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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 09 Dec 2013 04:08:30 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/09/t13865801294h17j3sxmqvzrgq.htm/, Retrieved Fri, 26 Apr 2024 23:54:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231582, Retrieved Fri, 26 Apr 2024 23:54:16 +0000

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126

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-       [Classical Decomposition] [] [2013-12-09 09:08:30] [d41d8cd98f00b204e9800998ecf8427e] [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	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231582&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231582&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231582&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	4 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	9.84	NA	NA	-0.00903935	NA
2	9.87	NA	NA	0.0254051	NA
3	9.9	NA	NA	0.0266551	NA
4	9.9	NA	NA	0.00915509	NA
5	9.87	NA	NA	0.0033912	NA
6	9.87	NA	NA	-0.00744213	NA
7	9.88	9.82422	9.82625	-0.00202546	0.0557755
8	9.76	9.80207	9.82167	-0.0195949	-0.0420718
9	9.76	9.80541	9.81792	-0.0125116	-0.0454051
10	9.76	9.79159	9.81375	-0.0221644	-0.0315856
11	9.77	9.82193	9.8125	0.00943287	-0.0519329
12	9.77	9.81332	9.81458	-0.00126157	-0.0433218
13	9.77	9.80846	9.8175	-0.00903935	-0.0384606
14	9.83	9.85082	9.82542	0.0254051	-0.0208218
15	9.85	9.86499	9.83833	0.0266551	-0.0149884
16	9.85	9.86082	9.85167	0.00915509	-0.0108218
17	9.89	9.86964	9.86625	0.0033912	0.0203588
18	9.9	9.87506	9.8825	-0.00744213	0.0249421
19	9.92	9.89756	9.89958	-0.00202546	0.0224421
20	9.91	9.89832	9.91792	-0.0195949	0.0116782
21	9.92	9.92416	9.93667	-0.0125116	-0.00415509
22	9.92	9.93492	9.95708	-0.0221644	-0.014919
23	9.96	9.98652	9.97708	0.00943287	-0.0265162
24	9.97	9.99291	9.99417	-0.00126157	-0.0229051
25	9.98	10.001	10.01	-0.00903935	-0.0209606
26	10.06	10.0546	10.0292	0.0254051	0.00542824
27	10.07	10.0796	10.0529	0.0266551	-0.00957176
28	10.12	10.0858	10.0767	0.00915509	0.0341782
29	10.1	10.1096	10.1062	0.0033912	-0.0096412
30	10.1	10.1342	10.1417	-0.00744213	-0.0342245
31	10.1	10.1742	10.1763	-0.00202546	-0.0742245
32	10.19	10.19	10.2096	-0.0195949	1.15741e-05
33	10.21	10.2308	10.2433	-0.0125116	-0.0208218
34	10.2	10.2537	10.2758	-0.0221644	-0.053669
35	10.39	10.3165	10.3071	0.00943287	0.0734838
36	10.39	10.3383	10.3396	-0.00126157	0.0516782
37	10.39	10.3635	10.3725	-0.00903935	0.0265394
38	10.45	10.4279	10.4025	0.0254051	0.0220949
39	10.49	10.455	10.4283	0.0266551	0.0350116
40	10.48	10.4637	10.4546	0.00915509	0.0162616
41	10.49	10.478	10.4746	0.0033912	0.0120255
42	10.49	10.4796	10.4871	-0.00744213	0.0103588
43	10.5	10.498	10.5	-0.00202546	0.00202546
44	10.51	10.4925	10.5121	-0.0195949	0.0175116
