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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 27 Nov 2015 09:43:22 +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/27/t1448617445v5jy02bstpxe0ph.htm/, Retrieved Wed, 15 May 2024 16:40:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284279, Retrieved Wed, 15 May 2024 16:40:50 +0000

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-       [Classical Decomposition] [] [2015-11-27 09:43:22] [f03ff3651993e75eb8cd64bbe7aa965c] [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=284279&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=284279&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284279&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	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	93.58	NA	NA	-5.4381	NA
2	95.79	NA	NA	-2.6981	NA
3	94.77	NA	NA	-2.05876	NA
4	94.2	NA	NA	1.16415	NA
5	96.23	NA	NA	4.16932	NA
6	92.3	NA	NA	6.3929	NA
7	88.86	91.5545	91.1075	0.446986	-2.69449
8	86.44	89.2625	90.6142	-1.35168	-2.82249
9	86.21	89.9885	90.2296	-0.241097	-3.77849
10	88.57	91.6272	89.8692	1.75807	-3.05724
11	90.69	90.3218	89.9454	0.376403	0.368181
12	89	88.0891	90.6092	-2.5201	0.910931
13	86.88	85.7207	91.1588	-5.4381	1.15935
14	90.65	88.9398	91.6379	-2.6981	1.71018
15	90.68	90.2592	92.3179	-2.05876	0.420847
16	89.64	94.1837	93.0196	1.16415	-4.54374
17	102.62	97.6768	93.5075	4.16932	4.94318
18	101.84	100.067	93.6737	6.3929	1.77335
19	92.51	94.0653	93.6183	0.446986	-1.55532
20	94.29	92.1183	93.47	-1.35168	2.17168
21	94.68	93.1264	93.3675	-0.241097	1.5536
22	96.94	95.2381	93.48	1.75807	1.70193
23	94.03	93.5727	93.1963	0.376403	0.457347
24	89.65	90.1003	92.6204	-2.5201	-0.450319
25	84.9	87.2111	92.6492	-5.4381	-2.31107
26	89.07	89.9357	92.6338	-2.6981	-0.865653
27	89.8	90.1929	92.2517	-2.05876	-0.392903
28	93.22	93.0204	91.8562	1.16415	0.199597
29	92.23	95.7935	91.6242	4.16932	-3.56349
30	98.41	98.0337	91.6408	6.3929	0.376264
31	96.63	92.1578	91.7108	0.446986	4.47218
32	89.8	90.3479	91.6996	-1.35168	-0.547903
33	90	91.381	91.6221	-0.241097	-1.38099
34	92.13	93.2089	91.4508	1.75807	-1.0789
35	93.27	91.7218	91.3454	0.376403	1.54818
36	90.81	88.7516	91.2717	-2.5201	2.05843
37	85.42	85.6644	91.1025	-5.4381	-0.244403
38	88.28	88.5157	91.2137	-2.6981	-0.235653
39	88.73	89.6296	91.6883	-2.05876	-0.899569
40	90.18	93.5204	92.3562	1.16415	-3.3404
41	92.74	97.131	92.9617	4.16932	-4.39099
42	96.13	99.7771	93.3842	6.3929	-3.64707
43	94.85	94.3807	93.9338	0.446986	0.469264
44	94.25	93.3479	94.6996	-1.35168	0.902097
45	96.94	95.2397	95.4808	-0.241097	1.70026
