	97.9081	97.6504	0.257646	-0.328062
32	97.57	98.1052	97.8592	0.246063	-0.535229
33	96.7	98.1256	98.0817	0.0438958	-1.42556
34	96.72	98.4028	98.2612	0.141563	-1.68281
35	96.72	97.9318	98.3992	-0.467354	-1.21181
36	96.74	98.1154	98.5183	-0.402938	-1.3754
37	101.2	99.0536	98.6346	0.418979	2.14644
38	100.59	98.6901	98.76	-0.0698542	1.89985
39	100.58	98.8681	98.9117	-0.0435208	1.71185
40	99.62	98.6402	99.1208	-0.480604	0.979771
41	99.63	99.4192	99.3512	0.0679792	0.210771
42	99.17	99.849	99.5608	0.288146	-0.678979
43	99.17	99.8322	99.5746	0.257646	-0.662229
44	98.99	99.6602	99.4142	0.246063	-0.670229
45	98.92	99.3026	99.2587	0.0438958	-0.382646
46	99.52	99.2182	99.0767	0.141563	0.301771
47	99.45	98.5589	99.0262	-0.467354	0.891104
48	99.04	98.7512	99.1542	-0.402938	0.288771
49	99.23	99.7236	99.3046	0.418979	-0.493562
50	98.71	99.396	99.4658	-0.0698542	-0.685979
51	98.73	99.5873	99.6308	-0.0435208	-0.857312
52	97.1	99.2744	99.755	-0.480604	-2.1744
53	100.94	99.9205	99.8525	0.0679792	1.01952
54	100.93	100.241	99.9529	0.288146	0.688938
55	101.02	100.268	100.01	0.257646	0.752354
56	101.01	100.285	100.039	0.246063	0.724771
57	100.86	100.119	100.075	0.0438958	0.741104
58	100.56	100.319	100.178	0.141563	0.240938
59	100.75	99.7047	100.172	-0.467354	1.04527
60	100.15	99.59	99.9929	-0.402938	0.560021
61	99.49	100.251	99.8321	0.418979	-0.761062
62	99.15	99.5806	99.6504	-0.0698542	-0.430562
63	99.15	99.3911	99.4346	-0.0435208	-0.241062
64	99.14	98.7511	99.2317	-0.480604	0.388937
65	98.77	99.0463	98.9783	0.0679792	-0.276313
66	98.8	98.9706	98.6825	0.288146	-0.170646
67	99.29	NA	NA	0.257646	NA
68	98.38	NA	NA	0.246063	NA
69	98.31	NA	NA	0.0438958	NA
70	98.24	NA	NA	0.141563	NA
71	96.99	NA	NA	-0.467354	NA
72	96.81	NA	NA	-0.402938	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.71 & NA & NA & 0.418979 & NA \tabularnewline
2 & 100.46 & NA & NA & -0.0698542 & NA \tabularnewline
3 & 100.46 & NA & NA & -0.0435208 & NA \tabularnewline
4 & 100.67 & NA & NA & -0.480604 & NA \tabularnewline
5 & 100.01 & NA & NA & 0.0679792 & NA \tabularnewline
6 & 100.01 & NA & NA & 0.288146 & NA \tabularnewline
7 & 99.99 & 99.6439 & 99.3862 & 0.257646 & 0.346104 \tabularnewline
8 & 99.98 & 99.3856 & 99.1396 & 0.246063 & 0.594354 \tabularnewline
9 & 99.87 & 98.8585 & 98.8146 & 0.0438958 & 1.01152 \tabularnewline
10 & 99.91 & 98.6311 & 98.4896 & 0.141563 & 1.27885 \tabularnewline
11 & 96.59 & 97.6926 & 98.16 & -0.467354 & -1.10265 \tabularnewline
12 & 96.99 & 97.4866 & 97.8896 & -0.402938 & -0.496646 \tabularnewline
13 & 96.68 & 98.0998 & 97.6808 & 0.418979 & -1.41981 \tabularnewline
14 & 96.57 & 97.4051 & 97.475 & -0.0698542 & -0.835146 \tabularnewline
15 & 96.55 & 97.2394 & 97.2829 & -0.0435208 & -0.689396 \tabularnewline
