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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 12 Jan 2014 07:09:27 -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/2014/Jan/12/t1389528764gdfvt62lf3z7bxb.htm/, Retrieved Mon, 27 May 2024 18:00:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232991, Retrieved Mon, 27 May 2024 18:00:24 +0000

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127

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

-       [Classical Decomposition] [] [2014-01-12 12:09:27] [62a6597007cd6653b71a687b26797f80] [Current]
- RMPD    [Exponential Smoothing] [] [2014-01-12 12:22:23] [7374732ae26351929a6f66a8cd8fe417] 
- R PD      [Exponential Smoothing] [] [2014-01-12 12:28:38] [7374732ae26351929a6f66a8cd8fe417] 

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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	6 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232991&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232991&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232991&T=0

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The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	103.43	NA	NA	0.686146	NA
2	103.49	NA	NA	0.24941	NA
3	103.5	NA	NA	0.250729	NA
4	103.5	NA	NA	0.15059	NA
5	103.5	NA	NA	0.0771181	NA
6	103.5	NA	NA	-0.0228125	NA
7	103.54	103.56	103.676	-0.116007	-0.0198264
8	103.71	103.72	103.833	-0.113368	-0.00954861
9	103.76	103.854	104.02	-0.16691	-0.0935069
10	103.76	103.981	104.222	-0.240382	-0.221285
11	103.76	104.093	104.423	-0.330521	-0.332812
12	103.82	104.201	104.625	-0.423993	-0.381007
13	105.11	105.513	104.827	0.686146	-0.402812
14	105.58	105.271	105.022	0.24941	0.308507
15	105.91	105.46	105.209	0.250729	0.450104
16	105.92	105.545	105.394	0.15059	0.375243
17	105.92	105.658	105.58	0.0771181	0.262465
18	105.92	105.743	105.765	-0.0228125	0.177396
19	105.96	105.816	105.932	-0.116007	0.14434
20	105.98	105.957	106.07	-0.113368	0.0229514
21	105.98	106.02	106.187	-0.16691	-0.0401736
22	105.98	106.053	106.293	-0.240382	-0.0729514
23	106.01	106.076	106.406	-0.330521	-0.0657292
24	106.01	106.101	106.525	-0.423993	-0.0914236
25	106.91	107.329	106.643	0.686146	-0.419062
26	107.11	107.014	106.765	0.24941	0.0955903
27	107.18	107.146	106.895	0.250729	0.0342708
28	107.2	107.177	107.026	0.15059	0.0231597
29	107.35	107.235	107.158	0.0771181	0.114965
30	107.35	107.268	107.29	-0.0228125	0.0823958
31	107.35	107.371	107.487	-0.116007	-0.0210764
32	107.52	107.636	107.749	-0.113368	-0.115799
33	107.56	107.845	108.012	-0.16691	-0.285174
34	107.55	108.033	108.274	-0.240382	-0.483368
35	107.6	108.198	108.528	-0.330521	-0.597813
36	107.6	108.353	108.777	-0.423993	-0.752674
37	110.04	109.711	109.025	0.686146	0.328854
38	110.27	109.516	109.267	0.24941	0.753507
