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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 29 Apr 2017 13:04:23 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/29/t1493468216arhh6403bp3zylq.htm/, Retrieved Sun, 12 May 2024 20:07:22 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 12 May 2024 20:07:22 +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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.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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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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	100.18	NA	NA	-0.0595556	NA
2	99.73	NA	NA	-0.117556	NA
3	99.69	NA	NA	-0.154139	NA
4	99.45	NA	NA	-0.0342222	NA
5	99.47	NA	NA	-0.0373889	NA
6	99.56	NA	NA	0.0401944	NA
7	99.54	99.7279	99.7304	-0.00247222	-0.187944
8	99.87	99.7659	99.725	0.0409444	0.104056
9	99.73	99.8567	99.7342	0.122528	-0.126694
10	99.86	99.9013	99.7662	0.135028	-0.0412778
11	99.91	99.8399	99.8188	0.0211111	0.0701389
12	99.91	99.9109	99.8654	0.0455278	-0.000944444
13	99.91	99.8534	99.9129	-0.0595556	0.0566389
14	99.87	99.8345	99.9521	-0.117556	0.0354722
15	99.77	99.8484	100.002	-0.154139	-0.0783611
16	100.14	100.02	100.055	-0.0342222	0.119639
17	100.04	100.035	100.072	-0.0373889	0.00530556
18	100.11	100.111	100.071	0.0401944	-0.00102778
19	100.13	100.063	100.066	-0.00247222	0.0666389
20	100.22	100.103	100.062	0.0409444	0.116556
21	100.59	100.2	100.077	0.122528	0.389972
22	100.25	100.237	100.102	0.135028	0.0133056
23	99.94	100.159	100.138	0.0211111	-0.219444
24	99.85	100.233	100.187	0.0455278	-0.383028
25	99.85	100.169	100.228	-0.0595556	-0.318778
26	99.85	100.143	100.261	-0.117556	-0.293278
27	100.15	100.121	100.275	-0.154139	0.0287222
28	100.34	100.257	100.291	-0.0342222	0.0833889
29	100.72	100.276	100.313	-0.0373889	0.444056
30	100.61	100.377	100.337	0.0401944	0.232722
31	100.61	100.364	100.366	-0.00247222	0.246222
32	100.52	100.428	100.387	0.0409444	0.0923889
33	100.64	100.496	100.373	0.122528	0.144139
34	100.57	100.469	100.334	0.135028	0.101222
35	100.16	100.285	100.264	0.0211111	-0.125278
36	100.2	100.221	100.176	0.0455278	-0.0213611
37	100.2	100.04	100.1	-0.0595556	0.159972
38	99.99	99.9124	100.03	-0.117556	0.0775556
39	99.69	99.8154	99.9696	-0.154139	-0.125444
40	99.85	99.8958	99.93	-0.0342222	-0.0457778
41	99.54	99.898	99.9354	-0.0373889	-0.358028
42	99.67	100.016	99.9762	0.0401944	-0.346444
43	99.72	100.002	100.004	-0.00247222	-0.281694
44	99.74	100.063	100.022	0.0409444	-0.323028
45	99.97	100.185	100.062	0.122528	-0.214611
46	100.29	100.245	100.11	0.135028	0.0449722
47	100.57	100.192	100.17	0.0211111	0.378472