16 & 96.78 & 96.6169 & 97.0975 & -0.480604 & 0.163104 \tabularnewline
17 & 95.99 & 97.1188 & 97.0508 & 0.0679792 & -1.12881 \tabularnewline
18 & 97.54 & 97.4494 & 97.1612 & 0.288146 & 0.0906042 \tabularnewline
19 & 97.45 & 97.5739 & 97.3162 & 0.257646 & -0.123896 \tabularnewline
20 & 97.58 & 97.7094 & 97.4633 & 0.246063 & -0.129396 \tabularnewline
21 & 97.66 & 97.6201 & 97.5762 & 0.0438958 & 0.0398542 \tabularnewline
22 & 97.67 & 97.8245 & 97.6829 & 0.141563 & -0.154479 \tabularnewline
23 & 97.71 & 97.3476 & 97.815 & -0.467354 & 0.362354 \tabularnewline
24 & 98.52 & 97.5125 & 97.9154 & -0.402938 & 1.00752 \tabularnewline
25 & 98.87 & 98.3577 & 97.9388 & 0.418979 & 0.512271 \tabularnewline
26 & 97.91 & 97.8739 & 97.9437 & -0.0698542 & 0.0361042 \tabularnewline
27 & 97.92 & 97.8598 & 97.9033 & -0.0435208 & 0.0601875 \tabularnewline
28 & 97.97 & 97.3431 & 97.8237 & -0.480604 & 0.626854 \tabularnewline
29 & 97.97 & 97.8109 & 97.7429 & 0.0679792 & 0.159104 \tabularnewline
30 & 97.97 & 97.9156 & 97.6275 & 0.288146 & 0.0543542 \tabularnewline
31 & 97.58 & 97.9081 & 97.6504 & 0.257646 & -0.328062 \tabularnewline
32 & 97.57 & 98.1052 & 97.8592 & 0.246063 & -0.535229 \tabularnewline
33 & 96.7 & 98.1256 & 98.0817 & 0.0438958 & -1.42556 \tabularnewline
34 & 96.72 & 98.4028 & 98.2612 & 0.141563 & -1.68281 \tabularnewline
35 & 96.72 & 97.9318 & 98.3992 & -0.467354 & -1.21181 \tabularnewline
36 & 96.74 & 98.1154 & 98.5183 & -0.402938 & -1.3754 \tabularnewline
37 & 101.2 & 99.0536 & 98.6346 & 0.418979 & 2.14644 \tabularnewline
38 & 100.59 & 98.6901 & 98.76 & -0.0698542 & 1.89985 \tabularnewline
39 & 100.58 & 98.8681 & 98.9117 & -0.0435208 & 1.71185 \tabularnewline
40 & 99.62 & 98.6402 & 99.1208 & -0.480604 & 0.979771 \tabularnewline
41 & 99.63 & 99.4192 & 99.3512 & 0.0679792 & 0.210771 \tabularnewline
42 & 99.17 & 99.849 & 99.5608 & 0.288146 & -0.678979 \tabularnewline
43 & 99.17 & 99.8322 & 99.5746 & 0.257646 & -0.662229 \tabularnewline
44 & 98.99 & 99.6602 & 99.4142 & 0.246063 & -0.670229 \tabularnewline
45 & 98.92 & 99.3026 & 99.2587 & 0.0438958 & -0.382646 \tabularnewline
46 & 99.52 & 99.2182 & 99.0767 & 0.141563 & 0.301771 \tabularnewline
47 & 99.45 & 98.5589 & 99.0262 & -0.467354 & 0.891104 \tabularnewline
48 & 99.04 & 98.7512 & 99.1542 & -0.402938 & 0.288771 \tabularnewline
49 & 99.23 & 99.7236 & 99.3046 & 0.418979 & -0.493562 \tabularnewline
50 & 98.71 & 99.396 & 99.4658 & -0.0698542 & -0.685979 \tabularnewline
51 & 98.73 & 99.5873 & 99.6308 & -0.0435208 & -0.857312 \tabularnewline
52 & 97.1 & 99.2744 & 99.755 & -0.480604 & -2.1744 \tabularnewline
53 & 100.94 & 99.9205 & 99.8525 & 0.0679792 & 1.01952 \tabularnewline
54 & 100.93 & 100.241 & 99.9529 & 0.288146 & 0.688938 \tabularnewline