46	101.22	98.0022	96.2442	1.75807	3.21776
47	98.71	97.6456	97.2692	0.376403	1.06443
48	95.51	95.8949	98.415	-2.5201	-0.384903
49	93.91	93.7169	99.155	-5.4381	0.193097
50	98.17	96.8911	99.5892	-2.6981	1.27893
51	97.59	97.9392	99.9979	-2.05876	-0.349153
52	99.64	101.363	100.199	1.16415	-1.7229
53	107.88	104.302	100.132	4.16932	3.57818
54	108.49	106.426	100.033	6.3929	2.06418
55	100.25	100.474	100.027	0.446986	-0.223653
56	99.27	98.5054	99.8571	-1.35168	0.764597
57	101.73	99.3564	99.5975	-0.241097	2.3736
58	101.25	101.566	99.8075	1.75807	-0.315569
59	97.09	100.06	99.6838	0.376403	-2.97015
60	94.74	96.4062	98.9262	-2.5201	-1.66615
61	94.53	92.859	98.2971	-5.4381	1.67101
62	93.48	94.8998	97.5979	-2.6981	-1.41982
63	96.05	94.3612	96.42	-2.05876	1.68876
64	106.22	96.3446	95.1804	1.16415	9.87543
65	98.33	98.4289	94.2596	4.16932	-0.0989028
66	99.86	99.9587	93.5658	6.3929	-0.0987361
67	93.78	NA	NA	0.446986	NA
68	88.96	NA	NA	-1.35168	NA
69	83.77	NA	NA	-0.241097	NA
70	89.46	NA	NA	1.75807	NA
71	86.78	NA	NA	0.376403	NA
72	88.4	NA	NA	-2.5201	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 93.58 & NA & NA & -5.4381 & NA \tabularnewline
2 & 95.79 & NA & NA & -2.6981 & NA \tabularnewline
3 & 94.77 & NA & NA & -2.05876 & NA \tabularnewline
4 & 94.2 & NA & NA & 1.16415 & NA \tabularnewline
5 & 96.23 & NA & NA & 4.16932 & NA \tabularnewline
6 & 92.3 & NA & NA & 6.3929 & NA \tabularnewline
7 & 88.86 & 91.5545 & 91.1075 & 0.446986 & -2.69449 \tabularnewline
8 & 86.44 & 89.2625 & 90.6142 & -1.35168 & -2.82249 \tabularnewline
9 & 86.21 & 89.9885 & 90.2296 & -0.241097 & -3.77849 \tabularnewline
10 & 88.57 & 91.6272 & 89.8692 & 1.75807 & -3.05724 \tabularnewline
11 & 90.69 & 90.3218 & 89.9454 & 0.376403 & 0.368181 \tabularnewline
12 & 89 & 88.0891 & 90.6092 & -2.5201 & 0.910931 \tabularnewline
13 & 86.88 & 85.7207 & 91.1588 & -5.4381 & 1.15935 \tabularnewline
14 & 90.65 & 88.9398 & 91.6379 & -2.6981 & 1.71018 \tabularnewline
15 & 90.68 & 90.2592 & 92.3179 & -2.05876 & 0.420847 \tabularnewline
16 & 89.64 & 94.1837 & 93.0196 & 1.16415 & -4.54374 \tabularnewline
17 & 102.62 & 97.6768 & 93.5075 & 4.16932 & 4.94318 \tabularnewline
18 & 101.84 & 100.067 & 93.6737 & 6.3929 & 1.77335 \tabularnewline
19 & 92.51 & 94.0653 & 93.6183 & 0.446986 & -1.55532 \tabularnewline
20 & 94.29 & 92.1183 & 93.47 & -1.35168 & 2.17168 \tabularnewline
21 & 94.68 & 93.1264 & 93.3675 & -0.241097 & 1.5536 \tabularnewline
22 & 96.94 & 95.2381 & 93.48 & 1.75807 & 1.70193 \tabularnewline
23 & 94.03 & 93.5727 & 93.1963 & 0.376403 & 0.457347 \tabularnewline