45	10.51	10.5092	10.5217	-0.0125116	0.000844907
46	10.53	10.507	10.5292	-0.0221644	0.0229977
47	10.54	10.5453	10.5358	0.00943287	-0.0052662
48	10.54	10.5421	10.5433	-0.00126157	-0.00207176
49	10.55	10.5439	10.5529	-0.00903935	0.00612269
50	10.58	10.5887	10.5633	0.0254051	-0.00873843
51	10.59	10.6012	10.5746	0.0266551	-0.0112384
52	10.56	10.5967	10.5875	0.00915509	-0.0366551
53	10.57	10.6051	10.6017	0.0033912	-0.0350579
54	10.59	10.6092	10.6167	-0.00744213	-0.0192245
55	10.63	10.6296	10.6317	-0.00202546	0.000358796
56	10.63	10.6267	10.6463	-0.0195949	0.00334491
57	10.66	10.6487	10.6613	-0.0125116	0.0112616
58	10.69	10.6566	10.6788	-0.0221644	0.0334144
59	10.72	10.7086	10.6992	0.00943287	0.0114005
60	10.72	10.7187	10.72	-0.00126157	0.00126157
61	10.73	10.7301	10.7392	-0.00903935	-0.000127315
62	10.75	10.7842	10.7588	0.0254051	-0.0341551
63	10.78	10.8087	10.7821	0.0266551	-0.0287384
64	10.79	10.8162	10.8071	0.00915509	-0.0262384
65	10.83	10.8342	10.8308	0.0033912	-0.00422454
66	10.83	10.8484	10.8558	-0.00744213	-0.0183912
67	10.85	10.8817	10.8838	-0.00202546	-0.0317245
68	10.88	10.8958	10.9154	-0.0195949	-0.0158218
69	10.97	10.9371	10.9496	-0.0125116	0.0329282
70	10.98	10.9616	10.9837	-0.0221644	0.0184144
71	11	11.0265	11.0171	0.00943287	-0.0265162
72	11.04	11.05	11.0512	-0.00126157	-0.00998843
73	11.08	11.0785	11.0875	-0.00903935	0.00153935
74	11.16	11.1492	11.1237	0.0254051	0.0108449
75	11.19	11.1858	11.1592	0.0266551	0.00417824
76	11.2	11.2021	11.1929	0.00915509	-0.00207176
77	11.22	11.2288	11.2254	0.0033912	-0.00880787
78	11.26	11.2488	11.2562	-0.00744213	0.0111921
79	11.29	NA	NA	-0.00202546	NA
80	11.31	NA	NA	-0.0195949	NA
81	11.39	NA	NA	-0.0125116	NA
82	11.37	NA	NA	-0.0221644	NA
83	11.39	NA	NA	0.00943287	NA
84	11.39	NA	NA	-0.00126157	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 9.84 & NA & NA & -0.00903935 & NA \tabularnewline
2 & 9.87 & NA & NA & 0.0254051 & NA \tabularnewline
3 & 9.9 & NA & NA & 0.0266551 & NA \tabularnewline
4 & 9.9 & NA & NA & 0.00915509 & NA \tabularnewline
5 & 9.87 & NA & NA & 0.0033912 & NA \tabularnewline
6 & 9.87 & NA & NA & -0.00744213 & NA \tabularnewline
7 & 9.88 & 9.82422 & 9.82625 & -0.00202546 & 0.0557755 \tabularnewline
8 & 9.76 & 9.80207 & 9.82167 & -0.0195949 & -0.0420718 \tabularnewline
9 & 9.76 & 9.80541 & 9.81792 & -0.0125116 & -0.0454051 \tabularnewline
10 & 9.76 & 9.79159 & 9.81375 & -0.0221644 & -0.0315856 \tabularnewline
11 & 9.77 & 9.82193 & 9.8125 & 0.00943287 & -0.0519329 \tabularnewline
12 & 9.77 & 9.81332 & 9.81458 & -0.00126157 & -0.0433218 \tabularnewline
13 & 9.77 & 9.80846 & 9.8175 & -0.00903935 & -0.0384606 \tabularnewline
14 & 9.83 & 9.85082 & 9.82542 & 0.0254051 & -0.0208218 \tabularnewline
15 & 9.85 & 9.86499 & 9.83833 & 0.0266551 & -0.0149884 \tabularnewline