39	110.33	109.753	109.503	0.250729	0.576771
40	110.33	109.895	109.745	0.15059	0.434826
41	110.33	110.069	109.992	0.0771181	0.261215
42	110.33	110.214	110.237	-0.0228125	0.116146
43	110.33	110.264	110.38	-0.116007	0.0660069
44	110.35	110.14	110.254	-0.113368	0.209618
45	110.38	109.792	109.959	-0.16691	0.58816
46	110.54	109.421	109.662	-0.240382	1.11872
47	110.54	109.033	109.363	-0.330521	1.50719
48	110.54	108.641	109.065	-0.423993	1.89899
49	110.54	109.456	108.77	0.686146	1.08427
50	106.74	108.736	108.487	0.24941	-1.99649
51	106.78	108.471	108.22	0.250729	-1.69115
52	106.75	108.105	107.954	0.15059	-1.35476
53	106.75	107.76	107.682	0.0771181	-1.00962
54	106.75	107.388	107.411	-0.0228125	-0.638021
55	106.82	107.071	107.187	-0.116007	-0.251493
56	107.08	107.095	107.208	-0.113368	-0.0145486
57	107.25	107.26	107.427	-0.16691	-0.00975694
58	107.28	107.409	107.65	-0.240382	-0.129201
59	107.28	107.544	107.874	-0.330521	-0.263646
60	107.28	107.675	108.099	-0.423993	-0.395174
61	108.44	109.007	108.321	0.686146	-0.567396
62	109.33	108.779	108.53	0.24941	0.551007
63	109.44	108.971	108.72	0.250729	0.468854
64	109.44	109.054	108.903	0.15059	0.386076
65	109.45	109.162	109.085	0.0771181	0.287882
66	109.45	109.244	109.267	-0.0228125	0.206146
67	109.45	109.346	109.462	-0.116007	0.103924
68	109.45	109.521	109.634	-0.113368	-0.0707986
69	109.46	109.598	109.765	-0.16691	-0.137674
70	109.46	109.65	109.89	-0.240382	-0.190035
71	109.46	109.685	110.016	-0.330521	-0.225313
72	109.46	109.717	110.141	-0.423993	-0.25684
73	110.95	110.952	110.266	0.686146	-0.00197917
74	110.95	110.64	110.391	0.24941	0.309757
75	110.95	110.767	110.516	0.250729	0.183021
76	110.95	110.793	110.642	0.15059	0.157326
77	110.95	110.845	110.768	0.0771181	0.104965
78	110.95	110.872	110.895	-0.0228125	0.0778125
79	110.95	NA	NA	-0.116007	NA
80	110.95	NA	NA	-0.113368	NA
81	110.97	NA	NA	-0.16691	NA
82	110.97	NA	NA	-0.240382	NA
83	110.97	NA	NA	-0.330521	NA
84	111	NA	NA	-0.423993	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.43 & NA & NA & 0.686146 & NA \tabularnewline
2 & 103.49 & NA & NA & 0.24941 & NA \tabularnewline
3 & 103.5 & NA & NA & 0.250729 & NA \tabularnewline
4 & 103.5 & NA & NA & 0.15059 & NA \tabularnewline
5 & 103.5 & NA & NA & 0.0771181 & NA \tabularnewline
6 & 103.5 & NA & NA & -0.0228125 & NA \tabularnewline
7 & 103.54 & 103.56 & 103.676 & -0.116007 & -0.0198264 \tabularnewline
8 & 103.71 & 103.72 & 103.833 & -0.113368 & -0.00954861 \tabularnewline
9 & 103.76 & 103.854 & 104.02 & -0.16691 & -0.0935069 \tabularnewline
10 & 103.76 & 103.981 & 104.222 & -0.240382 & -0.221285 \tabularnewline
11 & 103.76 & 104.093 & 104.423 & -0.330521 & -0.332812 \tabularnewline
12 & 103.82 & 104.201 & 104.625 & -0.423993 & -0.381007 \tabularnewline
