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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 26 Nov 2016 10:11:35 +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/2016/Nov/26/t1480155137pmg3nb560s1bjkm.htm/, Retrieved Fri, 03 May 2024 20:33:32 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 03 May 2024 20:33:32 +0200

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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	1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]1 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=&T=0

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

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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	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	97.78	NA	NA	-0.255069	NA
2	97.73	NA	NA	-0.310653	NA
3	97.61	NA	NA	-0.344403	NA
4	97.69	NA	NA	-0.430736	NA
5	97.68	NA	NA	-0.484153	NA
6	97.67	NA	NA	-0.477986	NA
7	97.67	98.0558	98.3254	-0.269569	-0.385847
8	97.96	98.2658	98.4937	-0.227903	-0.305847
9	98.27	98.8104	98.6792	0.131264	-0.540431
10	99.52	99.7117	98.885	0.826681	-0.191681
11	99.59	100	99.0917	0.908681	-0.410347
12	99.75	100.226	99.2921	0.933847	-0.475931
13	99.75	99.2378	99.4929	-0.255069	0.512153
14	99.8	99.3702	99.6808	-0.310653	0.429819
15	99.99	99.5377	99.8821	-0.344403	0.452319
16	100.25	99.6605	100.091	-0.430736	0.589486
17	100.08	99.7954	100.28	-0.484153	0.284569
18	100.08	99.9866	100.465	-0.477986	0.0934028
19	100.08	100.379	100.649	-0.269569	-0.299181
20	100.06	100.602	100.83	-0.227903	-0.541681
21	101	101.135	101.003	0.131264	-0.134597
22	101.81	101.993	101.166	0.826681	-0.182514
23	101.82	102.235	101.326	0.908681	-0.414931
24	101.96	102.437	101.503	0.933847	-0.477181
25	101.96	101.437	101.692	-0.255069	0.523403
26	101.93	101.57	101.88	-0.310653	0.360236
27	102.03	101.704	102.049	-0.344403	0.325653
28	102.11	101.745	102.175	-0.430736	0.365319
29	102.07	101.809	102.293	-0.484153	0.260819
30	102.34	101.942	102.42	-0.477986	0.397986
31	102.34	102.093	102.363	-0.269569	0.247069
32	102.33	101.9	102.128	-0.227903	0.430403
33	102.77	102.025	101.894	0.131264	0.744569
34	103.08	102.474	101.648	0.826681	0.605819
35	103.38	102.302	101.394	0.908681	1.07757
36	103.44	102.068	101.135	0.933847	1.37157
37	99.1	100.652	100.907	-0.255069	-1.55201
38	99.15	100.419	100.73	-0.310653	-1.26935
39	99.21	100.209	100.553	-0.344403	-0.998931
40	99.01	99.9593	100.39	-0.430736	-0.949264
41	99.08	99.7563	100.24	-0.484153	-0.676264
42	99.11	99.6028	100.081	-0.477986	-0.492847
43	100.11	99.7967	100.066	-0.269569	0.313319
44	100.31	99.9733	100.201	-0.227903	0.336653