16 & 9.85 & 9.86082 & 9.85167 & 0.00915509 & -0.0108218 \tabularnewline
17 & 9.89 & 9.86964 & 9.86625 & 0.0033912 & 0.0203588 \tabularnewline
18 & 9.9 & 9.87506 & 9.8825 & -0.00744213 & 0.0249421 \tabularnewline
19 & 9.92 & 9.89756 & 9.89958 & -0.00202546 & 0.0224421 \tabularnewline
20 & 9.91 & 9.89832 & 9.91792 & -0.0195949 & 0.0116782 \tabularnewline
21 & 9.92 & 9.92416 & 9.93667 & -0.0125116 & -0.00415509 \tabularnewline
22 & 9.92 & 9.93492 & 9.95708 & -0.0221644 & -0.014919 \tabularnewline
23 & 9.96 & 9.98652 & 9.97708 & 0.00943287 & -0.0265162 \tabularnewline
24 & 9.97 & 9.99291 & 9.99417 & -0.00126157 & -0.0229051 \tabularnewline
25 & 9.98 & 10.001 & 10.01 & -0.00903935 & -0.0209606 \tabularnewline
26 & 10.06 & 10.0546 & 10.0292 & 0.0254051 & 0.00542824 \tabularnewline
27 & 10.07 & 10.0796 & 10.0529 & 0.0266551 & -0.00957176 \tabularnewline
28 & 10.12 & 10.0858 & 10.0767 & 0.00915509 & 0.0341782 \tabularnewline
29 & 10.1 & 10.1096 & 10.1062 & 0.0033912 & -0.0096412 \tabularnewline
30 & 10.1 & 10.1342 & 10.1417 & -0.00744213 & -0.0342245 \tabularnewline
31 & 10.1 & 10.1742 & 10.1763 & -0.00202546 & -0.0742245 \tabularnewline
32 & 10.19 & 10.19 & 10.2096 & -0.0195949 & 1.15741e-05 \tabularnewline
33 & 10.21 & 10.2308 & 10.2433 & -0.0125116 & -0.0208218 \tabularnewline
34 & 10.2 & 10.2537 & 10.2758 & -0.0221644 & -0.053669 \tabularnewline
35 & 10.39 & 10.3165 & 10.3071 & 0.00943287 & 0.0734838 \tabularnewline
36 & 10.39 & 10.3383 & 10.3396 & -0.00126157 & 0.0516782 \tabularnewline
37 & 10.39 & 10.3635 & 10.3725 & -0.00903935 & 0.0265394 \tabularnewline
38 & 10.45 & 10.4279 & 10.4025 & 0.0254051 & 0.0220949 \tabularnewline
39 & 10.49 & 10.455 & 10.4283 & 0.0266551 & 0.0350116 \tabularnewline
40 & 10.48 & 10.4637 & 10.4546 & 0.00915509 & 0.0162616 \tabularnewline
41 & 10.49 & 10.478 & 10.4746 & 0.0033912 & 0.0120255 \tabularnewline
42 & 10.49 & 10.4796 & 10.4871 & -0.00744213 & 0.0103588 \tabularnewline
43 & 10.5 & 10.498 & 10.5 & -0.00202546 & 0.00202546 \tabularnewline
44 & 10.51 & 10.4925 & 10.5121 & -0.0195949 & 0.0175116 \tabularnewline
45 & 10.51 & 10.5092 & 10.5217 & -0.0125116 & 0.000844907 \tabularnewline
46 & 10.53 & 10.507 & 10.5292 & -0.0221644 & 0.0229977 \tabularnewline
47 & 10.54 & 10.5453 & 10.5358 & 0.00943287 & -0.0052662 \tabularnewline
48 & 10.54 & 10.5421 & 10.5433 & -0.00126157 & -0.00207176 \tabularnewline
49 & 10.55 & 10.5439 & 10.5529 & -0.00903935 & 0.00612269 \tabularnewline
50 & 10.58 & 10.5887 & 10.5633 & 0.0254051 & -0.00873843 \tabularnewline
51 & 10.59 & 10.6012 & 10.5746 & 0.0266551 & -0.0112384 \tabularnewline
52 & 10.56 & 10.5967 & 10.5875 & 0.00915509 & -0.0366551 \tabularnewline
53 & 10.57 & 10.6051 & 10.6017 & 0.0033912 & -0.0350579 \tabularnewline
54 & 10.59 & 10.6092 & 10.6167 & -0.00744213 & -0.0192245 \tabularnewline