55 & 101.02 & 100.268 & 100.01 & 0.257646 & 0.752354 \tabularnewline
56 & 101.01 & 100.285 & 100.039 & 0.246063 & 0.724771 \tabularnewline
57 & 100.86 & 100.119 & 100.075 & 0.0438958 & 0.741104 \tabularnewline
58 & 100.56 & 100.319 & 100.178 & 0.141563 & 0.240938 \tabularnewline
59 & 100.75 & 99.7047 & 100.172 & -0.467354 & 1.04527 \tabularnewline
60 & 100.15 & 99.59 & 99.9929 & -0.402938 & 0.560021 \tabularnewline
61 & 99.49 & 100.251 & 99.8321 & 0.418979 & -0.761062 \tabularnewline
62 & 99.15 & 99.5806 & 99.6504 & -0.0698542 & -0.430562 \tabularnewline
63 & 99.15 & 99.3911 & 99.4346 & -0.0435208 & -0.241062 \tabularnewline
64 & 99.14 & 98.7511 & 99.2317 & -0.480604 & 0.388937 \tabularnewline
65 & 98.77 & 99.0463 & 98.9783 & 0.0679792 & -0.276313 \tabularnewline
66 & 98.8 & 98.9706 & 98.6825 & 0.288146 & -0.170646 \tabularnewline
67 & 99.29 & NA & NA & 0.257646 & NA \tabularnewline
68 & 98.38 & NA & NA & 0.246063 & NA \tabularnewline
69 & 98.31 & NA & NA & 0.0438958 & NA \tabularnewline
70 & 98.24 & NA & NA & 0.141563 & NA \tabularnewline
71 & 96.99 & NA & NA & -0.467354 & NA \tabularnewline
72 & 96.81 & NA & NA & -0.402938 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284427&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]98.71[/C][C]NA[/C][C]NA[/C][C]0.418979[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.46[/C][C]NA[/C][C]NA[/C][C]-0.0698542[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.46[/C][C]NA[/C][C]NA[/C][C]-0.0435208[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.67[/C][C]NA[/C][C]NA[/C][C]-0.480604[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.01[/C][C]NA[/C][C]NA[/C][C]0.0679792[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.01[/C][C]NA[/C][C]NA[/C][C]0.288146[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.99[/C][C]99.6439[/C][C]99.3862[/C][C]0.257646[/C][C]0.346104[/C][/ROW]
[ROW][C]8[/C][C]99.98[/C][C]99.3856[/C][C]99.1396[/C][C]0.246063[/C][C]0.594354[/C][/ROW]
[ROW][C]9[/C][C]99.87[/C][C]98.8585[/C][C]98.8146[/C][C]0.0438958[/C][C]1.01152[/C][/ROW]
[ROW][C]10[/C][C]99.91[/C][C]98.6311[/C][C]98.4896[/C][C]0.141563[/C][C]1.27885[/C][/ROW]
[ROW][C]11[/C][C]96.59[/C][C]97.6926[/C][C]98.16[/C][C]-0.467354[/C][C]-1.10265[/C][/ROW]
[ROW][C]12[/C][C]96.99[/C][C]97.4866[/C][C]97.8896[/C][C]-0.402938[/C][C]-0.496646[/C][/ROW]
[ROW][C]13[/C][C]96.68[/C][C]98.0998[/C][C]97.6808[/C][C]0.418979[/C][C]-1.41981[/C][/ROW]
[ROW][C]14[/C][C]96.57[/C][C]97.4051[/C][C]97.475[/C][C]-0.0698542[/C][C]-0.835146[/C][/ROW]
[ROW][C]15[/C][C]96.55[/C][C]97.2394[/C][C]97.2829[/C][C]-0.0435208[/C][C]-0.689396[/C][/ROW]
[ROW][C]16[/C][C]96.78[/C][C]96.6169[/C][C]97.0975[/C][C]-0.480604[/C][C]0.163104[/C][/ROW]
[ROW][C]17[/C][C]95.99[/C][C]97.1188[/C][C]97.0508[/C][C]0.0679792[/C][C]-1.12881[/C][/ROW]
