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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 28 Apr 2017 17:04:19 +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/28/t1493395685bennj66g1jwjfew.htm/, Retrieved Fri, 10 May 2024 12:50:09 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 10 May 2024 12:50:09 +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	4 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.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	4 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	92.61	NA	NA	0.55916	NA
2	92.19	NA	NA	0.188993	NA
3	92.68	NA	NA	0.35066	NA
4	92.66	NA	NA	0.14041	NA
5	92.77	NA	NA	0.238826	NA
6	92.21	NA	NA	0.0274097	NA
7	92.58	92.6397	93.1112	-0.471507	-0.0597431
8	91.9	92.4412	93.2896	-0.848424	-0.54116
9	93.81	93.284	93.5154	-0.231424	0.526007
10	94.05	93.9069	93.7696	0.137326	0.14309
11	94.51	94.087	94.035	0.0519931	0.423007
12	94.49	94.1849	94.3283	-0.143424	0.30509
13	94.36	95.1842	94.625	0.55916	-0.82416
14	94.72	95.1223	94.9333	0.188993	-0.402326
15	95.57	95.594	95.2433	0.35066	-0.0239931
16	95.87	95.6712	95.5308	0.14041	0.198757
17	95.93	96.088	95.8492	0.238826	-0.157993
18	96.09	96.1953	96.1679	0.0274097	-0.105326
19	95.82	96.0343	96.5058	-0.471507	-0.214326
20	96.06	96.0216	96.87	-0.848424	0.0384236
21	97.09	97.0023	97.2337	-0.231424	0.0876736
22	97.67	97.7073	97.57	0.137326	-0.0373264
23	98.53	97.9349	97.8829	0.0519931	0.59509
24	98.12	98.0453	98.1887	-0.143424	0.0746736
25	98.84	99.0571	98.4979	0.55916	-0.217076
26	98.98	98.9986	98.8096	0.188993	-0.0185764
27	100.04	99.4357	99.085	0.35066	0.60434
28	99.47	99.5125	99.3721	0.14041	-0.0424931
29	99.84	99.8709	99.6321	0.238826	-0.0309097
30	99.52	99.8957	99.8683	0.0274097	-0.375743
31	99.81	99.6552	100.127	-0.471507	0.15484
32	99.55	99.5212	100.37	-0.848424	0.0288403
33	100.21	100.331	100.562	-0.231424	-0.12066
34	101.44	100.887	100.75	0.137326	0.55309
35	101	101.003	100.951	0.0519931	-0.00324306
36	101.32	100.992	101.135	-0.143424	0.328424
37	101.84	101.867	101.308	0.55916	-0.0274931
38	101.81	101.674	101.485	0.188993	0.136007
39	101.83	102.02	101.669	0.35066	-0.189826
40	102.18	101.949	101.809	0.14041	0.23084
41	101.97	102.168	101.93	0.238826	-0.19841
42	101.8	102.089	102.062	0.0274097	-0.289493
43	101.69	101.701	102.173	-0.471507	-0.0114097
44	101.91	101.42	102.268	-0.848424	0.49009
45	102.27	102.116	102.348	-0.231424	0.153507
46	102.73	102.552	102.415	0.137326	0.177674
47	102.61	102.577	102.525	0.0519931	0.0325903
48	102.89	102.539	102.683	-0.143424	0.350507
49	102.93	103.41	102.851	0.55916	-0.479993