24 & 89.65 & 90.1003 & 92.6204 & -2.5201 & -0.450319 \tabularnewline
25 & 84.9 & 87.2111 & 92.6492 & -5.4381 & -2.31107 \tabularnewline
26 & 89.07 & 89.9357 & 92.6338 & -2.6981 & -0.865653 \tabularnewline
27 & 89.8 & 90.1929 & 92.2517 & -2.05876 & -0.392903 \tabularnewline
28 & 93.22 & 93.0204 & 91.8562 & 1.16415 & 0.199597 \tabularnewline
29 & 92.23 & 95.7935 & 91.6242 & 4.16932 & -3.56349 \tabularnewline
30 & 98.41 & 98.0337 & 91.6408 & 6.3929 & 0.376264 \tabularnewline
31 & 96.63 & 92.1578 & 91.7108 & 0.446986 & 4.47218 \tabularnewline
32 & 89.8 & 90.3479 & 91.6996 & -1.35168 & -0.547903 \tabularnewline
33 & 90 & 91.381 & 91.6221 & -0.241097 & -1.38099 \tabularnewline
34 & 92.13 & 93.2089 & 91.4508 & 1.75807 & -1.0789 \tabularnewline
35 & 93.27 & 91.7218 & 91.3454 & 0.376403 & 1.54818 \tabularnewline
36 & 90.81 & 88.7516 & 91.2717 & -2.5201 & 2.05843 \tabularnewline
37 & 85.42 & 85.6644 & 91.1025 & -5.4381 & -0.244403 \tabularnewline
38 & 88.28 & 88.5157 & 91.2137 & -2.6981 & -0.235653 \tabularnewline
39 & 88.73 & 89.6296 & 91.6883 & -2.05876 & -0.899569 \tabularnewline
40 & 90.18 & 93.5204 & 92.3562 & 1.16415 & -3.3404 \tabularnewline
41 & 92.74 & 97.131 & 92.9617 & 4.16932 & -4.39099 \tabularnewline
42 & 96.13 & 99.7771 & 93.3842 & 6.3929 & -3.64707 \tabularnewline
43 & 94.85 & 94.3807 & 93.9338 & 0.446986 & 0.469264 \tabularnewline
44 & 94.25 & 93.3479 & 94.6996 & -1.35168 & 0.902097 \tabularnewline
45 & 96.94 & 95.2397 & 95.4808 & -0.241097 & 1.70026 \tabularnewline
46 & 101.22 & 98.0022 & 96.2442 & 1.75807 & 3.21776 \tabularnewline
47 & 98.71 & 97.6456 & 97.2692 & 0.376403 & 1.06443 \tabularnewline
48 & 95.51 & 95.8949 & 98.415 & -2.5201 & -0.384903 \tabularnewline
49 & 93.91 & 93.7169 & 99.155 & -5.4381 & 0.193097 \tabularnewline
50 & 98.17 & 96.8911 & 99.5892 & -2.6981 & 1.27893 \tabularnewline
51 & 97.59 & 97.9392 & 99.9979 & -2.05876 & -0.349153 \tabularnewline
52 & 99.64 & 101.363 & 100.199 & 1.16415 & -1.7229 \tabularnewline
53 & 107.88 & 104.302 & 100.132 & 4.16932 & 3.57818 \tabularnewline
54 & 108.49 & 106.426 & 100.033 & 6.3929 & 2.06418 \tabularnewline
55 & 100.25 & 100.474 & 100.027 & 0.446986 & -0.223653 \tabularnewline
56 & 99.27 & 98.5054 & 99.8571 & -1.35168 & 0.764597 \tabularnewline
57 & 101.73 & 99.3564 & 99.5975 & -0.241097 & 2.3736 \tabularnewline
58 & 101.25 & 101.566 & 99.8075 & 1.75807 & -0.315569 \tabularnewline
59 & 97.09 & 100.06 & 99.6838 & 0.376403 & -2.97015 \tabularnewline
60 & 94.74 & 96.4062 & 98.9262 & -2.5201 & -1.66615 \tabularnewline
61 & 94.53 & 92.859 & 98.2971 & -5.4381 & 1.67101 \tabularnewline