[ROW][C]18[/C][C]97.54[/C][C]97.4494[/C][C]97.1612[/C][C]0.288146[/C][C]0.0906042[/C][/ROW]
[ROW][C]19[/C][C]97.45[/C][C]97.5739[/C][C]97.3162[/C][C]0.257646[/C][C]-0.123896[/C][/ROW]
[ROW][C]20[/C][C]97.58[/C][C]97.7094[/C][C]97.4633[/C][C]0.246063[/C][C]-0.129396[/C][/ROW]
[ROW][C]21[/C][C]97.66[/C][C]97.6201[/C][C]97.5762[/C][C]0.0438958[/C][C]0.0398542[/C][/ROW]
[ROW][C]22[/C][C]97.67[/C][C]97.8245[/C][C]97.6829[/C][C]0.141563[/C][C]-0.154479[/C][/ROW]
[ROW][C]23[/C][C]97.71[/C][C]97.3476[/C][C]97.815[/C][C]-0.467354[/C][C]0.362354[/C][/ROW]
[ROW][C]24[/C][C]98.52[/C][C]97.5125[/C][C]97.9154[/C][C]-0.402938[/C][C]1.00752[/C][/ROW]
[ROW][C]25[/C][C]98.87[/C][C]98.3577[/C][C]97.9388[/C][C]0.418979[/C][C]0.512271[/C][/ROW]
[ROW][C]26[/C][C]97.91[/C][C]97.8739[/C][C]97.9437[/C][C]-0.0698542[/C][C]0.0361042[/C][/ROW]
[ROW][C]27[/C][C]97.92[/C][C]97.8598[/C][C]97.9033[/C][C]-0.0435208[/C][C]0.0601875[/C][/ROW]
[ROW][C]28[/C][C]97.97[/C][C]97.3431[/C][C]97.8237[/C][C]-0.480604[/C][C]0.626854[/C][/ROW]
[ROW][C]29[/C][C]97.97[/C][C]97.8109[/C][C]97.7429[/C][C]0.0679792[/C][C]0.159104[/C][/ROW]
[ROW][C]30[/C][C]97.97[/C][C]97.9156[/C][C]97.6275[/C][C]0.288146[/C][C]0.0543542[/C][/ROW]
[ROW][C]31[/C][C]97.58[/C][C]97.9081[/C][C]97.6504[/C][C]0.257646[/C][C]-0.328062[/C][/ROW]
[ROW][C]32[/C][C]97.57[/C][C]98.1052[/C][C]97.8592[/C][C]0.246063[/C][C]-0.535229[/C][/ROW]
[ROW][C]33[/C][C]96.7[/C][C]98.1256[/C][C]98.0817[/C][C]0.0438958[/C][C]-1.42556[/C][/ROW]
[ROW][C]34[/C][C]96.72[/C][C]98.4028[/C][C]98.2612[/C][C]0.141563[/C][C]-1.68281[/C][/ROW]
[ROW][C]35[/C][C]96.72[/C][C]97.9318[/C][C]98.3992[/C][C]-0.467354[/C][C]-1.21181[/C][/ROW]
[ROW][C]36[/C][C]96.74[/C][C]98.1154[/C][C]98.5183[/C][C]-0.402938[/C][C]-1.3754[/C][/ROW]
[ROW][C]37[/C][C]101.2[/C][C]99.0536[/C][C]98.6346[/C][C]0.418979[/C][C]2.14644[/C][/ROW]
[ROW][C]38[/C][C]100.59[/C][C]98.6901[/C][C]98.76[/C][C]-0.0698542[/C][C]1.89985[/C][/ROW]
[ROW][C]39[/C][C]100.58[/C][C]98.8681[/C][C]98.9117[/C][C]-0.0435208[/C][C]1.71185[/C][/ROW]
[ROW][C]40[/C][C]99.62[/C][C]98.6402[/C][C]99.1208[/C][C]-0.480604[/C][C]0.979771[/C][/ROW]
[ROW][C]41[/C][C]99.63[/C][C]99.4192[/C][C]99.3512[/C][C]0.0679792[/C][C]0.210771[/C][/ROW]
[ROW][C]42[/C][C]99.17[/C][C]99.849[/C][C]99.5608[/C][C]0.288146[/C][C]-0.678979[/C][/ROW]
[ROW][C]43[/C][C]99.17[/C][C]99.8322[/C][C]99.5746[/C][C]0.257646[/C][C]-0.662229[/C][/ROW]
[ROW][C]44[/C][C]98.99[/C][C]99.6602[/C][C]99.4142[/C][C]0.246063[/C][C]-0.670229[/C][/ROW]
[ROW][C]45[/C][C]98.92[/C][C]99.3026[/C][C]99.2587[/C][C]0.0438958[/C][C]-0.382646[/C][/ROW]
[ROW][C]46[/C][C]99.52[/C][C]99.2182[/C][C]99.0767[/C][C]0.141563[/C][C]0.301771[/C][/ROW]
[ROW][C]47[/C][C]99.45[/C][C]98.5589[/C][C]99.0262[/C][C]-0.467354[/C][C]0.891104[/C][/ROW]