45	100.55	100.458	100.327	0.131264	0.0916528
46	101.38	101.266	100.44	0.826681	0.113736
47	101.49	101.458	100.549	0.908681	0.0321528
48	101.5	101.588	100.654	0.933847	-0.0880139
49	100.69	100.49	100.745	-0.255069	0.200486
50	100.8	100.509	100.819	-0.310653	0.291486
51	100.58	100.544	100.888	-0.344403	0.0364861
52	100.34	100.516	100.947	-0.430736	-0.175931
53	100.38	100.519	101.003	-0.484153	-0.138764
54	100.33	100.591	101.069	-0.477986	-0.261181
55	101.06	100.885	101.155	-0.269569	0.174569
56	101.15	101.02	101.247	-0.227903	0.130403
57	101.36	101.471	101.34	0.131264	-0.111264
58	101.98	102.275	101.449	0.826681	-0.295431
59	102.24	102.475	101.566	0.908681	-0.234514
60	102.34	102.621	101.687	0.933847	-0.280514
61	101.91	101.544	101.799	-0.255069	0.365903
62	101.8	101.562	101.873	-0.310653	0.237736
63	101.8	101.566	101.91	-0.344403	0.234403
64	101.73	101.51	101.94	-0.430736	0.220319
65	101.8	101.48	101.965	-0.484153	0.319569
66	101.81	101.497	101.975	-0.477986	0.312569
67	102.28	NA	NA	-0.269569	NA
68	101.7	NA	NA	-0.227903	NA
69	101.7	NA	NA	0.131264	NA
70	102.37	NA	NA	0.826681	NA
71	102.43	NA	NA	0.908681	NA
72	102.41	NA	NA	0.933847	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 97.78 & NA & NA & -0.255069 & NA \tabularnewline
2 & 97.73 & NA & NA & -0.310653 & NA \tabularnewline
3 & 97.61 & NA & NA & -0.344403 & NA \tabularnewline
4 & 97.69 & NA & NA & -0.430736 & NA \tabularnewline
5 & 97.68 & NA & NA & -0.484153 & NA \tabularnewline
6 & 97.67 & NA & NA & -0.477986 & NA \tabularnewline
7 & 97.67 & 98.0558 & 98.3254 & -0.269569 & -0.385847 \tabularnewline
8 & 97.96 & 98.2658 & 98.4937 & -0.227903 & -0.305847 \tabularnewline
9 & 98.27 & 98.8104 & 98.6792 & 0.131264 & -0.540431 \tabularnewline
10 & 99.52 & 99.7117 & 98.885 & 0.826681 & -0.191681 \tabularnewline
11 & 99.59 & 100 & 99.0917 & 0.908681 & -0.410347 \tabularnewline
12 & 99.75 & 100.226 & 99.2921 & 0.933847 & -0.475931 \tabularnewline
13 & 99.75 & 99.2378 & 99.4929 & -0.255069 & 0.512153 \tabularnewline
14 & 99.8 & 99.3702 & 99.6808 & -0.310653 & 0.429819 \tabularnewline
15 & 99.99 & 99.5377 & 99.8821 & -0.344403 & 0.452319 \tabularnewline
16 & 100.25 & 99.6605 & 100.091 & -0.430736 & 0.589486 \tabularnewline
17 & 100.08 & 99.7954 & 100.28 & -0.484153 & 0.284569 \tabularnewline
18 & 100.08 & 99.9866 & 100.465 & -0.477986 & 0.0934028 \tabularnewline
19 & 100.08 & 100.379 & 100.649 & -0.269569 & -0.299181 \tabularnewline
20 & 100.06 & 100.602 & 100.83 & -0.227903 & -0.541681 \tabularnewline
21 & 101 & 101.135 & 101.003 & 0.131264 & -0.134597 \tabularnewline
22 & 101.81 & 101.993 & 101.166 & 0.826681 & -0.182514 \tabularnewline