62 & 93.48 & 94.8998 & 97.5979 & -2.6981 & -1.41982 \tabularnewline
63 & 96.05 & 94.3612 & 96.42 & -2.05876 & 1.68876 \tabularnewline
64 & 106.22 & 96.3446 & 95.1804 & 1.16415 & 9.87543 \tabularnewline
65 & 98.33 & 98.4289 & 94.2596 & 4.16932 & -0.0989028 \tabularnewline
66 & 99.86 & 99.9587 & 93.5658 & 6.3929 & -0.0987361 \tabularnewline
67 & 93.78 & NA & NA & 0.446986 & NA \tabularnewline
68 & 88.96 & NA & NA & -1.35168 & NA \tabularnewline
69 & 83.77 & NA & NA & -0.241097 & NA \tabularnewline
70 & 89.46 & NA & NA & 1.75807 & NA \tabularnewline
71 & 86.78 & NA & NA & 0.376403 & NA \tabularnewline
72 & 88.4 & NA & NA & -2.5201 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284279&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]93.58[/C][C]NA[/C][C]NA[/C][C]-5.4381[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]95.79[/C][C]NA[/C][C]NA[/C][C]-2.6981[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]94.77[/C][C]NA[/C][C]NA[/C][C]-2.05876[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]94.2[/C][C]NA[/C][C]NA[/C][C]1.16415[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]96.23[/C][C]NA[/C][C]NA[/C][C]4.16932[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.3[/C][C]NA[/C][C]NA[/C][C]6.3929[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]88.86[/C][C]91.5545[/C][C]91.1075[/C][C]0.446986[/C][C]-2.69449[/C][/ROW]
[ROW][C]8[/C][C]86.44[/C][C]89.2625[/C][C]90.6142[/C][C]-1.35168[/C][C]-2.82249[/C][/ROW]
[ROW][C]9[/C][C]86.21[/C][C]89.9885[/C][C]90.2296[/C][C]-0.241097[/C][C]-3.77849[/C][/ROW]
[ROW][C]10[/C][C]88.57[/C][C]91.6272[/C][C]89.8692[/C][C]1.75807[/C][C]-3.05724[/C][/ROW]
[ROW][C]11[/C][C]90.69[/C][C]90.3218[/C][C]89.9454[/C][C]0.376403[/C][C]0.368181[/C][/ROW]
[ROW][C]12[/C][C]89[/C][C]88.0891[/C][C]90.6092[/C][C]-2.5201[/C][C]0.910931[/C][/ROW]
[ROW][C]13[/C][C]86.88[/C][C]85.7207[/C][C]91.1588[/C][C]-5.4381[/C][C]1.15935[/C][/ROW]
[ROW][C]14[/C][C]90.65[/C][C]88.9398[/C][C]91.6379[/C][C]-2.6981[/C][C]1.71018[/C][/ROW]
[ROW][C]15[/C][C]90.68[/C][C]90.2592[/C][C]92.3179[/C][C]-2.05876[/C][C]0.420847[/C][/ROW]
[ROW][C]16[/C][C]89.64[/C][C]94.1837[/C][C]93.0196[/C][C]1.16415[/C][C]-4.54374[/C][/ROW]
[ROW][C]17[/C][C]102.62[/C][C]97.6768[/C][C]93.5075[/C][C]4.16932[/C][C]4.94318[/C][/ROW]
[ROW][C]18[/C][C]101.84[/C][C]100.067[/C][C]93.6737[/C][C]6.3929[/C][C]1.77335[/C][/ROW]
[ROW][C]19[/C][C]92.51[/C][C]94.0653[/C][C]93.6183[/C][C]0.446986[/C][C]-1.55532[/C][/ROW]
[ROW][C]20[/C][C]94.29[/C][C]92.1183[/C][C]93.47[/C][C]-1.35168[/C][C]2.17168[/C][/ROW]