[ROW][C]48[/C][C]99.04[/C][C]98.7512[/C][C]99.1542[/C][C]-0.402938[/C][C]0.288771[/C][/ROW]
[ROW][C]49[/C][C]99.23[/C][C]99.7236[/C][C]99.3046[/C][C]0.418979[/C][C]-0.493562[/C][/ROW]
[ROW][C]50[/C][C]98.71[/C][C]99.396[/C][C]99.4658[/C][C]-0.0698542[/C][C]-0.685979[/C][/ROW]
[ROW][C]51[/C][C]98.73[/C][C]99.5873[/C][C]99.6308[/C][C]-0.0435208[/C][C]-0.857312[/C][/ROW]
[ROW][C]52[/C][C]97.1[/C][C]99.2744[/C][C]99.755[/C][C]-0.480604[/C][C]-2.1744[/C][/ROW]
[ROW][C]53[/C][C]100.94[/C][C]99.9205[/C][C]99.8525[/C][C]0.0679792[/C][C]1.01952[/C][/ROW]
[ROW][C]54[/C][C]100.93[/C][C]100.241[/C][C]99.9529[/C][C]0.288146[/C][C]0.688938[/C][/ROW]
[ROW][C]55[/C][C]101.02[/C][C]100.268[/C][C]100.01[/C][C]0.257646[/C][C]0.752354[/C][/ROW]
[ROW][C]56[/C][C]101.01[/C][C]100.285[/C][C]100.039[/C][C]0.246063[/C][C]0.724771[/C][/ROW]
[ROW][C]57[/C][C]100.86[/C][C]100.119[/C][C]100.075[/C][C]0.0438958[/C][C]0.741104[/C][/ROW]
[ROW][C]58[/C][C]100.56[/C][C]100.319[/C][C]100.178[/C][C]0.141563[/C][C]0.240938[/C][/ROW]
[ROW][C]59[/C][C]100.75[/C][C]99.7047[/C][C]100.172[/C][C]-0.467354[/C][C]1.04527[/C][/ROW]
[ROW][C]60[/C][C]100.15[/C][C]99.59[/C][C]99.9929[/C][C]-0.402938[/C][C]0.560021[/C][/ROW]
[ROW][C]61[/C][C]99.49[/C][C]100.251[/C][C]99.8321[/C][C]0.418979[/C][C]-0.761062[/C][/ROW]
[ROW][C]62[/C][C]99.15[/C][C]99.5806[/C][C]99.6504[/C][C]-0.0698542[/C][C]-0.430562[/C][/ROW]
[ROW][C]63[/C][C]99.15[/C][C]99.3911[/C][C]99.4346[/C][C]-0.0435208[/C][C]-0.241062[/C][/ROW]
[ROW][C]64[/C][C]99.14[/C][C]98.7511[/C][C]99.2317[/C][C]-0.480604[/C][C]0.388937[/C][/ROW]
[ROW][C]65[/C][C]98.77[/C][C]99.0463[/C][C]98.9783[/C][C]0.0679792[/C][C]-0.276313[/C][/ROW]
[ROW][C]66[/C][C]98.8[/C][C]98.9706[/C][C]98.6825[/C][C]0.288146[/C][C]-0.170646[/C][/ROW]
[ROW][C]67[/C][C]99.29[/C][C]NA[/C][C]NA[/C][C]0.257646[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]98.38[/C][C]NA[/C][C]NA[/C][C]0.246063[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]98.31[/C][C]NA[/C][C]NA[/C][C]0.0438958[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]98.24[/C][C]NA[/C][C]NA[/C][C]0.141563[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]96.99[/C][C]NA[/C][C]NA[/C][C]-0.467354[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]96.81[/C][C]NA[/C][C]NA[/C][C]-0.402938[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284427&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284427&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	98.71	NA	NA	0.418979	NA
2	100.46	NA	NA	-0.0698542	NA
3	100.46	NA	NA	-0.0435208	NA
4	100.67	NA	NA	-0.480604	NA
5	100.01	NA	NA	0.0679792	NA
6	100.01	NA	NA	0.288146	NA
7	99.99	99.6439	99.3862	0.257646	0.346104
8	99.98	99.3856	99.1396	0.246063	0.594354