50	103.01	103.192	103.003	0.188993	-0.182326
51	102.54	103.493	103.142	0.35066	-0.95316
52	103.08	103.427	103.287	0.14041	-0.347493
53	103.72	103.683	103.444	0.238826	0.0374236
54	103.83	103.631	103.603	0.0274097	0.199257
55	103.69	103.437	103.909	-0.471507	0.252757
56	103.57	103.464	104.312	-0.848424	0.105924
57	103.95	104.474	104.706	-0.231424	-0.52441
58	104.52	105.234	105.097	0.137326	-0.71441
59	104.58	105.505	105.453	0.0519931	-0.925326
60	104.75	105.687	105.83	-0.143424	-0.936576
61	108.4	106.729	106.17	0.55916	1.67084
62	107.23	106.641	106.452	0.188993	0.58934
63	107.76	107.075	106.725	0.35066	0.684757
64	107.25	107.167	107.027	0.14041	0.0825069
65	108.1	107.628	107.389	0.238826	0.472007
66	108.49	107.797	107.769	0.0274097	0.693424
67	107.19	NA	NA	-0.471507	NA
68	106.83	NA	NA	-0.848424	NA
69	107.24	NA	NA	-0.231424	NA
70	108.49	NA	NA	0.137326	NA
71	109.3	NA	NA	0.0519931	NA
72	109.15	NA	NA	-0.143424	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 92.61 & NA & NA & 0.55916 & NA \tabularnewline
2 & 92.19 & NA & NA & 0.188993 & NA \tabularnewline
3 & 92.68 & NA & NA & 0.35066 & NA \tabularnewline
4 & 92.66 & NA & NA & 0.14041 & NA \tabularnewline
5 & 92.77 & NA & NA & 0.238826 & NA \tabularnewline
6 & 92.21 & NA & NA & 0.0274097 & NA \tabularnewline
7 & 92.58 & 92.6397 & 93.1112 & -0.471507 & -0.0597431 \tabularnewline
8 & 91.9 & 92.4412 & 93.2896 & -0.848424 & -0.54116 \tabularnewline
9 & 93.81 & 93.284 & 93.5154 & -0.231424 & 0.526007 \tabularnewline
10 & 94.05 & 93.9069 & 93.7696 & 0.137326 & 0.14309 \tabularnewline
11 & 94.51 & 94.087 & 94.035 & 0.0519931 & 0.423007 \tabularnewline
12 & 94.49 & 94.1849 & 94.3283 & -0.143424 & 0.30509 \tabularnewline
13 & 94.36 & 95.1842 & 94.625 & 0.55916 & -0.82416 \tabularnewline
14 & 94.72 & 95.1223 & 94.9333 & 0.188993 & -0.402326 \tabularnewline
15 & 95.57 & 95.594 & 95.2433 & 0.35066 & -0.0239931 \tabularnewline
16 & 95.87 & 95.6712 & 95.5308 & 0.14041 & 0.198757 \tabularnewline
17 & 95.93 & 96.088 & 95.8492 & 0.238826 & -0.157993 \tabularnewline
18 & 96.09 & 96.1953 & 96.1679 & 0.0274097 & -0.105326 \tabularnewline
19 & 95.82 & 96.0343 & 96.5058 & -0.471507 & -0.214326 \tabularnewline
20 & 96.06 & 96.0216 & 96.87 & -0.848424 & 0.0384236 \tabularnewline
21 & 97.09 & 97.0023 & 97.2337 & -0.231424 & 0.0876736 \tabularnewline
22 & 97.67 & 97.7073 & 97.57 & 0.137326 & -0.0373264 \tabularnewline
23 & 98.53 & 97.9349 & 97.8829 & 0.0519931 & 0.59509 \tabularnewline
24 & 98.12 & 98.0453 & 98.1887 & -0.143424 & 0.0746736 \tabularnewline
25 & 98.84 & 99.0571 & 98.4979 & 0.55916 & -0.217076 \tabularnewline