55 & 10.63 & 10.6296 & 10.6317 & -0.00202546 & 0.000358796 \tabularnewline
56 & 10.63 & 10.6267 & 10.6463 & -0.0195949 & 0.00334491 \tabularnewline
57 & 10.66 & 10.6487 & 10.6613 & -0.0125116 & 0.0112616 \tabularnewline
58 & 10.69 & 10.6566 & 10.6788 & -0.0221644 & 0.0334144 \tabularnewline
59 & 10.72 & 10.7086 & 10.6992 & 0.00943287 & 0.0114005 \tabularnewline
60 & 10.72 & 10.7187 & 10.72 & -0.00126157 & 0.00126157 \tabularnewline
61 & 10.73 & 10.7301 & 10.7392 & -0.00903935 & -0.000127315 \tabularnewline
62 & 10.75 & 10.7842 & 10.7588 & 0.0254051 & -0.0341551 \tabularnewline
63 & 10.78 & 10.8087 & 10.7821 & 0.0266551 & -0.0287384 \tabularnewline
64 & 10.79 & 10.8162 & 10.8071 & 0.00915509 & -0.0262384 \tabularnewline
65 & 10.83 & 10.8342 & 10.8308 & 0.0033912 & -0.00422454 \tabularnewline
66 & 10.83 & 10.8484 & 10.8558 & -0.00744213 & -0.0183912 \tabularnewline
67 & 10.85 & 10.8817 & 10.8838 & -0.00202546 & -0.0317245 \tabularnewline
68 & 10.88 & 10.8958 & 10.9154 & -0.0195949 & -0.0158218 \tabularnewline
69 & 10.97 & 10.9371 & 10.9496 & -0.0125116 & 0.0329282 \tabularnewline
70 & 10.98 & 10.9616 & 10.9837 & -0.0221644 & 0.0184144 \tabularnewline
71 & 11 & 11.0265 & 11.0171 & 0.00943287 & -0.0265162 \tabularnewline
72 & 11.04 & 11.05 & 11.0512 & -0.00126157 & -0.00998843 \tabularnewline
73 & 11.08 & 11.0785 & 11.0875 & -0.00903935 & 0.00153935 \tabularnewline
74 & 11.16 & 11.1492 & 11.1237 & 0.0254051 & 0.0108449 \tabularnewline
75 & 11.19 & 11.1858 & 11.1592 & 0.0266551 & 0.00417824 \tabularnewline
76 & 11.2 & 11.2021 & 11.1929 & 0.00915509 & -0.00207176 \tabularnewline
77 & 11.22 & 11.2288 & 11.2254 & 0.0033912 & -0.00880787 \tabularnewline
78 & 11.26 & 11.2488 & 11.2562 & -0.00744213 & 0.0111921 \tabularnewline
79 & 11.29 & NA & NA & -0.00202546 & NA \tabularnewline
80 & 11.31 & NA & NA & -0.0195949 & NA \tabularnewline
81 & 11.39 & NA & NA & -0.0125116 & NA \tabularnewline
82 & 11.37 & NA & NA & -0.0221644 & NA \tabularnewline
83 & 11.39 & NA & NA & 0.00943287 & NA \tabularnewline
84 & 11.39 & NA & NA & -0.00126157 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231582&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]9.84[/C][C]NA[/C][C]NA[/C][C]-0.00903935[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.87[/C][C]NA[/C][C]NA[/C][C]0.0254051[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9.9[/C][C]NA[/C][C]NA[/C][C]0.0266551[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9.9[/C][C]NA[/C][C]NA[/C][C]0.00915509[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]9.87[/C][C]NA[/C][C]NA[/C][C]0.0033912[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9.87[/C][C]NA[/C][C]NA[/C][C]-0.00744213[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9.88[/C][C]9.82422[/C][C]9.82625[/C][C]-0.00202546[/C][C]0.0557755[/C][/ROW]