23 & 101.82 & 102.235 & 101.326 & 0.908681 & -0.414931 \tabularnewline
24 & 101.96 & 102.437 & 101.503 & 0.933847 & -0.477181 \tabularnewline
25 & 101.96 & 101.437 & 101.692 & -0.255069 & 0.523403 \tabularnewline
26 & 101.93 & 101.57 & 101.88 & -0.310653 & 0.360236 \tabularnewline
27 & 102.03 & 101.704 & 102.049 & -0.344403 & 0.325653 \tabularnewline
28 & 102.11 & 101.745 & 102.175 & -0.430736 & 0.365319 \tabularnewline
29 & 102.07 & 101.809 & 102.293 & -0.484153 & 0.260819 \tabularnewline
30 & 102.34 & 101.942 & 102.42 & -0.477986 & 0.397986 \tabularnewline
31 & 102.34 & 102.093 & 102.363 & -0.269569 & 0.247069 \tabularnewline
32 & 102.33 & 101.9 & 102.128 & -0.227903 & 0.430403 \tabularnewline
33 & 102.77 & 102.025 & 101.894 & 0.131264 & 0.744569 \tabularnewline
34 & 103.08 & 102.474 & 101.648 & 0.826681 & 0.605819 \tabularnewline
35 & 103.38 & 102.302 & 101.394 & 0.908681 & 1.07757 \tabularnewline
36 & 103.44 & 102.068 & 101.135 & 0.933847 & 1.37157 \tabularnewline
37 & 99.1 & 100.652 & 100.907 & -0.255069 & -1.55201 \tabularnewline
38 & 99.15 & 100.419 & 100.73 & -0.310653 & -1.26935 \tabularnewline
39 & 99.21 & 100.209 & 100.553 & -0.344403 & -0.998931 \tabularnewline
40 & 99.01 & 99.9593 & 100.39 & -0.430736 & -0.949264 \tabularnewline
41 & 99.08 & 99.7563 & 100.24 & -0.484153 & -0.676264 \tabularnewline
42 & 99.11 & 99.6028 & 100.081 & -0.477986 & -0.492847 \tabularnewline
43 & 100.11 & 99.7967 & 100.066 & -0.269569 & 0.313319 \tabularnewline
44 & 100.31 & 99.9733 & 100.201 & -0.227903 & 0.336653 \tabularnewline
45 & 100.55 & 100.458 & 100.327 & 0.131264 & 0.0916528 \tabularnewline
46 & 101.38 & 101.266 & 100.44 & 0.826681 & 0.113736 \tabularnewline
47 & 101.49 & 101.458 & 100.549 & 0.908681 & 0.0321528 \tabularnewline
48 & 101.5 & 101.588 & 100.654 & 0.933847 & -0.0880139 \tabularnewline
49 & 100.69 & 100.49 & 100.745 & -0.255069 & 0.200486 \tabularnewline
50 & 100.8 & 100.509 & 100.819 & -0.310653 & 0.291486 \tabularnewline
51 & 100.58 & 100.544 & 100.888 & -0.344403 & 0.0364861 \tabularnewline
52 & 100.34 & 100.516 & 100.947 & -0.430736 & -0.175931 \tabularnewline
53 & 100.38 & 100.519 & 101.003 & -0.484153 & -0.138764 \tabularnewline
54 & 100.33 & 100.591 & 101.069 & -0.477986 & -0.261181 \tabularnewline
55 & 101.06 & 100.885 & 101.155 & -0.269569 & 0.174569 \tabularnewline
56 & 101.15 & 101.02 & 101.247 & -0.227903 & 0.130403 \tabularnewline
57 & 101.36 & 101.471 & 101.34 & 0.131264 & -0.111264 \tabularnewline
58 & 101.98 & 102.275 & 101.449 & 0.826681 & -0.295431 \tabularnewline
59 & 102.24 & 102.475 & 101.566 & 0.908681 & -0.234514 \tabularnewline