26 & 98.98 & 98.9986 & 98.8096 & 0.188993 & -0.0185764 \tabularnewline
27 & 100.04 & 99.4357 & 99.085 & 0.35066 & 0.60434 \tabularnewline
28 & 99.47 & 99.5125 & 99.3721 & 0.14041 & -0.0424931 \tabularnewline
29 & 99.84 & 99.8709 & 99.6321 & 0.238826 & -0.0309097 \tabularnewline
30 & 99.52 & 99.8957 & 99.8683 & 0.0274097 & -0.375743 \tabularnewline
31 & 99.81 & 99.6552 & 100.127 & -0.471507 & 0.15484 \tabularnewline
32 & 99.55 & 99.5212 & 100.37 & -0.848424 & 0.0288403 \tabularnewline
33 & 100.21 & 100.331 & 100.562 & -0.231424 & -0.12066 \tabularnewline
34 & 101.44 & 100.887 & 100.75 & 0.137326 & 0.55309 \tabularnewline
35 & 101 & 101.003 & 100.951 & 0.0519931 & -0.00324306 \tabularnewline
36 & 101.32 & 100.992 & 101.135 & -0.143424 & 0.328424 \tabularnewline
37 & 101.84 & 101.867 & 101.308 & 0.55916 & -0.0274931 \tabularnewline
38 & 101.81 & 101.674 & 101.485 & 0.188993 & 0.136007 \tabularnewline
39 & 101.83 & 102.02 & 101.669 & 0.35066 & -0.189826 \tabularnewline
40 & 102.18 & 101.949 & 101.809 & 0.14041 & 0.23084 \tabularnewline
41 & 101.97 & 102.168 & 101.93 & 0.238826 & -0.19841 \tabularnewline
42 & 101.8 & 102.089 & 102.062 & 0.0274097 & -0.289493 \tabularnewline
43 & 101.69 & 101.701 & 102.173 & -0.471507 & -0.0114097 \tabularnewline
44 & 101.91 & 101.42 & 102.268 & -0.848424 & 0.49009 \tabularnewline
45 & 102.27 & 102.116 & 102.348 & -0.231424 & 0.153507 \tabularnewline
46 & 102.73 & 102.552 & 102.415 & 0.137326 & 0.177674 \tabularnewline
47 & 102.61 & 102.577 & 102.525 & 0.0519931 & 0.0325903 \tabularnewline
48 & 102.89 & 102.539 & 102.683 & -0.143424 & 0.350507 \tabularnewline
49 & 102.93 & 103.41 & 102.851 & 0.55916 & -0.479993 \tabularnewline
50 & 103.01 & 103.192 & 103.003 & 0.188993 & -0.182326 \tabularnewline
51 & 102.54 & 103.493 & 103.142 & 0.35066 & -0.95316 \tabularnewline
52 & 103.08 & 103.427 & 103.287 & 0.14041 & -0.347493 \tabularnewline
53 & 103.72 & 103.683 & 103.444 & 0.238826 & 0.0374236 \tabularnewline
54 & 103.83 & 103.631 & 103.603 & 0.0274097 & 0.199257 \tabularnewline
55 & 103.69 & 103.437 & 103.909 & -0.471507 & 0.252757 \tabularnewline
56 & 103.57 & 103.464 & 104.312 & -0.848424 & 0.105924 \tabularnewline
57 & 103.95 & 104.474 & 104.706 & -0.231424 & -0.52441 \tabularnewline
58 & 104.52 & 105.234 & 105.097 & 0.137326 & -0.71441 \tabularnewline
59 & 104.58 & 105.505 & 105.453 & 0.0519931 & -0.925326 \tabularnewline
60 & 104.75 & 105.687 & 105.83 & -0.143424 & -0.936576 \tabularnewline
61 & 108.4 & 106.729 & 106.17 & 0.55916 & 1.67084 \tabularnewline