[ROW][C]8[/C][C]9.76[/C][C]9.80207[/C][C]9.82167[/C][C]-0.0195949[/C][C]-0.0420718[/C][/ROW]
[ROW][C]9[/C][C]9.76[/C][C]9.80541[/C][C]9.81792[/C][C]-0.0125116[/C][C]-0.0454051[/C][/ROW]
[ROW][C]10[/C][C]9.76[/C][C]9.79159[/C][C]9.81375[/C][C]-0.0221644[/C][C]-0.0315856[/C][/ROW]
[ROW][C]11[/C][C]9.77[/C][C]9.82193[/C][C]9.8125[/C][C]0.00943287[/C][C]-0.0519329[/C][/ROW]
[ROW][C]12[/C][C]9.77[/C][C]9.81332[/C][C]9.81458[/C][C]-0.00126157[/C][C]-0.0433218[/C][/ROW]
[ROW][C]13[/C][C]9.77[/C][C]9.80846[/C][C]9.8175[/C][C]-0.00903935[/C][C]-0.0384606[/C][/ROW]
[ROW][C]14[/C][C]9.83[/C][C]9.85082[/C][C]9.82542[/C][C]0.0254051[/C][C]-0.0208218[/C][/ROW]
[ROW][C]15[/C][C]9.85[/C][C]9.86499[/C][C]9.83833[/C][C]0.0266551[/C][C]-0.0149884[/C][/ROW]
[ROW][C]16[/C][C]9.85[/C][C]9.86082[/C][C]9.85167[/C][C]0.00915509[/C][C]-0.0108218[/C][/ROW]
[ROW][C]17[/C][C]9.89[/C][C]9.86964[/C][C]9.86625[/C][C]0.0033912[/C][C]0.0203588[/C][/ROW]
[ROW][C]18[/C][C]9.9[/C][C]9.87506[/C][C]9.8825[/C][C]-0.00744213[/C][C]0.0249421[/C][/ROW]
[ROW][C]19[/C][C]9.92[/C][C]9.89756[/C][C]9.89958[/C][C]-0.00202546[/C][C]0.0224421[/C][/ROW]
[ROW][C]20[/C][C]9.91[/C][C]9.89832[/C][C]9.91792[/C][C]-0.0195949[/C][C]0.0116782[/C][/ROW]
[ROW][C]21[/C][C]9.92[/C][C]9.92416[/C][C]9.93667[/C][C]-0.0125116[/C][C]-0.00415509[/C][/ROW]
[ROW][C]22[/C][C]9.92[/C][C]9.93492[/C][C]9.95708[/C][C]-0.0221644[/C][C]-0.014919[/C][/ROW]
[ROW][C]23[/C][C]9.96[/C][C]9.98652[/C][C]9.97708[/C][C]0.00943287[/C][C]-0.0265162[/C][/ROW]
[ROW][C]24[/C][C]9.97[/C][C]9.99291[/C][C]9.99417[/C][C]-0.00126157[/C][C]-0.0229051[/C][/ROW]
[ROW][C]25[/C][C]9.98[/C][C]10.001[/C][C]10.01[/C][C]-0.00903935[/C][C]-0.0209606[/C][/ROW]
[ROW][C]26[/C][C]10.06[/C][C]10.0546[/C][C]10.0292[/C][C]0.0254051[/C][C]0.00542824[/C][/ROW]
[ROW][C]27[/C][C]10.07[/C][C]10.0796[/C][C]10.0529[/C][C]0.0266551[/C][C]-0.00957176[/C][/ROW]
[ROW][C]28[/C][C]10.12[/C][C]10.0858[/C][C]10.0767[/C][C]0.00915509[/C][C]0.0341782[/C][/ROW]
[ROW][C]29[/C][C]10.1[/C][C]10.1096[/C][C]10.1062[/C][C]0.0033912[/C][C]-0.0096412[/C][/ROW]
[ROW][C]30[/C][C]10.1[/C][C]10.1342[/C][C]10.1417[/C][C]-0.00744213[/C][C]-0.0342245[/C][/ROW]
[ROW][C]31[/C][C]10.1[/C][C]10.1742[/C][C]10.1763[/C][C]-0.00202546[/C][C]-0.0742245[/C][/ROW]
[ROW][C]32[/C][C]10.19[/C][C]10.19[/C][C]10.2096[/C][C]-0.0195949[/C][C]1.15741e-05[/C][/ROW]
[ROW][C]33[/C][C]10.21[/C][C]10.2308[/C][C]10.2433[/C][C]-0.0125116[/C][C]-0.0208218[/C][/ROW]
[ROW][C]34[/C][C]10.2[/C][C]10.2537[/C][C]10.2758[/C][C]-0.0221644[/C][C]-0.053669[/C][/ROW]
[ROW][C]35[/C][C]10.39[/C][C]10.3165[/C][C]10.3071[/C][C]0.00943287[/C][C]0.0734838[/C][/ROW]
[ROW][C]36[/C][C]10.39[/C][C]10.3383[/C][C]10.3396[/C][C]-0.00126157[/C][C]0.0516782[/C][/ROW]