60 & 102.34 & 102.621 & 101.687 & 0.933847 & -0.280514 \tabularnewline
61 & 101.91 & 101.544 & 101.799 & -0.255069 & 0.365903 \tabularnewline
62 & 101.8 & 101.562 & 101.873 & -0.310653 & 0.237736 \tabularnewline
63 & 101.8 & 101.566 & 101.91 & -0.344403 & 0.234403 \tabularnewline
64 & 101.73 & 101.51 & 101.94 & -0.430736 & 0.220319 \tabularnewline
65 & 101.8 & 101.48 & 101.965 & -0.484153 & 0.319569 \tabularnewline
66 & 101.81 & 101.497 & 101.975 & -0.477986 & 0.312569 \tabularnewline
67 & 102.28 & NA & NA & -0.269569 & NA \tabularnewline
68 & 101.7 & NA & NA & -0.227903 & NA \tabularnewline
69 & 101.7 & NA & NA & 0.131264 & NA \tabularnewline
70 & 102.37 & NA & NA & 0.826681 & NA \tabularnewline
71 & 102.43 & NA & NA & 0.908681 & NA \tabularnewline
72 & 102.41 & NA & NA & 0.933847 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]97.78[/C][C]NA[/C][C]NA[/C][C]-0.255069[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]97.73[/C][C]NA[/C][C]NA[/C][C]-0.310653[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]97.61[/C][C]NA[/C][C]NA[/C][C]-0.344403[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]97.69[/C][C]NA[/C][C]NA[/C][C]-0.430736[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]97.68[/C][C]NA[/C][C]NA[/C][C]-0.484153[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]97.67[/C][C]NA[/C][C]NA[/C][C]-0.477986[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]97.67[/C][C]98.0558[/C][C]98.3254[/C][C]-0.269569[/C][C]-0.385847[/C][/ROW]
[ROW][C]8[/C][C]97.96[/C][C]98.2658[/C][C]98.4937[/C][C]-0.227903[/C][C]-0.305847[/C][/ROW]
[ROW][C]9[/C][C]98.27[/C][C]98.8104[/C][C]98.6792[/C][C]0.131264[/C][C]-0.540431[/C][/ROW]
[ROW][C]10[/C][C]99.52[/C][C]99.7117[/C][C]98.885[/C][C]0.826681[/C][C]-0.191681[/C][/ROW]
[ROW][C]11[/C][C]99.59[/C][C]100[/C][C]99.0917[/C][C]0.908681[/C][C]-0.410347[/C][/ROW]
[ROW][C]12[/C][C]99.75[/C][C]100.226[/C][C]99.2921[/C][C]0.933847[/C][C]-0.475931[/C][/ROW]
[ROW][C]13[/C][C]99.75[/C][C]99.2378[/C][C]99.4929[/C][C]-0.255069[/C][C]0.512153[/C][/ROW]
[ROW][C]14[/C][C]99.8[/C][C]99.3702[/C][C]99.6808[/C][C]-0.310653[/C][C]0.429819[/C][/ROW]
[ROW][C]15[/C][C]99.99[/C][C]99.5377[/C][C]99.8821[/C][C]-0.344403[/C][C]0.452319[/C][/ROW]
[ROW][C]16[/C][C]100.25[/C][C]99.6605[/C][C]100.091[/C][C]-0.430736[/C][C]0.589486[/C][/ROW]
[ROW][C]17[/C][C]100.08[/C][C]99.7954[/C][C]100.28[/C][C]-0.484153[/C][C]0.284569[/C][/ROW]
[ROW][C]18[/C][C]100.08[/C][C]99.9866[/C][C]100.465[/C][C]-0.477986[/C][C]0.0934028[/C][/ROW]
[ROW][C]19[/C][C]100.08[/C][C]100.379[/C][C]100.649[/C][C]-0.269569[/C][C]-0.299181[/C][/ROW]
[ROW][C]20[/C][C]100.06[/C][C]100.602[/C][C]100.83[/C][C]-0.227903[/C][C]-0.541681[/C][/ROW]