48	100.77	100.297	100.251	0.0455278	0.473222
49	100.3	100.275	100.334	-0.0595556	0.0253889
50	100.32	100.294	100.412	-0.117556	0.0258889
51	100.32	100.317	100.471	-0.154139	0.00288889
52	100.37	100.474	100.508	-0.0342222	-0.103694
53	100.47	100.482	100.52	-0.0373889	-0.0121944
54	100.68	100.549	100.509	0.0401944	0.130639
55	100.7	100.51	100.513	-0.00247222	0.189556
56	100.62	100.577	100.536	0.0409444	0.0428056
57	100.52	100.68	100.557	0.122528	-0.160028
58	100.62	100.705	100.57	0.135028	-0.0854444
59	100.52	100.591	100.57	0.0211111	-0.0711111
60	100.57	100.605	100.56	0.0455278	-0.0351111
61	100.59	100.48	100.54	-0.0595556	0.109556
62	100.59	100.403	100.52	-0.117556	0.187139
63	100.56	100.355	100.509	-0.154139	0.204972
64	100.44	100.461	100.495	-0.0342222	-0.0207778
65	100.39	100.436	100.474	-0.0373889	-0.0463611
66	100.51	100.493	100.453	0.0401944	0.0168889
67	100.4	NA	NA	-0.00247222	NA
68	100.45	NA	NA	0.0409444	NA
69	100.42	NA	NA	0.122528	NA
70	100.38	NA	NA	0.135028	NA
71	100.25	NA	NA	0.0211111	NA
72	100.34	NA	NA	0.0455278	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 100.18 & NA & NA & -0.0595556 & NA \tabularnewline
2 & 99.73 & NA & NA & -0.117556 & NA \tabularnewline
3 & 99.69 & NA & NA & -0.154139 & NA \tabularnewline
4 & 99.45 & NA & NA & -0.0342222 & NA \tabularnewline
5 & 99.47 & NA & NA & -0.0373889 & NA \tabularnewline
6 & 99.56 & NA & NA & 0.0401944 & NA \tabularnewline
7 & 99.54 & 99.7279 & 99.7304 & -0.00247222 & -0.187944 \tabularnewline
8 & 99.87 & 99.7659 & 99.725 & 0.0409444 & 0.104056 \tabularnewline
9 & 99.73 & 99.8567 & 99.7342 & 0.122528 & -0.126694 \tabularnewline
10 & 99.86 & 99.9013 & 99.7662 & 0.135028 & -0.0412778 \tabularnewline
11 & 99.91 & 99.8399 & 99.8188 & 0.0211111 & 0.0701389 \tabularnewline
12 & 99.91 & 99.9109 & 99.8654 & 0.0455278 & -0.000944444 \tabularnewline
13 & 99.91 & 99.8534 & 99.9129 & -0.0595556 & 0.0566389 \tabularnewline
14 & 99.87 & 99.8345 & 99.9521 & -0.117556 & 0.0354722 \tabularnewline
15 & 99.77 & 99.8484 & 100.002 & -0.154139 & -0.0783611 \tabularnewline
16 & 100.14 & 100.02 & 100.055 & -0.0342222 & 0.119639 \tabularnewline
17 & 100.04 & 100.035 & 100.072 & -0.0373889 & 0.00530556 \tabularnewline
18 & 100.11 & 100.111 & 100.071 & 0.0401944 & -0.00102778 \tabularnewline
19 & 100.13 & 100.063 & 100.066 & -0.00247222 & 0.0666389 \tabularnewline
20 & 100.22 & 100.103 & 100.062 & 0.0409444 & 0.116556 \tabularnewline
21 & 100.59 & 100.2 & 100.077 & 0.122528 & 0.389972 \tabularnewline
22 & 100.25 & 100.237 & 100.102 & 0.135028 & 0.0133056 \tabularnewline
23 & 99.94 & 100.159 & 100.138 & 0.0211111 & -0.219444 \tabularnewline