13 & 105.11 & 105.513 & 104.827 & 0.686146 & -0.402812 \tabularnewline
14 & 105.58 & 105.271 & 105.022 & 0.24941 & 0.308507 \tabularnewline
15 & 105.91 & 105.46 & 105.209 & 0.250729 & 0.450104 \tabularnewline
16 & 105.92 & 105.545 & 105.394 & 0.15059 & 0.375243 \tabularnewline
17 & 105.92 & 105.658 & 105.58 & 0.0771181 & 0.262465 \tabularnewline
18 & 105.92 & 105.743 & 105.765 & -0.0228125 & 0.177396 \tabularnewline
19 & 105.96 & 105.816 & 105.932 & -0.116007 & 0.14434 \tabularnewline
20 & 105.98 & 105.957 & 106.07 & -0.113368 & 0.0229514 \tabularnewline
21 & 105.98 & 106.02 & 106.187 & -0.16691 & -0.0401736 \tabularnewline
22 & 105.98 & 106.053 & 106.293 & -0.240382 & -0.0729514 \tabularnewline
23 & 106.01 & 106.076 & 106.406 & -0.330521 & -0.0657292 \tabularnewline
24 & 106.01 & 106.101 & 106.525 & -0.423993 & -0.0914236 \tabularnewline
25 & 106.91 & 107.329 & 106.643 & 0.686146 & -0.419062 \tabularnewline
26 & 107.11 & 107.014 & 106.765 & 0.24941 & 0.0955903 \tabularnewline
27 & 107.18 & 107.146 & 106.895 & 0.250729 & 0.0342708 \tabularnewline
28 & 107.2 & 107.177 & 107.026 & 0.15059 & 0.0231597 \tabularnewline
29 & 107.35 & 107.235 & 107.158 & 0.0771181 & 0.114965 \tabularnewline
30 & 107.35 & 107.268 & 107.29 & -0.0228125 & 0.0823958 \tabularnewline
31 & 107.35 & 107.371 & 107.487 & -0.116007 & -0.0210764 \tabularnewline
32 & 107.52 & 107.636 & 107.749 & -0.113368 & -0.115799 \tabularnewline
33 & 107.56 & 107.845 & 108.012 & -0.16691 & -0.285174 \tabularnewline
34 & 107.55 & 108.033 & 108.274 & -0.240382 & -0.483368 \tabularnewline
35 & 107.6 & 108.198 & 108.528 & -0.330521 & -0.597813 \tabularnewline
36 & 107.6 & 108.353 & 108.777 & -0.423993 & -0.752674 \tabularnewline
37 & 110.04 & 109.711 & 109.025 & 0.686146 & 0.328854 \tabularnewline
38 & 110.27 & 109.516 & 109.267 & 0.24941 & 0.753507 \tabularnewline
39 & 110.33 & 109.753 & 109.503 & 0.250729 & 0.576771 \tabularnewline
40 & 110.33 & 109.895 & 109.745 & 0.15059 & 0.434826 \tabularnewline
41 & 110.33 & 110.069 & 109.992 & 0.0771181 & 0.261215 \tabularnewline
42 & 110.33 & 110.214 & 110.237 & -0.0228125 & 0.116146 \tabularnewline
43 & 110.33 & 110.264 & 110.38 & -0.116007 & 0.0660069 \tabularnewline
44 & 110.35 & 110.14 & 110.254 & -0.113368 & 0.209618 \tabularnewline
45 & 110.38 & 109.792 & 109.959 & -0.16691 & 0.58816 \tabularnewline
46 & 110.54 & 109.421 & 109.662 & -0.240382 & 1.11872 \tabularnewline
47 & 110.54 & 109.033 & 109.363 & -0.330521 & 1.50719 \tabularnewline
48 & 110.54 & 108.641 & 109.065 & -0.423993 & 1.89899 \tabularnewline
49 & 110.54 & 109.456 & 108.77 & 0.686146 & 1.08427 \tabularnewline
50 & 106.74 & 108.736 & 108.487 & 0.24941 & -1.99649 \tabularnewline
51 & 106.78 & 108.471 & 108.22 & 0.250729 & -1.69115 \tabularnewline