[ROW][C]21[/C][C]94.68[/C][C]93.1264[/C][C]93.3675[/C][C]-0.241097[/C][C]1.5536[/C][/ROW]
[ROW][C]22[/C][C]96.94[/C][C]95.2381[/C][C]93.48[/C][C]1.75807[/C][C]1.70193[/C][/ROW]
[ROW][C]23[/C][C]94.03[/C][C]93.5727[/C][C]93.1963[/C][C]0.376403[/C][C]0.457347[/C][/ROW]
[ROW][C]24[/C][C]89.65[/C][C]90.1003[/C][C]92.6204[/C][C]-2.5201[/C][C]-0.450319[/C][/ROW]
[ROW][C]25[/C][C]84.9[/C][C]87.2111[/C][C]92.6492[/C][C]-5.4381[/C][C]-2.31107[/C][/ROW]
[ROW][C]26[/C][C]89.07[/C][C]89.9357[/C][C]92.6338[/C][C]-2.6981[/C][C]-0.865653[/C][/ROW]
[ROW][C]27[/C][C]89.8[/C][C]90.1929[/C][C]92.2517[/C][C]-2.05876[/C][C]-0.392903[/C][/ROW]
[ROW][C]28[/C][C]93.22[/C][C]93.0204[/C][C]91.8562[/C][C]1.16415[/C][C]0.199597[/C][/ROW]
[ROW][C]29[/C][C]92.23[/C][C]95.7935[/C][C]91.6242[/C][C]4.16932[/C][C]-3.56349[/C][/ROW]
[ROW][C]30[/C][C]98.41[/C][C]98.0337[/C][C]91.6408[/C][C]6.3929[/C][C]0.376264[/C][/ROW]
[ROW][C]31[/C][C]96.63[/C][C]92.1578[/C][C]91.7108[/C][C]0.446986[/C][C]4.47218[/C][/ROW]
[ROW][C]32[/C][C]89.8[/C][C]90.3479[/C][C]91.6996[/C][C]-1.35168[/C][C]-0.547903[/C][/ROW]
[ROW][C]33[/C][C]90[/C][C]91.381[/C][C]91.6221[/C][C]-0.241097[/C][C]-1.38099[/C][/ROW]
[ROW][C]34[/C][C]92.13[/C][C]93.2089[/C][C]91.4508[/C][C]1.75807[/C][C]-1.0789[/C][/ROW]
[ROW][C]35[/C][C]93.27[/C][C]91.7218[/C][C]91.3454[/C][C]0.376403[/C][C]1.54818[/C][/ROW]
[ROW][C]36[/C][C]90.81[/C][C]88.7516[/C][C]91.2717[/C][C]-2.5201[/C][C]2.05843[/C][/ROW]
[ROW][C]37[/C][C]85.42[/C][C]85.6644[/C][C]91.1025[/C][C]-5.4381[/C][C]-0.244403[/C][/ROW]
[ROW][C]38[/C][C]88.28[/C][C]88.5157[/C][C]91.2137[/C][C]-2.6981[/C][C]-0.235653[/C][/ROW]
[ROW][C]39[/C][C]88.73[/C][C]89.6296[/C][C]91.6883[/C][C]-2.05876[/C][C]-0.899569[/C][/ROW]
[ROW][C]40[/C][C]90.18[/C][C]93.5204[/C][C]92.3562[/C][C]1.16415[/C][C]-3.3404[/C][/ROW]
[ROW][C]41[/C][C]92.74[/C][C]97.131[/C][C]92.9617[/C][C]4.16932[/C][C]-4.39099[/C][/ROW]
[ROW][C]42[/C][C]96.13[/C][C]99.7771[/C][C]93.3842[/C][C]6.3929[/C][C]-3.64707[/C][/ROW]
[ROW][C]43[/C][C]94.85[/C][C]94.3807[/C][C]93.9338[/C][C]0.446986[/C][C]0.469264[/C][/ROW]
[ROW][C]44[/C][C]94.25[/C][C]93.3479[/C][C]94.6996[/C][C]-1.35168[/C][C]0.902097[/C][/ROW]
[ROW][C]45[/C][C]96.94[/C][C]95.2397[/C][C]95.4808[/C][C]-0.241097[/C][C]1.70026[/C][/ROW]
[ROW][C]46[/C][C]101.22[/C][C]98.0022[/C][C]96.2442[/C][C]1.75807[/C][C]3.21776[/C][/ROW]
[ROW][C]47[/C][C]98.71[/C][C]97.6456[/C][C]97.2692[/C][C]0.376403[/C][C]1.06443[/C][/ROW]
[ROW][C]48[/C][C]95.51[/C][C]95.8949[/C][C]98.415[/C][C]-2.5201[/C][C]-0.384903[/C][/ROW]
[ROW][C]49[/C][C]93.91[/C][C]93.7169[/C][C]99.155[/C][C]-5.4381[/C][C]0.193097[/C][/ROW]