24 & 99.85 & 100.233 & 100.187 & 0.0455278 & -0.383028 \tabularnewline
25 & 99.85 & 100.169 & 100.228 & -0.0595556 & -0.318778 \tabularnewline
26 & 99.85 & 100.143 & 100.261 & -0.117556 & -0.293278 \tabularnewline
27 & 100.15 & 100.121 & 100.275 & -0.154139 & 0.0287222 \tabularnewline
28 & 100.34 & 100.257 & 100.291 & -0.0342222 & 0.0833889 \tabularnewline
29 & 100.72 & 100.276 & 100.313 & -0.0373889 & 0.444056 \tabularnewline
30 & 100.61 & 100.377 & 100.337 & 0.0401944 & 0.232722 \tabularnewline
31 & 100.61 & 100.364 & 100.366 & -0.00247222 & 0.246222 \tabularnewline
32 & 100.52 & 100.428 & 100.387 & 0.0409444 & 0.0923889 \tabularnewline
33 & 100.64 & 100.496 & 100.373 & 0.122528 & 0.144139 \tabularnewline
34 & 100.57 & 100.469 & 100.334 & 0.135028 & 0.101222 \tabularnewline
35 & 100.16 & 100.285 & 100.264 & 0.0211111 & -0.125278 \tabularnewline
36 & 100.2 & 100.221 & 100.176 & 0.0455278 & -0.0213611 \tabularnewline
37 & 100.2 & 100.04 & 100.1 & -0.0595556 & 0.159972 \tabularnewline
38 & 99.99 & 99.9124 & 100.03 & -0.117556 & 0.0775556 \tabularnewline
39 & 99.69 & 99.8154 & 99.9696 & -0.154139 & -0.125444 \tabularnewline
40 & 99.85 & 99.8958 & 99.93 & -0.0342222 & -0.0457778 \tabularnewline
41 & 99.54 & 99.898 & 99.9354 & -0.0373889 & -0.358028 \tabularnewline
42 & 99.67 & 100.016 & 99.9762 & 0.0401944 & -0.346444 \tabularnewline
43 & 99.72 & 100.002 & 100.004 & -0.00247222 & -0.281694 \tabularnewline
44 & 99.74 & 100.063 & 100.022 & 0.0409444 & -0.323028 \tabularnewline
45 & 99.97 & 100.185 & 100.062 & 0.122528 & -0.214611 \tabularnewline
46 & 100.29 & 100.245 & 100.11 & 0.135028 & 0.0449722 \tabularnewline
47 & 100.57 & 100.192 & 100.17 & 0.0211111 & 0.378472 \tabularnewline
48 & 100.77 & 100.297 & 100.251 & 0.0455278 & 0.473222 \tabularnewline
49 & 100.3 & 100.275 & 100.334 & -0.0595556 & 0.0253889 \tabularnewline
50 & 100.32 & 100.294 & 100.412 & -0.117556 & 0.0258889 \tabularnewline
51 & 100.32 & 100.317 & 100.471 & -0.154139 & 0.00288889 \tabularnewline
52 & 100.37 & 100.474 & 100.508 & -0.0342222 & -0.103694 \tabularnewline
53 & 100.47 & 100.482 & 100.52 & -0.0373889 & -0.0121944 \tabularnewline
54 & 100.68 & 100.549 & 100.509 & 0.0401944 & 0.130639 \tabularnewline
55 & 100.7 & 100.51 & 100.513 & -0.00247222 & 0.189556 \tabularnewline
56 & 100.62 & 100.577 & 100.536 & 0.0409444 & 0.0428056 \tabularnewline
57 & 100.52 & 100.68 & 100.557 & 0.122528 & -0.160028 \tabularnewline
58 & 100.62 & 100.705 & 100.57 & 0.135028 & -0.0854444 \tabularnewline
59 & 100.52 & 100.591 & 100.57 & 0.0211111 & -0.0711111 \tabularnewline
60 & 100.57 & 100.605 & 100.56 & 0.0455278 & -0.0351111 \tabularnewline