[ROW][C]21[/C][C]101[/C][C]101.135[/C][C]101.003[/C][C]0.131264[/C][C]-0.134597[/C][/ROW]
[ROW][C]22[/C][C]101.81[/C][C]101.993[/C][C]101.166[/C][C]0.826681[/C][C]-0.182514[/C][/ROW]
[ROW][C]23[/C][C]101.82[/C][C]102.235[/C][C]101.326[/C][C]0.908681[/C][C]-0.414931[/C][/ROW]
[ROW][C]24[/C][C]101.96[/C][C]102.437[/C][C]101.503[/C][C]0.933847[/C][C]-0.477181[/C][/ROW]
[ROW][C]25[/C][C]101.96[/C][C]101.437[/C][C]101.692[/C][C]-0.255069[/C][C]0.523403[/C][/ROW]
[ROW][C]26[/C][C]101.93[/C][C]101.57[/C][C]101.88[/C][C]-0.310653[/C][C]0.360236[/C][/ROW]
[ROW][C]27[/C][C]102.03[/C][C]101.704[/C][C]102.049[/C][C]-0.344403[/C][C]0.325653[/C][/ROW]
[ROW][C]28[/C][C]102.11[/C][C]101.745[/C][C]102.175[/C][C]-0.430736[/C][C]0.365319[/C][/ROW]
[ROW][C]29[/C][C]102.07[/C][C]101.809[/C][C]102.293[/C][C]-0.484153[/C][C]0.260819[/C][/ROW]
[ROW][C]30[/C][C]102.34[/C][C]101.942[/C][C]102.42[/C][C]-0.477986[/C][C]0.397986[/C][/ROW]
[ROW][C]31[/C][C]102.34[/C][C]102.093[/C][C]102.363[/C][C]-0.269569[/C][C]0.247069[/C][/ROW]
[ROW][C]32[/C][C]102.33[/C][C]101.9[/C][C]102.128[/C][C]-0.227903[/C][C]0.430403[/C][/ROW]
[ROW][C]33[/C][C]102.77[/C][C]102.025[/C][C]101.894[/C][C]0.131264[/C][C]0.744569[/C][/ROW]
[ROW][C]34[/C][C]103.08[/C][C]102.474[/C][C]101.648[/C][C]0.826681[/C][C]0.605819[/C][/ROW]
[ROW][C]35[/C][C]103.38[/C][C]102.302[/C][C]101.394[/C][C]0.908681[/C][C]1.07757[/C][/ROW]
[ROW][C]36[/C][C]103.44[/C][C]102.068[/C][C]101.135[/C][C]0.933847[/C][C]1.37157[/C][/ROW]
[ROW][C]37[/C][C]99.1[/C][C]100.652[/C][C]100.907[/C][C]-0.255069[/C][C]-1.55201[/C][/ROW]
[ROW][C]38[/C][C]99.15[/C][C]100.419[/C][C]100.73[/C][C]-0.310653[/C][C]-1.26935[/C][/ROW]
[ROW][C]39[/C][C]99.21[/C][C]100.209[/C][C]100.553[/C][C]-0.344403[/C][C]-0.998931[/C][/ROW]
[ROW][C]40[/C][C]99.01[/C][C]99.9593[/C][C]100.39[/C][C]-0.430736[/C][C]-0.949264[/C][/ROW]
[ROW][C]41[/C][C]99.08[/C][C]99.7563[/C][C]100.24[/C][C]-0.484153[/C][C]-0.676264[/C][/ROW]
[ROW][C]42[/C][C]99.11[/C][C]99.6028[/C][C]100.081[/C][C]-0.477986[/C][C]-0.492847[/C][/ROW]
[ROW][C]43[/C][C]100.11[/C][C]99.7967[/C][C]100.066[/C][C]-0.269569[/C][C]0.313319[/C][/ROW]
[ROW][C]44[/C][C]100.31[/C][C]99.9733[/C][C]100.201[/C][C]-0.227903[/C][C]0.336653[/C][/ROW]
[ROW][C]45[/C][C]100.55[/C][C]100.458[/C][C]100.327[/C][C]0.131264[/C][C]0.0916528[/C][/ROW]
[ROW][C]46[/C][C]101.38[/C][C]101.266[/C][C]100.44[/C][C]0.826681[/C][C]0.113736[/C][/ROW]
[ROW][C]47[/C][C]101.49[/C][C]101.458[/C][C]100.549[/C][C]0.908681[/C][C]0.0321528[/C][/ROW]
[ROW][C]48[/C][C]101.5[/C][C]101.588[/C][C]100.654[/C][C]0.933847[/C][C]-0.0880139[/C][/ROW]