62 & 107.23 & 106.641 & 106.452 & 0.188993 & 0.58934 \tabularnewline
63 & 107.76 & 107.075 & 106.725 & 0.35066 & 0.684757 \tabularnewline
64 & 107.25 & 107.167 & 107.027 & 0.14041 & 0.0825069 \tabularnewline
65 & 108.1 & 107.628 & 107.389 & 0.238826 & 0.472007 \tabularnewline
66 & 108.49 & 107.797 & 107.769 & 0.0274097 & 0.693424 \tabularnewline
67 & 107.19 & NA & NA & -0.471507 & NA \tabularnewline
68 & 106.83 & NA & NA & -0.848424 & NA \tabularnewline
69 & 107.24 & NA & NA & -0.231424 & NA \tabularnewline
70 & 108.49 & NA & NA & 0.137326 & NA \tabularnewline
71 & 109.3 & NA & NA & 0.0519931 & NA \tabularnewline
72 & 109.15 & NA & NA & -0.143424 & 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]92.61[/C][C]NA[/C][C]NA[/C][C]0.55916[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]92.19[/C][C]NA[/C][C]NA[/C][C]0.188993[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]92.68[/C][C]NA[/C][C]NA[/C][C]0.35066[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]92.66[/C][C]NA[/C][C]NA[/C][C]0.14041[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.77[/C][C]NA[/C][C]NA[/C][C]0.238826[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.21[/C][C]NA[/C][C]NA[/C][C]0.0274097[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]92.58[/C][C]92.6397[/C][C]93.1112[/C][C]-0.471507[/C][C]-0.0597431[/C][/ROW]
[ROW][C]8[/C][C]91.9[/C][C]92.4412[/C][C]93.2896[/C][C]-0.848424[/C][C]-0.54116[/C][/ROW]
[ROW][C]9[/C][C]93.81[/C][C]93.284[/C][C]93.5154[/C][C]-0.231424[/C][C]0.526007[/C][/ROW]
[ROW][C]10[/C][C]94.05[/C][C]93.9069[/C][C]93.7696[/C][C]0.137326[/C][C]0.14309[/C][/ROW]
[ROW][C]11[/C][C]94.51[/C][C]94.087[/C][C]94.035[/C][C]0.0519931[/C][C]0.423007[/C][/ROW]
[ROW][C]12[/C][C]94.49[/C][C]94.1849[/C][C]94.3283[/C][C]-0.143424[/C][C]0.30509[/C][/ROW]
[ROW][C]13[/C][C]94.36[/C][C]95.1842[/C][C]94.625[/C][C]0.55916[/C][C]-0.82416[/C][/ROW]
[ROW][C]14[/C][C]94.72[/C][C]95.1223[/C][C]94.9333[/C][C]0.188993[/C][C]-0.402326[/C][/ROW]
[ROW][C]15[/C][C]95.57[/C][C]95.594[/C][C]95.2433[/C][C]0.35066[/C][C]-0.0239931[/C][/ROW]
[ROW][C]16[/C][C]95.87[/C][C]95.6712[/C][C]95.5308[/C][C]0.14041[/C][C]0.198757[/C][/ROW]
[ROW][C]17[/C][C]95.93[/C][C]96.088[/C][C]95.8492[/C][C]0.238826[/C][C]-0.157993[/C][/ROW]
[ROW][C]18[/C][C]96.09[/C][C]96.1953[/C][C]96.1679[/C][C]0.0274097[/C][C]-0.105326[/C][/ROW]
[ROW][C]19[/C][C]95.82[/C][C]96.0343[/C][C]96.5058[/C][C]-0.471507[/C][C]-0.214326[/C][/ROW]
[ROW][C]20[/C][C]96.06[/C][C]96.0216[/C][C]96.87[/C][C]-0.848424[/C][C]0.0384236[/C][/ROW]
[ROW][C]21[/C][C]97.09[/C][C]97.0023[/C][C]97.2337[/C][C]-0.231424[/C][C]0.0876736[/C][/ROW]