[ROW][C]37[/C][C]10.39[/C][C]10.3635[/C][C]10.3725[/C][C]-0.00903935[/C][C]0.0265394[/C][/ROW]
[ROW][C]38[/C][C]10.45[/C][C]10.4279[/C][C]10.4025[/C][C]0.0254051[/C][C]0.0220949[/C][/ROW]
[ROW][C]39[/C][C]10.49[/C][C]10.455[/C][C]10.4283[/C][C]0.0266551[/C][C]0.0350116[/C][/ROW]
[ROW][C]40[/C][C]10.48[/C][C]10.4637[/C][C]10.4546[/C][C]0.00915509[/C][C]0.0162616[/C][/ROW]
[ROW][C]41[/C][C]10.49[/C][C]10.478[/C][C]10.4746[/C][C]0.0033912[/C][C]0.0120255[/C][/ROW]
[ROW][C]42[/C][C]10.49[/C][C]10.4796[/C][C]10.4871[/C][C]-0.00744213[/C][C]0.0103588[/C][/ROW]
[ROW][C]43[/C][C]10.5[/C][C]10.498[/C][C]10.5[/C][C]-0.00202546[/C][C]0.00202546[/C][/ROW]
[ROW][C]44[/C][C]10.51[/C][C]10.4925[/C][C]10.5121[/C][C]-0.0195949[/C][C]0.0175116[/C][/ROW]
[ROW][C]45[/C][C]10.51[/C][C]10.5092[/C][C]10.5217[/C][C]-0.0125116[/C][C]0.000844907[/C][/ROW]
[ROW][C]46[/C][C]10.53[/C][C]10.507[/C][C]10.5292[/C][C]-0.0221644[/C][C]0.0229977[/C][/ROW]
[ROW][C]47[/C][C]10.54[/C][C]10.5453[/C][C]10.5358[/C][C]0.00943287[/C][C]-0.0052662[/C][/ROW]
[ROW][C]48[/C][C]10.54[/C][C]10.5421[/C][C]10.5433[/C][C]-0.00126157[/C][C]-0.00207176[/C][/ROW]
[ROW][C]49[/C][C]10.55[/C][C]10.5439[/C][C]10.5529[/C][C]-0.00903935[/C][C]0.00612269[/C][/ROW]
[ROW][C]50[/C][C]10.58[/C][C]10.5887[/C][C]10.5633[/C][C]0.0254051[/C][C]-0.00873843[/C][/ROW]
[ROW][C]51[/C][C]10.59[/C][C]10.6012[/C][C]10.5746[/C][C]0.0266551[/C][C]-0.0112384[/C][/ROW]
[ROW][C]52[/C][C]10.56[/C][C]10.5967[/C][C]10.5875[/C][C]0.00915509[/C][C]-0.0366551[/C][/ROW]
[ROW][C]53[/C][C]10.57[/C][C]10.6051[/C][C]10.6017[/C][C]0.0033912[/C][C]-0.0350579[/C][/ROW]
[ROW][C]54[/C][C]10.59[/C][C]10.6092[/C][C]10.6167[/C][C]-0.00744213[/C][C]-0.0192245[/C][/ROW]
[ROW][C]55[/C][C]10.63[/C][C]10.6296[/C][C]10.6317[/C][C]-0.00202546[/C][C]0.000358796[/C][/ROW]
[ROW][C]56[/C][C]10.63[/C][C]10.6267[/C][C]10.6463[/C][C]-0.0195949[/C][C]0.00334491[/C][/ROW]
[ROW][C]57[/C][C]10.66[/C][C]10.6487[/C][C]10.6613[/C][C]-0.0125116[/C][C]0.0112616[/C][/ROW]
[ROW][C]58[/C][C]10.69[/C][C]10.6566[/C][C]10.6788[/C][C]-0.0221644[/C][C]0.0334144[/C][/ROW]
[ROW][C]59[/C][C]10.72[/C][C]10.7086[/C][C]10.6992[/C][C]0.00943287[/C][C]0.0114005[/C][/ROW]
[ROW][C]60[/C][C]10.72[/C][C]10.7187[/C][C]10.72[/C][C]-0.00126157[/C][C]0.00126157[/C][/ROW]
[ROW][C]61[/C][C]10.73[/C][C]10.7301[/C][C]10.7392[/C][C]-0.00903935[/C][C]-0.000127315[/C][/ROW]
[ROW][C]62[/C][C]10.75[/C][C]10.7842[/C][C]10.7588[/C][C]0.0254051[/C][C]-0.0341551[/C][/ROW]
[ROW][C]63[/C][C]10.78[/C][C]10.8087[/C][C]10.7821[/C][C]0.0266551[/C][C]-0.0287384[/C][/ROW]
[ROW][C]64[/C][C]10.79[/C][C]10.8162[/C][C]10.8071[/C][C]0.00915509[/C][C]-0.0262384[/C][/ROW]
[ROW][C]65[/C][C]10.83[/C][C]10.8342[/C][C]10.8308[/C][C]0.0033912[/C][C]-0.00422454[/C][/ROW]
[ROW][C]66[/C][C]10.83[/C][C]10.8484[/C][C]10.8558[/C][C]-0.00744213[/C][C]-0.0183912[/C][/ROW]