[ROW][C]49[/C][C]100.69[/C][C]100.49[/C][C]100.745[/C][C]-0.255069[/C][C]0.200486[/C][/ROW]
[ROW][C]50[/C][C]100.8[/C][C]100.509[/C][C]100.819[/C][C]-0.310653[/C][C]0.291486[/C][/ROW]
[ROW][C]51[/C][C]100.58[/C][C]100.544[/C][C]100.888[/C][C]-0.344403[/C][C]0.0364861[/C][/ROW]
[ROW][C]52[/C][C]100.34[/C][C]100.516[/C][C]100.947[/C][C]-0.430736[/C][C]-0.175931[/C][/ROW]
[ROW][C]53[/C][C]100.38[/C][C]100.519[/C][C]101.003[/C][C]-0.484153[/C][C]-0.138764[/C][/ROW]
[ROW][C]54[/C][C]100.33[/C][C]100.591[/C][C]101.069[/C][C]-0.477986[/C][C]-0.261181[/C][/ROW]
[ROW][C]55[/C][C]101.06[/C][C]100.885[/C][C]101.155[/C][C]-0.269569[/C][C]0.174569[/C][/ROW]
[ROW][C]56[/C][C]101.15[/C][C]101.02[/C][C]101.247[/C][C]-0.227903[/C][C]0.130403[/C][/ROW]
[ROW][C]57[/C][C]101.36[/C][C]101.471[/C][C]101.34[/C][C]0.131264[/C][C]-0.111264[/C][/ROW]
[ROW][C]58[/C][C]101.98[/C][C]102.275[/C][C]101.449[/C][C]0.826681[/C][C]-0.295431[/C][/ROW]
[ROW][C]59[/C][C]102.24[/C][C]102.475[/C][C]101.566[/C][C]0.908681[/C][C]-0.234514[/C][/ROW]
[ROW][C]60[/C][C]102.34[/C][C]102.621[/C][C]101.687[/C][C]0.933847[/C][C]-0.280514[/C][/ROW]
[ROW][C]61[/C][C]101.91[/C][C]101.544[/C][C]101.799[/C][C]-0.255069[/C][C]0.365903[/C][/ROW]
[ROW][C]62[/C][C]101.8[/C][C]101.562[/C][C]101.873[/C][C]-0.310653[/C][C]0.237736[/C][/ROW]
[ROW][C]63[/C][C]101.8[/C][C]101.566[/C][C]101.91[/C][C]-0.344403[/C][C]0.234403[/C][/ROW]
[ROW][C]64[/C][C]101.73[/C][C]101.51[/C][C]101.94[/C][C]-0.430736[/C][C]0.220319[/C][/ROW]
[ROW][C]65[/C][C]101.8[/C][C]101.48[/C][C]101.965[/C][C]-0.484153[/C][C]0.319569[/C][/ROW]
[ROW][C]66[/C][C]101.81[/C][C]101.497[/C][C]101.975[/C][C]-0.477986[/C][C]0.312569[/C][/ROW]
[ROW][C]67[/C][C]102.28[/C][C]NA[/C][C]NA[/C][C]-0.269569[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.7[/C][C]NA[/C][C]NA[/C][C]-0.227903[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]101.7[/C][C]NA[/C][C]NA[/C][C]0.131264[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]102.37[/C][C]NA[/C][C]NA[/C][C]0.826681[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]102.43[/C][C]NA[/C][C]NA[/C][C]0.908681[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]102.41[/C][C]NA[/C][C]NA[/C][C]0.933847[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	97.78	NA	NA	-0.255069	NA
2	97.73	NA	NA	-0.310653	NA
3	97.61	NA	NA	-0.344403	NA
4	97.69	NA	NA	-0.430736	NA
5	97.68	NA	NA	-0.484153	NA
6	97.67	NA	NA	-0.477986	NA
7	97.67	98.0558	98.3254	-0.269569	-0.385847
8	97.96	98.2658	98.4937	-0.227903	-0.305847
9	98.27	98.8104	98.6792	0.131264	-0.540431
10	99.52	99.7117	98.885	0.826681	-0.191681
11	99.59	100	99.0917	0.908681	-0.410347
12	99.75	100.226	99.2921	0.933847	-0.475931