[ROW][C]22[/C][C]97.67[/C][C]97.7073[/C][C]97.57[/C][C]0.137326[/C][C]-0.0373264[/C][/ROW]
[ROW][C]23[/C][C]98.53[/C][C]97.9349[/C][C]97.8829[/C][C]0.0519931[/C][C]0.59509[/C][/ROW]
[ROW][C]24[/C][C]98.12[/C][C]98.0453[/C][C]98.1887[/C][C]-0.143424[/C][C]0.0746736[/C][/ROW]
[ROW][C]25[/C][C]98.84[/C][C]99.0571[/C][C]98.4979[/C][C]0.55916[/C][C]-0.217076[/C][/ROW]
[ROW][C]26[/C][C]98.98[/C][C]98.9986[/C][C]98.8096[/C][C]0.188993[/C][C]-0.0185764[/C][/ROW]
[ROW][C]27[/C][C]100.04[/C][C]99.4357[/C][C]99.085[/C][C]0.35066[/C][C]0.60434[/C][/ROW]
[ROW][C]28[/C][C]99.47[/C][C]99.5125[/C][C]99.3721[/C][C]0.14041[/C][C]-0.0424931[/C][/ROW]
[ROW][C]29[/C][C]99.84[/C][C]99.8709[/C][C]99.6321[/C][C]0.238826[/C][C]-0.0309097[/C][/ROW]
[ROW][C]30[/C][C]99.52[/C][C]99.8957[/C][C]99.8683[/C][C]0.0274097[/C][C]-0.375743[/C][/ROW]
[ROW][C]31[/C][C]99.81[/C][C]99.6552[/C][C]100.127[/C][C]-0.471507[/C][C]0.15484[/C][/ROW]
[ROW][C]32[/C][C]99.55[/C][C]99.5212[/C][C]100.37[/C][C]-0.848424[/C][C]0.0288403[/C][/ROW]
[ROW][C]33[/C][C]100.21[/C][C]100.331[/C][C]100.562[/C][C]-0.231424[/C][C]-0.12066[/C][/ROW]
[ROW][C]34[/C][C]101.44[/C][C]100.887[/C][C]100.75[/C][C]0.137326[/C][C]0.55309[/C][/ROW]
[ROW][C]35[/C][C]101[/C][C]101.003[/C][C]100.951[/C][C]0.0519931[/C][C]-0.00324306[/C][/ROW]
[ROW][C]36[/C][C]101.32[/C][C]100.992[/C][C]101.135[/C][C]-0.143424[/C][C]0.328424[/C][/ROW]
[ROW][C]37[/C][C]101.84[/C][C]101.867[/C][C]101.308[/C][C]0.55916[/C][C]-0.0274931[/C][/ROW]
[ROW][C]38[/C][C]101.81[/C][C]101.674[/C][C]101.485[/C][C]0.188993[/C][C]0.136007[/C][/ROW]
[ROW][C]39[/C][C]101.83[/C][C]102.02[/C][C]101.669[/C][C]0.35066[/C][C]-0.189826[/C][/ROW]
[ROW][C]40[/C][C]102.18[/C][C]101.949[/C][C]101.809[/C][C]0.14041[/C][C]0.23084[/C][/ROW]
[ROW][C]41[/C][C]101.97[/C][C]102.168[/C][C]101.93[/C][C]0.238826[/C][C]-0.19841[/C][/ROW]
[ROW][C]42[/C][C]101.8[/C][C]102.089[/C][C]102.062[/C][C]0.0274097[/C][C]-0.289493[/C][/ROW]
[ROW][C]43[/C][C]101.69[/C][C]101.701[/C][C]102.173[/C][C]-0.471507[/C][C]-0.0114097[/C][/ROW]
[ROW][C]44[/C][C]101.91[/C][C]101.42[/C][C]102.268[/C][C]-0.848424[/C][C]0.49009[/C][/ROW]
[ROW][C]45[/C][C]102.27[/C][C]102.116[/C][C]102.348[/C][C]-0.231424[/C][C]0.153507[/C][/ROW]
[ROW][C]46[/C][C]102.73[/C][C]102.552[/C][C]102.415[/C][C]0.137326[/C][C]0.177674[/C][/ROW]
[ROW][C]47[/C][C]102.61[/C][C]102.577[/C][C]102.525[/C][C]0.0519931[/C][C]0.0325903[/C][/ROW]
[ROW][C]48[/C][C]102.89[/C][C]102.539[/C][C]102.683[/C][C]-0.143424[/C][C]0.350507[/C][/ROW]
[ROW][C]49[/C][C]102.93[/C][C]103.41[/C][C]102.851[/C][C]0.55916[/C][C]-0.479993[/C][/ROW]