61 & 100.59 & 100.48 & 100.54 & -0.0595556 & 0.109556 \tabularnewline
62 & 100.59 & 100.403 & 100.52 & -0.117556 & 0.187139 \tabularnewline
63 & 100.56 & 100.355 & 100.509 & -0.154139 & 0.204972 \tabularnewline
64 & 100.44 & 100.461 & 100.495 & -0.0342222 & -0.0207778 \tabularnewline
65 & 100.39 & 100.436 & 100.474 & -0.0373889 & -0.0463611 \tabularnewline
66 & 100.51 & 100.493 & 100.453 & 0.0401944 & 0.0168889 \tabularnewline
67 & 100.4 & NA & NA & -0.00247222 & NA \tabularnewline
68 & 100.45 & NA & NA & 0.0409444 & NA \tabularnewline
69 & 100.42 & NA & NA & 0.122528 & NA \tabularnewline
70 & 100.38 & NA & NA & 0.135028 & NA \tabularnewline
71 & 100.25 & NA & NA & 0.0211111 & NA \tabularnewline
72 & 100.34 & NA & NA & 0.0455278 & 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]100.18[/C][C]NA[/C][C]NA[/C][C]-0.0595556[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]99.73[/C][C]NA[/C][C]NA[/C][C]-0.117556[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99.69[/C][C]NA[/C][C]NA[/C][C]-0.154139[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]99.45[/C][C]NA[/C][C]NA[/C][C]-0.0342222[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]99.47[/C][C]NA[/C][C]NA[/C][C]-0.0373889[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]99.56[/C][C]NA[/C][C]NA[/C][C]0.0401944[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.54[/C][C]99.7279[/C][C]99.7304[/C][C]-0.00247222[/C][C]-0.187944[/C][/ROW]
[ROW][C]8[/C][C]99.87[/C][C]99.7659[/C][C]99.725[/C][C]0.0409444[/C][C]0.104056[/C][/ROW]
[ROW][C]9[/C][C]99.73[/C][C]99.8567[/C][C]99.7342[/C][C]0.122528[/C][C]-0.126694[/C][/ROW]
[ROW][C]10[/C][C]99.86[/C][C]99.9013[/C][C]99.7662[/C][C]0.135028[/C][C]-0.0412778[/C][/ROW]
[ROW][C]11[/C][C]99.91[/C][C]99.8399[/C][C]99.8188[/C][C]0.0211111[/C][C]0.0701389[/C][/ROW]
[ROW][C]12[/C][C]99.91[/C][C]99.9109[/C][C]99.8654[/C][C]0.0455278[/C][C]-0.000944444[/C][/ROW]
[ROW][C]13[/C][C]99.91[/C][C]99.8534[/C][C]99.9129[/C][C]-0.0595556[/C][C]0.0566389[/C][/ROW]
[ROW][C]14[/C][C]99.87[/C][C]99.8345[/C][C]99.9521[/C][C]-0.117556[/C][C]0.0354722[/C][/ROW]
[ROW][C]15[/C][C]99.77[/C][C]99.8484[/C][C]100.002[/C][C]-0.154139[/C][C]-0.0783611[/C][/ROW]
[ROW][C]16[/C][C]100.14[/C][C]100.02[/C][C]100.055[/C][C]-0.0342222[/C][C]0.119639[/C][/ROW]
[ROW][C]17[/C][C]100.04[/C][C]100.035[/C][C]100.072[/C][C]-0.0373889[/C][C]0.00530556[/C][/ROW]
[ROW][C]18[/C][C]100.11[/C][C]100.111[/C][C]100.071[/C][C]0.0401944[/C][C]-0.00102778[/C][/ROW]
[ROW][C]19[/C][C]100.13[/C][C]100.063[/C][C]100.066[/C][C]-0.00247222[/C][C]0.0666389[/C][/ROW]
[ROW][C]20[/C][C]100.22[/C][C]100.103[/C][C]100.062[/C][C]0.0409444[/C][C]0.116556[/C][/ROW]