[ROW][C]50[/C][C]98.17[/C][C]96.8911[/C][C]99.5892[/C][C]-2.6981[/C][C]1.27893[/C][/ROW]
[ROW][C]51[/C][C]97.59[/C][C]97.9392[/C][C]99.9979[/C][C]-2.05876[/C][C]-0.349153[/C][/ROW]
[ROW][C]52[/C][C]99.64[/C][C]101.363[/C][C]100.199[/C][C]1.16415[/C][C]-1.7229[/C][/ROW]
[ROW][C]53[/C][C]107.88[/C][C]104.302[/C][C]100.132[/C][C]4.16932[/C][C]3.57818[/C][/ROW]
[ROW][C]54[/C][C]108.49[/C][C]106.426[/C][C]100.033[/C][C]6.3929[/C][C]2.06418[/C][/ROW]
[ROW][C]55[/C][C]100.25[/C][C]100.474[/C][C]100.027[/C][C]0.446986[/C][C]-0.223653[/C][/ROW]
[ROW][C]56[/C][C]99.27[/C][C]98.5054[/C][C]99.8571[/C][C]-1.35168[/C][C]0.764597[/C][/ROW]
[ROW][C]57[/C][C]101.73[/C][C]99.3564[/C][C]99.5975[/C][C]-0.241097[/C][C]2.3736[/C][/ROW]
[ROW][C]58[/C][C]101.25[/C][C]101.566[/C][C]99.8075[/C][C]1.75807[/C][C]-0.315569[/C][/ROW]
[ROW][C]59[/C][C]97.09[/C][C]100.06[/C][C]99.6838[/C][C]0.376403[/C][C]-2.97015[/C][/ROW]
[ROW][C]60[/C][C]94.74[/C][C]96.4062[/C][C]98.9262[/C][C]-2.5201[/C][C]-1.66615[/C][/ROW]
[ROW][C]61[/C][C]94.53[/C][C]92.859[/C][C]98.2971[/C][C]-5.4381[/C][C]1.67101[/C][/ROW]
[ROW][C]62[/C][C]93.48[/C][C]94.8998[/C][C]97.5979[/C][C]-2.6981[/C][C]-1.41982[/C][/ROW]
[ROW][C]63[/C][C]96.05[/C][C]94.3612[/C][C]96.42[/C][C]-2.05876[/C][C]1.68876[/C][/ROW]
[ROW][C]64[/C][C]106.22[/C][C]96.3446[/C][C]95.1804[/C][C]1.16415[/C][C]9.87543[/C][/ROW]
[ROW][C]65[/C][C]98.33[/C][C]98.4289[/C][C]94.2596[/C][C]4.16932[/C][C]-0.0989028[/C][/ROW]
[ROW][C]66[/C][C]99.86[/C][C]99.9587[/C][C]93.5658[/C][C]6.3929[/C][C]-0.0987361[/C][/ROW]
[ROW][C]67[/C][C]93.78[/C][C]NA[/C][C]NA[/C][C]0.446986[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]88.96[/C][C]NA[/C][C]NA[/C][C]-1.35168[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]83.77[/C][C]NA[/C][C]NA[/C][C]-0.241097[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]89.46[/C][C]NA[/C][C]NA[/C][C]1.75807[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]86.78[/C][C]NA[/C][C]NA[/C][C]0.376403[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]88.4[/C][C]NA[/C][C]NA[/C][C]-2.5201[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284279&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284279&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	93.58	NA	NA	-5.4381	NA
2	95.79	NA	NA	-2.6981	NA
3	94.77	NA	NA	-2.05876	NA
4	94.2	NA	NA	1.16415	NA
5	96.23	NA	NA	4.16932	NA
6	92.3	NA	NA	6.3929	NA
7	88.86	91.5545	91.1075	0.446986	-2.69449
8	86.44	89.2625	90.6142	-1.35168	-2.82249
9	86.21	89.9885	90.2296	-0.241097	-3.77849
10	88.57	91.6272	89.8692	1.75807	-3.05724