52 & 106.75 & 108.105 & 107.954 & 0.15059 & -1.35476 \tabularnewline
53 & 106.75 & 107.76 & 107.682 & 0.0771181 & -1.00962 \tabularnewline
54 & 106.75 & 107.388 & 107.411 & -0.0228125 & -0.638021 \tabularnewline
55 & 106.82 & 107.071 & 107.187 & -0.116007 & -0.251493 \tabularnewline
56 & 107.08 & 107.095 & 107.208 & -0.113368 & -0.0145486 \tabularnewline
57 & 107.25 & 107.26 & 107.427 & -0.16691 & -0.00975694 \tabularnewline
58 & 107.28 & 107.409 & 107.65 & -0.240382 & -0.129201 \tabularnewline
59 & 107.28 & 107.544 & 107.874 & -0.330521 & -0.263646 \tabularnewline
60 & 107.28 & 107.675 & 108.099 & -0.423993 & -0.395174 \tabularnewline
61 & 108.44 & 109.007 & 108.321 & 0.686146 & -0.567396 \tabularnewline
62 & 109.33 & 108.779 & 108.53 & 0.24941 & 0.551007 \tabularnewline
63 & 109.44 & 108.971 & 108.72 & 0.250729 & 0.468854 \tabularnewline
64 & 109.44 & 109.054 & 108.903 & 0.15059 & 0.386076 \tabularnewline
65 & 109.45 & 109.162 & 109.085 & 0.0771181 & 0.287882 \tabularnewline
66 & 109.45 & 109.244 & 109.267 & -0.0228125 & 0.206146 \tabularnewline
67 & 109.45 & 109.346 & 109.462 & -0.116007 & 0.103924 \tabularnewline
68 & 109.45 & 109.521 & 109.634 & -0.113368 & -0.0707986 \tabularnewline
69 & 109.46 & 109.598 & 109.765 & -0.16691 & -0.137674 \tabularnewline
70 & 109.46 & 109.65 & 109.89 & -0.240382 & -0.190035 \tabularnewline
71 & 109.46 & 109.685 & 110.016 & -0.330521 & -0.225313 \tabularnewline
72 & 109.46 & 109.717 & 110.141 & -0.423993 & -0.25684 \tabularnewline
73 & 110.95 & 110.952 & 110.266 & 0.686146 & -0.00197917 \tabularnewline
74 & 110.95 & 110.64 & 110.391 & 0.24941 & 0.309757 \tabularnewline
75 & 110.95 & 110.767 & 110.516 & 0.250729 & 0.183021 \tabularnewline
76 & 110.95 & 110.793 & 110.642 & 0.15059 & 0.157326 \tabularnewline
77 & 110.95 & 110.845 & 110.768 & 0.0771181 & 0.104965 \tabularnewline
78 & 110.95 & 110.872 & 110.895 & -0.0228125 & 0.0778125 \tabularnewline
79 & 110.95 & NA & NA & -0.116007 & NA \tabularnewline
80 & 110.95 & NA & NA & -0.113368 & NA \tabularnewline
81 & 110.97 & NA & NA & -0.16691 & NA \tabularnewline
82 & 110.97 & NA & NA & -0.240382 & NA \tabularnewline
83 & 110.97 & NA & NA & -0.330521 & NA \tabularnewline
84 & 111 & NA & NA & -0.423993 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232991&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]103.43[/C][C]NA[/C][C]NA[/C][C]0.686146[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.49[/C][C]NA[/C][C]NA[/C][C]0.24941[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.5[/C][C]NA[/C][C]NA[/C][C]0.250729[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]103.5[/C][C]NA[/C][C]NA[/C][C]0.15059[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]103.5[/C][C]NA[/C][C]NA[/C][C]0.0771181[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]103.5[/C][C]NA[/C][C]NA[/C][C]-0.0228125[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]103.54[/C][C]103.56[/C][C]103.676[/C][C]-0.116007[/C][C]-0.0198264[/C][/ROW]