[ROW][C]21[/C][C]100.59[/C][C]100.2[/C][C]100.077[/C][C]0.122528[/C][C]0.389972[/C][/ROW]
[ROW][C]22[/C][C]100.25[/C][C]100.237[/C][C]100.102[/C][C]0.135028[/C][C]0.0133056[/C][/ROW]
[ROW][C]23[/C][C]99.94[/C][C]100.159[/C][C]100.138[/C][C]0.0211111[/C][C]-0.219444[/C][/ROW]
[ROW][C]24[/C][C]99.85[/C][C]100.233[/C][C]100.187[/C][C]0.0455278[/C][C]-0.383028[/C][/ROW]
[ROW][C]25[/C][C]99.85[/C][C]100.169[/C][C]100.228[/C][C]-0.0595556[/C][C]-0.318778[/C][/ROW]
[ROW][C]26[/C][C]99.85[/C][C]100.143[/C][C]100.261[/C][C]-0.117556[/C][C]-0.293278[/C][/ROW]
[ROW][C]27[/C][C]100.15[/C][C]100.121[/C][C]100.275[/C][C]-0.154139[/C][C]0.0287222[/C][/ROW]
[ROW][C]28[/C][C]100.34[/C][C]100.257[/C][C]100.291[/C][C]-0.0342222[/C][C]0.0833889[/C][/ROW]
[ROW][C]29[/C][C]100.72[/C][C]100.276[/C][C]100.313[/C][C]-0.0373889[/C][C]0.444056[/C][/ROW]
[ROW][C]30[/C][C]100.61[/C][C]100.377[/C][C]100.337[/C][C]0.0401944[/C][C]0.232722[/C][/ROW]
[ROW][C]31[/C][C]100.61[/C][C]100.364[/C][C]100.366[/C][C]-0.00247222[/C][C]0.246222[/C][/ROW]
[ROW][C]32[/C][C]100.52[/C][C]100.428[/C][C]100.387[/C][C]0.0409444[/C][C]0.0923889[/C][/ROW]
[ROW][C]33[/C][C]100.64[/C][C]100.496[/C][C]100.373[/C][C]0.122528[/C][C]0.144139[/C][/ROW]
[ROW][C]34[/C][C]100.57[/C][C]100.469[/C][C]100.334[/C][C]0.135028[/C][C]0.101222[/C][/ROW]
[ROW][C]35[/C][C]100.16[/C][C]100.285[/C][C]100.264[/C][C]0.0211111[/C][C]-0.125278[/C][/ROW]
[ROW][C]36[/C][C]100.2[/C][C]100.221[/C][C]100.176[/C][C]0.0455278[/C][C]-0.0213611[/C][/ROW]
[ROW][C]37[/C][C]100.2[/C][C]100.04[/C][C]100.1[/C][C]-0.0595556[/C][C]0.159972[/C][/ROW]
[ROW][C]38[/C][C]99.99[/C][C]99.9124[/C][C]100.03[/C][C]-0.117556[/C][C]0.0775556[/C][/ROW]
[ROW][C]39[/C][C]99.69[/C][C]99.8154[/C][C]99.9696[/C][C]-0.154139[/C][C]-0.125444[/C][/ROW]
[ROW][C]40[/C][C]99.85[/C][C]99.8958[/C][C]99.93[/C][C]-0.0342222[/C][C]-0.0457778[/C][/ROW]
[ROW][C]41[/C][C]99.54[/C][C]99.898[/C][C]99.9354[/C][C]-0.0373889[/C][C]-0.358028[/C][/ROW]
[ROW][C]42[/C][C]99.67[/C][C]100.016[/C][C]99.9762[/C][C]0.0401944[/C][C]-0.346444[/C][/ROW]
[ROW][C]43[/C][C]99.72[/C][C]100.002[/C][C]100.004[/C][C]-0.00247222[/C][C]-0.281694[/C][/ROW]
[ROW][C]44[/C][C]99.74[/C][C]100.063[/C][C]100.022[/C][C]0.0409444[/C][C]-0.323028[/C][/ROW]
[ROW][C]45[/C][C]99.97[/C][C]100.185[/C][C]100.062[/C][C]0.122528[/C][C]-0.214611[/C][/ROW]
[ROW][C]46[/C][C]100.29[/C][C]100.245[/C][C]100.11[/C][C]0.135028[/C][C]0.0449722[/C][/ROW]
[ROW][C]47[/C][C]100.57[/C][C]100.192[/C][C]100.17[/C][C]0.0211111[/C][C]0.378472[/C][/ROW]
[ROW][C]48[/C][C]100.77[/C][C]100.297[/C][C]100.251[/C][C]0.0455278[/C][C]0.473222[/C][/ROW]
[ROW][C]49[/C][C]100.3[/C][C]100.275[/C][C]100.334[/C][C]-0.0595556[/C][C]0.0253889[/C][/ROW]