[ROW][C]50[/C][C]103.01[/C][C]103.192[/C][C]103.003[/C][C]0.188993[/C][C]-0.182326[/C][/ROW]
[ROW][C]51[/C][C]102.54[/C][C]103.493[/C][C]103.142[/C][C]0.35066[/C][C]-0.95316[/C][/ROW]
[ROW][C]52[/C][C]103.08[/C][C]103.427[/C][C]103.287[/C][C]0.14041[/C][C]-0.347493[/C][/ROW]
[ROW][C]53[/C][C]103.72[/C][C]103.683[/C][C]103.444[/C][C]0.238826[/C][C]0.0374236[/C][/ROW]
[ROW][C]54[/C][C]103.83[/C][C]103.631[/C][C]103.603[/C][C]0.0274097[/C][C]0.199257[/C][/ROW]
[ROW][C]55[/C][C]103.69[/C][C]103.437[/C][C]103.909[/C][C]-0.471507[/C][C]0.252757[/C][/ROW]
[ROW][C]56[/C][C]103.57[/C][C]103.464[/C][C]104.312[/C][C]-0.848424[/C][C]0.105924[/C][/ROW]
[ROW][C]57[/C][C]103.95[/C][C]104.474[/C][C]104.706[/C][C]-0.231424[/C][C]-0.52441[/C][/ROW]
[ROW][C]58[/C][C]104.52[/C][C]105.234[/C][C]105.097[/C][C]0.137326[/C][C]-0.71441[/C][/ROW]
[ROW][C]59[/C][C]104.58[/C][C]105.505[/C][C]105.453[/C][C]0.0519931[/C][C]-0.925326[/C][/ROW]
[ROW][C]60[/C][C]104.75[/C][C]105.687[/C][C]105.83[/C][C]-0.143424[/C][C]-0.936576[/C][/ROW]
[ROW][C]61[/C][C]108.4[/C][C]106.729[/C][C]106.17[/C][C]0.55916[/C][C]1.67084[/C][/ROW]
[ROW][C]62[/C][C]107.23[/C][C]106.641[/C][C]106.452[/C][C]0.188993[/C][C]0.58934[/C][/ROW]
[ROW][C]63[/C][C]107.76[/C][C]107.075[/C][C]106.725[/C][C]0.35066[/C][C]0.684757[/C][/ROW]
[ROW][C]64[/C][C]107.25[/C][C]107.167[/C][C]107.027[/C][C]0.14041[/C][C]0.0825069[/C][/ROW]
[ROW][C]65[/C][C]108.1[/C][C]107.628[/C][C]107.389[/C][C]0.238826[/C][C]0.472007[/C][/ROW]
[ROW][C]66[/C][C]108.49[/C][C]107.797[/C][C]107.769[/C][C]0.0274097[/C][C]0.693424[/C][/ROW]
[ROW][C]67[/C][C]107.19[/C][C]NA[/C][C]NA[/C][C]-0.471507[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]106.83[/C][C]NA[/C][C]NA[/C][C]-0.848424[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]107.24[/C][C]NA[/C][C]NA[/C][C]-0.231424[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]108.49[/C][C]NA[/C][C]NA[/C][C]0.137326[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]109.3[/C][C]NA[/C][C]NA[/C][C]0.0519931[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]109.15[/C][C]NA[/C][C]NA[/C][C]-0.143424[/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	92.61	NA	NA	0.55916	NA
2	92.19	NA	NA	0.188993	NA
3	92.68	NA	NA	0.35066	NA
4	92.66	NA	NA	0.14041	NA
5	92.77	NA	NA	0.238826	NA
6	92.21	NA	NA	0.0274097	NA
7	92.58	92.6397	93.1112	-0.471507	-0.0597431
8	91.9	92.4412	93.2896	-0.848424	-0.54116
9	93.81	93.284	93.5154	-0.231424	0.526007
10	94.05	93.9069	93.7696	0.137326	0.14309
11	94.51	94.087	94.035	0.0519931	0.423007
12	94.49	94.1849	94.3283	-0.143424	0.30509