[ROW][C]8[/C][C]103.71[/C][C]103.72[/C][C]103.833[/C][C]-0.113368[/C][C]-0.00954861[/C][/ROW]
[ROW][C]9[/C][C]103.76[/C][C]103.854[/C][C]104.02[/C][C]-0.16691[/C][C]-0.0935069[/C][/ROW]
[ROW][C]10[/C][C]103.76[/C][C]103.981[/C][C]104.222[/C][C]-0.240382[/C][C]-0.221285[/C][/ROW]
[ROW][C]11[/C][C]103.76[/C][C]104.093[/C][C]104.423[/C][C]-0.330521[/C][C]-0.332812[/C][/ROW]
[ROW][C]12[/C][C]103.82[/C][C]104.201[/C][C]104.625[/C][C]-0.423993[/C][C]-0.381007[/C][/ROW]
[ROW][C]13[/C][C]105.11[/C][C]105.513[/C][C]104.827[/C][C]0.686146[/C][C]-0.402812[/C][/ROW]
[ROW][C]14[/C][C]105.58[/C][C]105.271[/C][C]105.022[/C][C]0.24941[/C][C]0.308507[/C][/ROW]
[ROW][C]15[/C][C]105.91[/C][C]105.46[/C][C]105.209[/C][C]0.250729[/C][C]0.450104[/C][/ROW]
[ROW][C]16[/C][C]105.92[/C][C]105.545[/C][C]105.394[/C][C]0.15059[/C][C]0.375243[/C][/ROW]
[ROW][C]17[/C][C]105.92[/C][C]105.658[/C][C]105.58[/C][C]0.0771181[/C][C]0.262465[/C][/ROW]
[ROW][C]18[/C][C]105.92[/C][C]105.743[/C][C]105.765[/C][C]-0.0228125[/C][C]0.177396[/C][/ROW]
[ROW][C]19[/C][C]105.96[/C][C]105.816[/C][C]105.932[/C][C]-0.116007[/C][C]0.14434[/C][/ROW]
[ROW][C]20[/C][C]105.98[/C][C]105.957[/C][C]106.07[/C][C]-0.113368[/C][C]0.0229514[/C][/ROW]
[ROW][C]21[/C][C]105.98[/C][C]106.02[/C][C]106.187[/C][C]-0.16691[/C][C]-0.0401736[/C][/ROW]
[ROW][C]22[/C][C]105.98[/C][C]106.053[/C][C]106.293[/C][C]-0.240382[/C][C]-0.0729514[/C][/ROW]
[ROW][C]23[/C][C]106.01[/C][C]106.076[/C][C]106.406[/C][C]-0.330521[/C][C]-0.0657292[/C][/ROW]
[ROW][C]24[/C][C]106.01[/C][C]106.101[/C][C]106.525[/C][C]-0.423993[/C][C]-0.0914236[/C][/ROW]
[ROW][C]25[/C][C]106.91[/C][C]107.329[/C][C]106.643[/C][C]0.686146[/C][C]-0.419062[/C][/ROW]
[ROW][C]26[/C][C]107.11[/C][C]107.014[/C][C]106.765[/C][C]0.24941[/C][C]0.0955903[/C][/ROW]
[ROW][C]27[/C][C]107.18[/C][C]107.146[/C][C]106.895[/C][C]0.250729[/C][C]0.0342708[/C][/ROW]
[ROW][C]28[/C][C]107.2[/C][C]107.177[/C][C]107.026[/C][C]0.15059[/C][C]0.0231597[/C][/ROW]
[ROW][C]29[/C][C]107.35[/C][C]107.235[/C][C]107.158[/C][C]0.0771181[/C][C]0.114965[/C][/ROW]
[ROW][C]30[/C][C]107.35[/C][C]107.268[/C][C]107.29[/C][C]-0.0228125[/C][C]0.0823958[/C][/ROW]
[ROW][C]31[/C][C]107.35[/C][C]107.371[/C][C]107.487[/C][C]-0.116007[/C][C]-0.0210764[/C][/ROW]
[ROW][C]32[/C][C]107.52[/C][C]107.636[/C][C]107.749[/C][C]-0.113368[/C][C]-0.115799[/C][/ROW]
[ROW][C]33[/C][C]107.56[/C][C]107.845[/C][C]108.012[/C][C]-0.16691[/C][C]-0.285174[/C][/ROW]
[ROW][C]34[/C][C]107.55[/C][C]108.033[/C][C]108.274[/C][C]-0.240382[/C][C]-0.483368[/C][/ROW]
[ROW][C]35[/C][C]107.6[/C][C]108.198[/C][C]108.528[/C][C]-0.330521[/C][C]-0.597813[/C][/ROW]