[ROW][C]50[/C][C]100.32[/C][C]100.294[/C][C]100.412[/C][C]-0.117556[/C][C]0.0258889[/C][/ROW]
[ROW][C]51[/C][C]100.32[/C][C]100.317[/C][C]100.471[/C][C]-0.154139[/C][C]0.00288889[/C][/ROW]
[ROW][C]52[/C][C]100.37[/C][C]100.474[/C][C]100.508[/C][C]-0.0342222[/C][C]-0.103694[/C][/ROW]
[ROW][C]53[/C][C]100.47[/C][C]100.482[/C][C]100.52[/C][C]-0.0373889[/C][C]-0.0121944[/C][/ROW]
[ROW][C]54[/C][C]100.68[/C][C]100.549[/C][C]100.509[/C][C]0.0401944[/C][C]0.130639[/C][/ROW]
[ROW][C]55[/C][C]100.7[/C][C]100.51[/C][C]100.513[/C][C]-0.00247222[/C][C]0.189556[/C][/ROW]
[ROW][C]56[/C][C]100.62[/C][C]100.577[/C][C]100.536[/C][C]0.0409444[/C][C]0.0428056[/C][/ROW]
[ROW][C]57[/C][C]100.52[/C][C]100.68[/C][C]100.557[/C][C]0.122528[/C][C]-0.160028[/C][/ROW]
[ROW][C]58[/C][C]100.62[/C][C]100.705[/C][C]100.57[/C][C]0.135028[/C][C]-0.0854444[/C][/ROW]
[ROW][C]59[/C][C]100.52[/C][C]100.591[/C][C]100.57[/C][C]0.0211111[/C][C]-0.0711111[/C][/ROW]
[ROW][C]60[/C][C]100.57[/C][C]100.605[/C][C]100.56[/C][C]0.0455278[/C][C]-0.0351111[/C][/ROW]
[ROW][C]61[/C][C]100.59[/C][C]100.48[/C][C]100.54[/C][C]-0.0595556[/C][C]0.109556[/C][/ROW]
[ROW][C]62[/C][C]100.59[/C][C]100.403[/C][C]100.52[/C][C]-0.117556[/C][C]0.187139[/C][/ROW]
[ROW][C]63[/C][C]100.56[/C][C]100.355[/C][C]100.509[/C][C]-0.154139[/C][C]0.204972[/C][/ROW]
[ROW][C]64[/C][C]100.44[/C][C]100.461[/C][C]100.495[/C][C]-0.0342222[/C][C]-0.0207778[/C][/ROW]
[ROW][C]65[/C][C]100.39[/C][C]100.436[/C][C]100.474[/C][C]-0.0373889[/C][C]-0.0463611[/C][/ROW]
[ROW][C]66[/C][C]100.51[/C][C]100.493[/C][C]100.453[/C][C]0.0401944[/C][C]0.0168889[/C][/ROW]
[ROW][C]67[/C][C]100.4[/C][C]NA[/C][C]NA[/C][C]-0.00247222[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]100.45[/C][C]NA[/C][C]NA[/C][C]0.0409444[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.42[/C][C]NA[/C][C]NA[/C][C]0.122528[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]100.38[/C][C]NA[/C][C]NA[/C][C]0.135028[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]100.25[/C][C]NA[/C][C]NA[/C][C]0.0211111[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]100.34[/C][C]NA[/C][C]NA[/C][C]0.0455278[/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	100.18	NA	NA	-0.0595556	NA
2	99.73	NA	NA	-0.117556	NA
3	99.69	NA	NA	-0.154139	NA
4	99.45	NA	NA	-0.0342222	NA
5	99.47	NA	NA	-0.0373889	NA
6	99.56	NA	NA	0.0401944	NA
7	99.54	99.7279	99.7304	-0.00247222	-0.187944
8	99.87	99.7659	99.725	0.0409444	0.104056
9	99.73	99.8567	99.7342	0.122528	-0.126694
10	99.86	99.9013	99.7662	0.135028	-0.0412778
11	99.91	99.8399	99.8188	0.0211111	0.0701389
12	99.91	99.9109	99.8654	0.0455278	-0.000944444
13	99.91	99.8534	99.9129	-0.0595556	0.0566389