9	99.87	98.8585	98.8146	0.0438958	1.01152
10	99.91	98.6311	98.4896	0.141563	1.27885
11	96.59	97.6926	98.16	-0.467354	-1.10265
12	96.99	97.4866	97.8896	-0.402938	-0.496646
13	96.68	98.0998	97.6808	0.418979	-1.41981
14	96.57	97.4051	97.475	-0.0698542	-0.835146
15	96.55	97.2394	97.2829	-0.0435208	-0.689396
16	96.78	96.6169	97.0975	-0.480604	0.163104
17	95.99	97.1188	97.0508	0.0679792	-1.12881
18	97.54	97.4494	97.1612	0.288146	0.0906042
19	97.45	97.5739	97.3162	0.257646	-0.123896
20	97.58	97.7094	97.4633	0.246063	-0.129396
21	97.66	97.6201	97.5762	0.0438958	0.0398542
22	97.67	97.8245	97.6829	0.141563	-0.154479
23	97.71	97.3476	97.815	-0.467354	0.362354
24	98.52	97.5125	97.9154	-0.402938	1.00752
25	98.87	98.3577	97.9388	0.418979	0.512271
26	97.91	97.8739	97.9437	-0.0698542	0.0361042
27	97.92	97.8598	97.9033	-0.0435208	0.0601875
28	97.97	97.3431	97.8237	-0.480604	0.626854
29	97.97	97.8109	97.7429	0.0679792	0.159104
30	97.97	97.9156	97.6275	0.288146	0.0543542
31	97.58	97.9081	97.6504	0.257646	-0.328062
32	97.57	98.1052	97.8592	0.246063	-0.535229
33	96.7	98.1256	98.0817	0.0438958	-1.42556
34	96.72	98.4028	98.2612	0.141563	-1.68281
35	96.72	97.9318	98.3992	-0.467354	-1.21181
36	96.74	98.1154	98.5183	-0.402938	-1.3754
37	101.2	99.0536	98.6346	0.418979	2.14644
38	100.59	98.6901	98.76	-0.0698542	1.89985
39	100.58	98.8681	98.9117	-0.0435208	1.71185
40	99.62	98.6402	99.1208	-0.480604	0.979771
41	99.63	99.4192	99.3512	0.0679792	0.210771
42	99.17	99.849	99.5608	0.288146	-0.678979
43	99.17	99.8322	99.5746	0.257646	-0.662229
44	98.99	99.6602	99.4142	0.246063	-0.670229
45	98.92	99.3026	99.2587	0.0438958	-0.382646
46	99.52	99.2182	99.0767	0.141563	0.301771
47	99.45	98.5589	99.0262	-0.467354	0.891104
48	99.04	98.7512	99.1542	-0.402938	0.288771
49	99.23	99.7236	99.3046	0.418979	-0.493562
50	98.71	99.396	99.4658	-0.0698542	-0.685979
51	98.73	99.5873	99.6308	-0.0435208	-0.857312
52	97.1	99.2744	99.755	-0.480604	-2.1744
53	100.94	99.9205	99.8525	0.0679792	1.01952
54	100.93	100.241	99.9529	0.288146	0.688938
55	101.02	100.268	100.01	0.257646	0.752354
56	101.01	100.285	100.039	0.246063	0.724771
57	100.86	100.119	100.075	0.0438958	0.741104
58	100.56	100.319	100.178	0.141563	0.240938
59	100.75	99.7047	100.172	-0.467354	1.04527
60	100.15	99.59	99.9929	-0.402938	0.560021
61	99.49	100.251	99.8321	0.418979	-0.761062
62	99.15	99.5806	99.6504	-0.0698542	-0.430562
63	99.15	99.3911	99.4346	-0.0435208	-0.241062
64	99.14	98.7511	99.2317	-0.480604	0.388937
65	98.77	99.0463	98.9783	0.0679792	-0.276313
66	98.8	98.9706	98.6825	0.288146	-0.170646
67	99.29	NA	NA	0.257646	NA
68	98.38	NA	NA	0.246063	NA
69	98.31	NA	NA	0.0438958	NA
70	98.24	NA	NA	0.141563	NA
71	96.99	NA	NA	-0.467354	NA
72	96.81	NA	NA	-0.402938	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