[ROW][C]36[/C][C]107.6[/C][C]108.353[/C][C]108.777[/C][C]-0.423993[/C][C]-0.752674[/C][/ROW]
[ROW][C]37[/C][C]110.04[/C][C]109.711[/C][C]109.025[/C][C]0.686146[/C][C]0.328854[/C][/ROW]
[ROW][C]38[/C][C]110.27[/C][C]109.516[/C][C]109.267[/C][C]0.24941[/C][C]0.753507[/C][/ROW]
[ROW][C]39[/C][C]110.33[/C][C]109.753[/C][C]109.503[/C][C]0.250729[/C][C]0.576771[/C][/ROW]
[ROW][C]40[/C][C]110.33[/C][C]109.895[/C][C]109.745[/C][C]0.15059[/C][C]0.434826[/C][/ROW]
[ROW][C]41[/C][C]110.33[/C][C]110.069[/C][C]109.992[/C][C]0.0771181[/C][C]0.261215[/C][/ROW]
[ROW][C]42[/C][C]110.33[/C][C]110.214[/C][C]110.237[/C][C]-0.0228125[/C][C]0.116146[/C][/ROW]
[ROW][C]43[/C][C]110.33[/C][C]110.264[/C][C]110.38[/C][C]-0.116007[/C][C]0.0660069[/C][/ROW]
[ROW][C]44[/C][C]110.35[/C][C]110.14[/C][C]110.254[/C][C]-0.113368[/C][C]0.209618[/C][/ROW]
[ROW][C]45[/C][C]110.38[/C][C]109.792[/C][C]109.959[/C][C]-0.16691[/C][C]0.58816[/C][/ROW]
[ROW][C]46[/C][C]110.54[/C][C]109.421[/C][C]109.662[/C][C]-0.240382[/C][C]1.11872[/C][/ROW]
[ROW][C]47[/C][C]110.54[/C][C]109.033[/C][C]109.363[/C][C]-0.330521[/C][C]1.50719[/C][/ROW]
[ROW][C]48[/C][C]110.54[/C][C]108.641[/C][C]109.065[/C][C]-0.423993[/C][C]1.89899[/C][/ROW]
[ROW][C]49[/C][C]110.54[/C][C]109.456[/C][C]108.77[/C][C]0.686146[/C][C]1.08427[/C][/ROW]
[ROW][C]50[/C][C]106.74[/C][C]108.736[/C][C]108.487[/C][C]0.24941[/C][C]-1.99649[/C][/ROW]
[ROW][C]51[/C][C]106.78[/C][C]108.471[/C][C]108.22[/C][C]0.250729[/C][C]-1.69115[/C][/ROW]
[ROW][C]52[/C][C]106.75[/C][C]108.105[/C][C]107.954[/C][C]0.15059[/C][C]-1.35476[/C][/ROW]
[ROW][C]53[/C][C]106.75[/C][C]107.76[/C][C]107.682[/C][C]0.0771181[/C][C]-1.00962[/C][/ROW]
[ROW][C]54[/C][C]106.75[/C][C]107.388[/C][C]107.411[/C][C]-0.0228125[/C][C]-0.638021[/C][/ROW]
[ROW][C]55[/C][C]106.82[/C][C]107.071[/C][C]107.187[/C][C]-0.116007[/C][C]-0.251493[/C][/ROW]
[ROW][C]56[/C][C]107.08[/C][C]107.095[/C][C]107.208[/C][C]-0.113368[/C][C]-0.0145486[/C][/ROW]
[ROW][C]57[/C][C]107.25[/C][C]107.26[/C][C]107.427[/C][C]-0.16691[/C][C]-0.00975694[/C][/ROW]
[ROW][C]58[/C][C]107.28[/C][C]107.409[/C][C]107.65[/C][C]-0.240382[/C][C]-0.129201[/C][/ROW]
[ROW][C]59[/C][C]107.28[/C][C]107.544[/C][C]107.874[/C][C]-0.330521[/C][C]-0.263646[/C][/ROW]
[ROW][C]60[/C][C]107.28[/C][C]107.675[/C][C]108.099[/C][C]-0.423993[/C][C]-0.395174[/C][/ROW]
[ROW][C]61[/C][C]108.44[/C][C]109.007[/C][C]108.321[/C][C]0.686146[/C][C]-0.567396[/C][/ROW]
[ROW][C]62[/C][C]109.33[/C][C]108.779[/C][C]108.53[/C][C]0.24941[/C][C]0.551007[/C][/ROW]
[ROW][C]63[/C][C]109.44[/C][C]108.971[/C][C]108.72[/C][C]0.250729[/C][C]0.468854[/C][/ROW]
[ROW][C]64[/C][C]109.44[/C][C]109.054[/C][C]108.903[/C][C]0.15059[/C][C]0.386076[/C][/ROW]
[ROW][C]65[/C][C]109.45[/C][C]109.162[/C][C]109.085[/C][C]0.0771181[/C][C]0.287882[/C][/ROW]