[ROW][C]67[/C][C]10.85[/C][C]10.8817[/C][C]10.8838[/C][C]-0.00202546[/C][C]-0.0317245[/C][/ROW]
[ROW][C]68[/C][C]10.88[/C][C]10.8958[/C][C]10.9154[/C][C]-0.0195949[/C][C]-0.0158218[/C][/ROW]
[ROW][C]69[/C][C]10.97[/C][C]10.9371[/C][C]10.9496[/C][C]-0.0125116[/C][C]0.0329282[/C][/ROW]
[ROW][C]70[/C][C]10.98[/C][C]10.9616[/C][C]10.9837[/C][C]-0.0221644[/C][C]0.0184144[/C][/ROW]
[ROW][C]71[/C][C]11[/C][C]11.0265[/C][C]11.0171[/C][C]0.00943287[/C][C]-0.0265162[/C][/ROW]
[ROW][C]72[/C][C]11.04[/C][C]11.05[/C][C]11.0512[/C][C]-0.00126157[/C][C]-0.00998843[/C][/ROW]
[ROW][C]73[/C][C]11.08[/C][C]11.0785[/C][C]11.0875[/C][C]-0.00903935[/C][C]0.00153935[/C][/ROW]
[ROW][C]74[/C][C]11.16[/C][C]11.1492[/C][C]11.1237[/C][C]0.0254051[/C][C]0.0108449[/C][/ROW]
[ROW][C]75[/C][C]11.19[/C][C]11.1858[/C][C]11.1592[/C][C]0.0266551[/C][C]0.00417824[/C][/ROW]
[ROW][C]76[/C][C]11.2[/C][C]11.2021[/C][C]11.1929[/C][C]0.00915509[/C][C]-0.00207176[/C][/ROW]
[ROW][C]77[/C][C]11.22[/C][C]11.2288[/C][C]11.2254[/C][C]0.0033912[/C][C]-0.00880787[/C][/ROW]
[ROW][C]78[/C][C]11.26[/C][C]11.2488[/C][C]11.2562[/C][C]-0.00744213[/C][C]0.0111921[/C][/ROW]
[ROW][C]79[/C][C]11.29[/C][C]NA[/C][C]NA[/C][C]-0.00202546[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]11.31[/C][C]NA[/C][C]NA[/C][C]-0.0195949[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]11.39[/C][C]NA[/C][C]NA[/C][C]-0.0125116[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]11.37[/C][C]NA[/C][C]NA[/C][C]-0.0221644[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]11.39[/C][C]NA[/C][C]NA[/C][C]0.00943287[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]11.39[/C][C]NA[/C][C]NA[/C][C]-0.00126157[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231582&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231582&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	9.84	NA	NA	-0.00903935	NA
2	9.87	NA	NA	0.0254051	NA
3	9.9	NA	NA	0.0266551	NA
4	9.9	NA	NA	0.00915509	NA
5	9.87	NA	NA	0.0033912	NA
6	9.87	NA	NA	-0.00744213	NA
7	9.88	9.82422	9.82625	-0.00202546	0.0557755
8	9.76	9.80207	9.82167	-0.0195949	-0.0420718
9	9.76	9.80541	9.81792	-0.0125116	-0.0454051
10	9.76	9.79159	9.81375	-0.0221644	-0.0315856
11	9.77	9.82193	9.8125	0.00943287	-0.0519329
12	9.77	9.81332	9.81458	-0.00126157	-0.0433218
13	9.77	9.80846	9.8175	-0.00903935	-0.0384606
14	9.83	9.85082	9.82542	0.0254051	-0.0208218
15	9.85	9.86499	9.83833	0.0266551	-0.0149884
16	9.85	9.86082	9.85167	0.00915509	-0.0108218
17	9.89	9.86964	9.86625	0.0033912	0.0203588
18	9.9	9.87506	9.8825	-0.00744213	0.0249421
19	9.92	9.89756	9.89958	-0.00202546	0.0224421
20	9.91	9.89832	9.91792	-0.0195949	0.0116782
21	9.92	9.92416	9.93667	-0.0125116	-0.00415509
22	9.92	9.93492	9.95708	-0.0221644	-0.014919
23	9.96	9.98652	9.97708	0.00943287	-0.0265162