13	99.75	99.2378	99.4929	-0.255069	0.512153
14	99.8	99.3702	99.6808	-0.310653	0.429819
15	99.99	99.5377	99.8821	-0.344403	0.452319
16	100.25	99.6605	100.091	-0.430736	0.589486
17	100.08	99.7954	100.28	-0.484153	0.284569
18	100.08	99.9866	100.465	-0.477986	0.0934028
19	100.08	100.379	100.649	-0.269569	-0.299181
20	100.06	100.602	100.83	-0.227903	-0.541681
21	101	101.135	101.003	0.131264	-0.134597
22	101.81	101.993	101.166	0.826681	-0.182514
23	101.82	102.235	101.326	0.908681	-0.414931
24	101.96	102.437	101.503	0.933847	-0.477181
25	101.96	101.437	101.692	-0.255069	0.523403
26	101.93	101.57	101.88	-0.310653	0.360236
27	102.03	101.704	102.049	-0.344403	0.325653
28	102.11	101.745	102.175	-0.430736	0.365319
29	102.07	101.809	102.293	-0.484153	0.260819
30	102.34	101.942	102.42	-0.477986	0.397986
31	102.34	102.093	102.363	-0.269569	0.247069
32	102.33	101.9	102.128	-0.227903	0.430403
33	102.77	102.025	101.894	0.131264	0.744569
34	103.08	102.474	101.648	0.826681	0.605819
35	103.38	102.302	101.394	0.908681	1.07757
36	103.44	102.068	101.135	0.933847	1.37157
37	99.1	100.652	100.907	-0.255069	-1.55201
38	99.15	100.419	100.73	-0.310653	-1.26935
39	99.21	100.209	100.553	-0.344403	-0.998931
40	99.01	99.9593	100.39	-0.430736	-0.949264
41	99.08	99.7563	100.24	-0.484153	-0.676264
42	99.11	99.6028	100.081	-0.477986	-0.492847
43	100.11	99.7967	100.066	-0.269569	0.313319
44	100.31	99.9733	100.201	-0.227903	0.336653
45	100.55	100.458	100.327	0.131264	0.0916528
46	101.38	101.266	100.44	0.826681	0.113736
47	101.49	101.458	100.549	0.908681	0.0321528
48	101.5	101.588	100.654	0.933847	-0.0880139
49	100.69	100.49	100.745	-0.255069	0.200486
50	100.8	100.509	100.819	-0.310653	0.291486
51	100.58	100.544	100.888	-0.344403	0.0364861
52	100.34	100.516	100.947	-0.430736	-0.175931
53	100.38	100.519	101.003	-0.484153	-0.138764
54	100.33	100.591	101.069	-0.477986	-0.261181
55	101.06	100.885	101.155	-0.269569	0.174569
56	101.15	101.02	101.247	-0.227903	0.130403
57	101.36	101.471	101.34	0.131264	-0.111264
58	101.98	102.275	101.449	0.826681	-0.295431
59	102.24	102.475	101.566	0.908681	-0.234514
60	102.34	102.621	101.687	0.933847	-0.280514
61	101.91	101.544	101.799	-0.255069	0.365903
62	101.8	101.562	101.873	-0.310653	0.237736
63	101.8	101.566	101.91	-0.344403	0.234403
64	101.73	101.51	101.94	-0.430736	0.220319
65	101.8	101.48	101.965	-0.484153	0.319569
66	101.81	101.497	101.975	-0.477986	0.312569
67	102.28	NA	NA	-0.269569	NA
68	101.7	NA	NA	-0.227903	NA
69	101.7	NA	NA	0.131264	NA
70	102.37	NA	NA	0.826681	NA
71	102.43	NA	NA	0.908681	NA
72	102.41	NA	NA	0.933847	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