[ROW][C]66[/C][C]109.45[/C][C]109.244[/C][C]109.267[/C][C]-0.0228125[/C][C]0.206146[/C][/ROW]
[ROW][C]67[/C][C]109.45[/C][C]109.346[/C][C]109.462[/C][C]-0.116007[/C][C]0.103924[/C][/ROW]
[ROW][C]68[/C][C]109.45[/C][C]109.521[/C][C]109.634[/C][C]-0.113368[/C][C]-0.0707986[/C][/ROW]
[ROW][C]69[/C][C]109.46[/C][C]109.598[/C][C]109.765[/C][C]-0.16691[/C][C]-0.137674[/C][/ROW]
[ROW][C]70[/C][C]109.46[/C][C]109.65[/C][C]109.89[/C][C]-0.240382[/C][C]-0.190035[/C][/ROW]
[ROW][C]71[/C][C]109.46[/C][C]109.685[/C][C]110.016[/C][C]-0.330521[/C][C]-0.225313[/C][/ROW]
[ROW][C]72[/C][C]109.46[/C][C]109.717[/C][C]110.141[/C][C]-0.423993[/C][C]-0.25684[/C][/ROW]
[ROW][C]73[/C][C]110.95[/C][C]110.952[/C][C]110.266[/C][C]0.686146[/C][C]-0.00197917[/C][/ROW]
[ROW][C]74[/C][C]110.95[/C][C]110.64[/C][C]110.391[/C][C]0.24941[/C][C]0.309757[/C][/ROW]
[ROW][C]75[/C][C]110.95[/C][C]110.767[/C][C]110.516[/C][C]0.250729[/C][C]0.183021[/C][/ROW]
[ROW][C]76[/C][C]110.95[/C][C]110.793[/C][C]110.642[/C][C]0.15059[/C][C]0.157326[/C][/ROW]
[ROW][C]77[/C][C]110.95[/C][C]110.845[/C][C]110.768[/C][C]0.0771181[/C][C]0.104965[/C][/ROW]
[ROW][C]78[/C][C]110.95[/C][C]110.872[/C][C]110.895[/C][C]-0.0228125[/C][C]0.0778125[/C][/ROW]
[ROW][C]79[/C][C]110.95[/C][C]NA[/C][C]NA[/C][C]-0.116007[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]110.95[/C][C]NA[/C][C]NA[/C][C]-0.113368[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]110.97[/C][C]NA[/C][C]NA[/C][C]-0.16691[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]110.97[/C][C]NA[/C][C]NA[/C][C]-0.240382[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]110.97[/C][C]NA[/C][C]NA[/C][C]-0.330521[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]111[/C][C]NA[/C][C]NA[/C][C]-0.423993[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232991&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232991&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	103.43	NA	NA	0.686146	NA
2	103.49	NA	NA	0.24941	NA
3	103.5	NA	NA	0.250729	NA
4	103.5	NA	NA	0.15059	NA
5	103.5	NA	NA	0.0771181	NA
6	103.5	NA	NA	-0.0228125	NA
7	103.54	103.56	103.676	-0.116007	-0.0198264
8	103.71	103.72	103.833	-0.113368	-0.00954861
9	103.76	103.854	104.02	-0.16691	-0.0935069
10	103.76	103.981	104.222	-0.240382	-0.221285
11	103.76	104.093	104.423	-0.330521	-0.332812
12	103.82	104.201	104.625	-0.423993	-0.381007
13	105.11	105.513	104.827	0.686146	-0.402812
14	105.58	105.271	105.022	0.24941	0.308507
15	105.91	105.46	105.209	0.250729	0.450104
16	105.92	105.545	105.394	0.15059	0.375243
17	105.92	105.658	105.58	0.0771181	0.262465
18	105.92	105.743	105.765	-0.0228125	0.177396
19	105.96	105.816	105.932	-0.116007	0.14434
20	105.98	105.957	106.07	-0.113368	0.0229514
21	105.98	106.02	106.187	-0.16691	-0.0401736