14	99.87	99.8345	99.9521	-0.117556	0.0354722
15	99.77	99.8484	100.002	-0.154139	-0.0783611
16	100.14	100.02	100.055	-0.0342222	0.119639
17	100.04	100.035	100.072	-0.0373889	0.00530556
18	100.11	100.111	100.071	0.0401944	-0.00102778
19	100.13	100.063	100.066	-0.00247222	0.0666389
20	100.22	100.103	100.062	0.0409444	0.116556
21	100.59	100.2	100.077	0.122528	0.389972
22	100.25	100.237	100.102	0.135028	0.0133056
23	99.94	100.159	100.138	0.0211111	-0.219444
24	99.85	100.233	100.187	0.0455278	-0.383028
25	99.85	100.169	100.228	-0.0595556	-0.318778
26	99.85	100.143	100.261	-0.117556	-0.293278
27	100.15	100.121	100.275	-0.154139	0.0287222
28	100.34	100.257	100.291	-0.0342222	0.0833889
29	100.72	100.276	100.313	-0.0373889	0.444056
30	100.61	100.377	100.337	0.0401944	0.232722
31	100.61	100.364	100.366	-0.00247222	0.246222
32	100.52	100.428	100.387	0.0409444	0.0923889
33	100.64	100.496	100.373	0.122528	0.144139
34	100.57	100.469	100.334	0.135028	0.101222
35	100.16	100.285	100.264	0.0211111	-0.125278
36	100.2	100.221	100.176	0.0455278	-0.0213611
37	100.2	100.04	100.1	-0.0595556	0.159972
38	99.99	99.9124	100.03	-0.117556	0.0775556
39	99.69	99.8154	99.9696	-0.154139	-0.125444
40	99.85	99.8958	99.93	-0.0342222	-0.0457778
41	99.54	99.898	99.9354	-0.0373889	-0.358028
42	99.67	100.016	99.9762	0.0401944	-0.346444
43	99.72	100.002	100.004	-0.00247222	-0.281694
44	99.74	100.063	100.022	0.0409444	-0.323028
45	99.97	100.185	100.062	0.122528	-0.214611
46	100.29	100.245	100.11	0.135028	0.0449722
47	100.57	100.192	100.17	0.0211111	0.378472
48	100.77	100.297	100.251	0.0455278	0.473222
49	100.3	100.275	100.334	-0.0595556	0.0253889
50	100.32	100.294	100.412	-0.117556	0.0258889
51	100.32	100.317	100.471	-0.154139	0.00288889
52	100.37	100.474	100.508	-0.0342222	-0.103694
53	100.47	100.482	100.52	-0.0373889	-0.0121944
54	100.68	100.549	100.509	0.0401944	0.130639
55	100.7	100.51	100.513	-0.00247222	0.189556
56	100.62	100.577	100.536	0.0409444	0.0428056
57	100.52	100.68	100.557	0.122528	-0.160028
58	100.62	100.705	100.57	0.135028	-0.0854444
59	100.52	100.591	100.57	0.0211111	-0.0711111
60	100.57	100.605	100.56	0.0455278	-0.0351111
61	100.59	100.48	100.54	-0.0595556	0.109556
62	100.59	100.403	100.52	-0.117556	0.187139
63	100.56	100.355	100.509	-0.154139	0.204972
64	100.44	100.461	100.495	-0.0342222	-0.0207778
65	100.39	100.436	100.474	-0.0373889	-0.0463611
66	100.51	100.493	100.453	0.0401944	0.0168889
67	100.4	NA	NA	-0.00247222	NA
68	100.45	NA	NA	0.0409444	NA
69	100.42	NA	NA	0.122528	NA
70	100.38	NA	NA	0.135028	NA
71	100.25	NA	NA	0.0211111	NA
72	100.34	NA	NA	0.0455278	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