11	90.69	90.3218	89.9454	0.376403	0.368181
12	89	88.0891	90.6092	-2.5201	0.910931
13	86.88	85.7207	91.1588	-5.4381	1.15935
14	90.65	88.9398	91.6379	-2.6981	1.71018
15	90.68	90.2592	92.3179	-2.05876	0.420847
16	89.64	94.1837	93.0196	1.16415	-4.54374
17	102.62	97.6768	93.5075	4.16932	4.94318
18	101.84	100.067	93.6737	6.3929	1.77335
19	92.51	94.0653	93.6183	0.446986	-1.55532
20	94.29	92.1183	93.47	-1.35168	2.17168
21	94.68	93.1264	93.3675	-0.241097	1.5536
22	96.94	95.2381	93.48	1.75807	1.70193
23	94.03	93.5727	93.1963	0.376403	0.457347
24	89.65	90.1003	92.6204	-2.5201	-0.450319
25	84.9	87.2111	92.6492	-5.4381	-2.31107
26	89.07	89.9357	92.6338	-2.6981	-0.865653
27	89.8	90.1929	92.2517	-2.05876	-0.392903
28	93.22	93.0204	91.8562	1.16415	0.199597
29	92.23	95.7935	91.6242	4.16932	-3.56349
30	98.41	98.0337	91.6408	6.3929	0.376264
31	96.63	92.1578	91.7108	0.446986	4.47218
32	89.8	90.3479	91.6996	-1.35168	-0.547903
33	90	91.381	91.6221	-0.241097	-1.38099
34	92.13	93.2089	91.4508	1.75807	-1.0789
35	93.27	91.7218	91.3454	0.376403	1.54818
36	90.81	88.7516	91.2717	-2.5201	2.05843
37	85.42	85.6644	91.1025	-5.4381	-0.244403
38	88.28	88.5157	91.2137	-2.6981	-0.235653
39	88.73	89.6296	91.6883	-2.05876	-0.899569
40	90.18	93.5204	92.3562	1.16415	-3.3404
41	92.74	97.131	92.9617	4.16932	-4.39099
42	96.13	99.7771	93.3842	6.3929	-3.64707
43	94.85	94.3807	93.9338	0.446986	0.469264
44	94.25	93.3479	94.6996	-1.35168	0.902097
45	96.94	95.2397	95.4808	-0.241097	1.70026
46	101.22	98.0022	96.2442	1.75807	3.21776
47	98.71	97.6456	97.2692	0.376403	1.06443
48	95.51	95.8949	98.415	-2.5201	-0.384903
49	93.91	93.7169	99.155	-5.4381	0.193097
50	98.17	96.8911	99.5892	-2.6981	1.27893
51	97.59	97.9392	99.9979	-2.05876	-0.349153
52	99.64	101.363	100.199	1.16415	-1.7229
53	107.88	104.302	100.132	4.16932	3.57818
54	108.49	106.426	100.033	6.3929	2.06418
55	100.25	100.474	100.027	0.446986	-0.223653
56	99.27	98.5054	99.8571	-1.35168	0.764597
57	101.73	99.3564	99.5975	-0.241097	2.3736
58	101.25	101.566	99.8075	1.75807	-0.315569
59	97.09	100.06	99.6838	0.376403	-2.97015
60	94.74	96.4062	98.9262	-2.5201	-1.66615
61	94.53	92.859	98.2971	-5.4381	1.67101
62	93.48	94.8998	97.5979	-2.6981	-1.41982
63	96.05	94.3612	96.42	-2.05876	1.68876
64	106.22	96.3446	95.1804	1.16415	9.87543
65	98.33	98.4289	94.2596	4.16932	-0.0989028
66	99.86	99.9587	93.5658	6.3929	-0.0987361
67	93.78	NA	NA	0.446986	NA
68	88.96	NA	NA	-1.35168	NA
69	83.77	NA	NA	-0.241097	NA
70	89.46	NA	NA	1.75807	NA
71	86.78	NA	NA	0.376403	NA
72	88.4	NA	NA	-2.5201	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