24	9.97	9.99291	9.99417	-0.00126157	-0.0229051
25	9.98	10.001	10.01	-0.00903935	-0.0209606
26	10.06	10.0546	10.0292	0.0254051	0.00542824
27	10.07	10.0796	10.0529	0.0266551	-0.00957176
28	10.12	10.0858	10.0767	0.00915509	0.0341782
29	10.1	10.1096	10.1062	0.0033912	-0.0096412
30	10.1	10.1342	10.1417	-0.00744213	-0.0342245
31	10.1	10.1742	10.1763	-0.00202546	-0.0742245
32	10.19	10.19	10.2096	-0.0195949	1.15741e-05
33	10.21	10.2308	10.2433	-0.0125116	-0.0208218
34	10.2	10.2537	10.2758	-0.0221644	-0.053669
35	10.39	10.3165	10.3071	0.00943287	0.0734838
36	10.39	10.3383	10.3396	-0.00126157	0.0516782
37	10.39	10.3635	10.3725	-0.00903935	0.0265394
38	10.45	10.4279	10.4025	0.0254051	0.0220949
39	10.49	10.455	10.4283	0.0266551	0.0350116
40	10.48	10.4637	10.4546	0.00915509	0.0162616
41	10.49	10.478	10.4746	0.0033912	0.0120255
42	10.49	10.4796	10.4871	-0.00744213	0.0103588
43	10.5	10.498	10.5	-0.00202546	0.00202546
44	10.51	10.4925	10.5121	-0.0195949	0.0175116
45	10.51	10.5092	10.5217	-0.0125116	0.000844907
46	10.53	10.507	10.5292	-0.0221644	0.0229977
47	10.54	10.5453	10.5358	0.00943287	-0.0052662
48	10.54	10.5421	10.5433	-0.00126157	-0.00207176
49	10.55	10.5439	10.5529	-0.00903935	0.00612269
50	10.58	10.5887	10.5633	0.0254051	-0.00873843
51	10.59	10.6012	10.5746	0.0266551	-0.0112384
52	10.56	10.5967	10.5875	0.00915509	-0.0366551
53	10.57	10.6051	10.6017	0.0033912	-0.0350579
54	10.59	10.6092	10.6167	-0.00744213	-0.0192245
55	10.63	10.6296	10.6317	-0.00202546	0.000358796
56	10.63	10.6267	10.6463	-0.0195949	0.00334491
57	10.66	10.6487	10.6613	-0.0125116	0.0112616
58	10.69	10.6566	10.6788	-0.0221644	0.0334144
59	10.72	10.7086	10.6992	0.00943287	0.0114005
60	10.72	10.7187	10.72	-0.00126157	0.00126157
61	10.73	10.7301	10.7392	-0.00903935	-0.000127315
62	10.75	10.7842	10.7588	0.0254051	-0.0341551
63	10.78	10.8087	10.7821	0.0266551	-0.0287384
64	10.79	10.8162	10.8071	0.00915509	-0.0262384
65	10.83	10.8342	10.8308	0.0033912	-0.00422454
66	10.83	10.8484	10.8558	-0.00744213	-0.0183912
67	10.85	10.8817	10.8838	-0.00202546	-0.0317245
68	10.88	10.8958	10.9154	-0.0195949	-0.0158218
69	10.97	10.9371	10.9496	-0.0125116	0.0329282
70	10.98	10.9616	10.9837	-0.0221644	0.0184144
71	11	11.0265	11.0171	0.00943287	-0.0265162
72	11.04	11.05	11.0512	-0.00126157	-0.00998843
73	11.08	11.0785	11.0875	-0.00903935	0.00153935
74	11.16	11.1492	11.1237	0.0254051	0.0108449
75	11.19	11.1858	11.1592	0.0266551	0.00417824
76	11.2	11.2021	11.1929	0.00915509	-0.00207176
77	11.22	11.2288	11.2254	0.0033912	-0.00880787
78	11.26	11.2488	11.2562	-0.00744213	0.0111921
79	11.29	NA	NA	-0.00202546	NA
80	11.31	NA	NA	-0.0195949	NA
81	11.39	NA	NA	-0.0125116	NA
82	11.37	NA	NA	-0.0221644	NA
83	11.39	NA	NA	0.00943287	NA
84	11.39	NA	NA	-0.00126157	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