22	105.98	106.053	106.293	-0.240382	-0.0729514
23	106.01	106.076	106.406	-0.330521	-0.0657292
24	106.01	106.101	106.525	-0.423993	-0.0914236
25	106.91	107.329	106.643	0.686146	-0.419062
26	107.11	107.014	106.765	0.24941	0.0955903
27	107.18	107.146	106.895	0.250729	0.0342708
28	107.2	107.177	107.026	0.15059	0.0231597
29	107.35	107.235	107.158	0.0771181	0.114965
30	107.35	107.268	107.29	-0.0228125	0.0823958
31	107.35	107.371	107.487	-0.116007	-0.0210764
32	107.52	107.636	107.749	-0.113368	-0.115799
33	107.56	107.845	108.012	-0.16691	-0.285174
34	107.55	108.033	108.274	-0.240382	-0.483368
35	107.6	108.198	108.528	-0.330521	-0.597813
36	107.6	108.353	108.777	-0.423993	-0.752674
37	110.04	109.711	109.025	0.686146	0.328854
38	110.27	109.516	109.267	0.24941	0.753507
39	110.33	109.753	109.503	0.250729	0.576771
40	110.33	109.895	109.745	0.15059	0.434826
41	110.33	110.069	109.992	0.0771181	0.261215
42	110.33	110.214	110.237	-0.0228125	0.116146
43	110.33	110.264	110.38	-0.116007	0.0660069
44	110.35	110.14	110.254	-0.113368	0.209618
45	110.38	109.792	109.959	-0.16691	0.58816
46	110.54	109.421	109.662	-0.240382	1.11872
47	110.54	109.033	109.363	-0.330521	1.50719
48	110.54	108.641	109.065	-0.423993	1.89899
49	110.54	109.456	108.77	0.686146	1.08427
50	106.74	108.736	108.487	0.24941	-1.99649
51	106.78	108.471	108.22	0.250729	-1.69115
52	106.75	108.105	107.954	0.15059	-1.35476
53	106.75	107.76	107.682	0.0771181	-1.00962
54	106.75	107.388	107.411	-0.0228125	-0.638021
55	106.82	107.071	107.187	-0.116007	-0.251493
56	107.08	107.095	107.208	-0.113368	-0.0145486
57	107.25	107.26	107.427	-0.16691	-0.00975694
58	107.28	107.409	107.65	-0.240382	-0.129201
59	107.28	107.544	107.874	-0.330521	-0.263646
60	107.28	107.675	108.099	-0.423993	-0.395174
61	108.44	109.007	108.321	0.686146	-0.567396
62	109.33	108.779	108.53	0.24941	0.551007
63	109.44	108.971	108.72	0.250729	0.468854
64	109.44	109.054	108.903	0.15059	0.386076
65	109.45	109.162	109.085	0.0771181	0.287882
66	109.45	109.244	109.267	-0.0228125	0.206146
67	109.45	109.346	109.462	-0.116007	0.103924
68	109.45	109.521	109.634	-0.113368	-0.0707986
69	109.46	109.598	109.765	-0.16691	-0.137674
70	109.46	109.65	109.89	-0.240382	-0.190035
71	109.46	109.685	110.016	-0.330521	-0.225313
72	109.46	109.717	110.141	-0.423993	-0.25684
73	110.95	110.952	110.266	0.686146	-0.00197917
74	110.95	110.64	110.391	0.24941	0.309757
75	110.95	110.767	110.516	0.250729	0.183021
76	110.95	110.793	110.642	0.15059	0.157326
77	110.95	110.845	110.768	0.0771181	0.104965
78	110.95	110.872	110.895	-0.0228125	0.0778125
79	110.95	NA	NA	-0.116007	NA
80	110.95	NA	NA	-0.113368	NA
81	110.97	NA	NA	-0.16691	NA
82	110.97	NA	NA	-0.240382	NA
83	110.97	NA	NA	-0.330521	NA
84	111	NA	NA	-0.423993	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