13	94.36	95.1842	94.625	0.55916	-0.82416
14	94.72	95.1223	94.9333	0.188993	-0.402326
15	95.57	95.594	95.2433	0.35066	-0.0239931
16	95.87	95.6712	95.5308	0.14041	0.198757
17	95.93	96.088	95.8492	0.238826	-0.157993
18	96.09	96.1953	96.1679	0.0274097	-0.105326
19	95.82	96.0343	96.5058	-0.471507	-0.214326
20	96.06	96.0216	96.87	-0.848424	0.0384236
21	97.09	97.0023	97.2337	-0.231424	0.0876736
22	97.67	97.7073	97.57	0.137326	-0.0373264
23	98.53	97.9349	97.8829	0.0519931	0.59509
24	98.12	98.0453	98.1887	-0.143424	0.0746736
25	98.84	99.0571	98.4979	0.55916	-0.217076
26	98.98	98.9986	98.8096	0.188993	-0.0185764
27	100.04	99.4357	99.085	0.35066	0.60434
28	99.47	99.5125	99.3721	0.14041	-0.0424931
29	99.84	99.8709	99.6321	0.238826	-0.0309097
30	99.52	99.8957	99.8683	0.0274097	-0.375743
31	99.81	99.6552	100.127	-0.471507	0.15484
32	99.55	99.5212	100.37	-0.848424	0.0288403
33	100.21	100.331	100.562	-0.231424	-0.12066
34	101.44	100.887	100.75	0.137326	0.55309
35	101	101.003	100.951	0.0519931	-0.00324306
36	101.32	100.992	101.135	-0.143424	0.328424
37	101.84	101.867	101.308	0.55916	-0.0274931
38	101.81	101.674	101.485	0.188993	0.136007
39	101.83	102.02	101.669	0.35066	-0.189826
40	102.18	101.949	101.809	0.14041	0.23084
41	101.97	102.168	101.93	0.238826	-0.19841
42	101.8	102.089	102.062	0.0274097	-0.289493
43	101.69	101.701	102.173	-0.471507	-0.0114097
44	101.91	101.42	102.268	-0.848424	0.49009
45	102.27	102.116	102.348	-0.231424	0.153507
46	102.73	102.552	102.415	0.137326	0.177674
47	102.61	102.577	102.525	0.0519931	0.0325903
48	102.89	102.539	102.683	-0.143424	0.350507
49	102.93	103.41	102.851	0.55916	-0.479993
50	103.01	103.192	103.003	0.188993	-0.182326
51	102.54	103.493	103.142	0.35066	-0.95316
52	103.08	103.427	103.287	0.14041	-0.347493
53	103.72	103.683	103.444	0.238826	0.0374236
54	103.83	103.631	103.603	0.0274097	0.199257
55	103.69	103.437	103.909	-0.471507	0.252757
56	103.57	103.464	104.312	-0.848424	0.105924
57	103.95	104.474	104.706	-0.231424	-0.52441
58	104.52	105.234	105.097	0.137326	-0.71441
59	104.58	105.505	105.453	0.0519931	-0.925326
60	104.75	105.687	105.83	-0.143424	-0.936576
61	108.4	106.729	106.17	0.55916	1.67084
62	107.23	106.641	106.452	0.188993	0.58934
63	107.76	107.075	106.725	0.35066	0.684757
64	107.25	107.167	107.027	0.14041	0.0825069
65	108.1	107.628	107.389	0.238826	0.472007
66	108.49	107.797	107.769	0.0274097	0.693424
67	107.19	NA	NA	-0.471507	NA
68	106.83	NA	NA	-0.848424	NA
69	107.24	NA	NA	-0.231424	NA
70	108.49	NA	NA	0.137326	NA
71	109.3	NA	NA	0.0519931	NA
72	109.15	NA	NA	-0.143424	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