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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 23 Dec 2013 12:05:57 -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/2013/Dec/23/t13878183797krd8iae0y5cfu0.htm/, Retrieved Tue, 16 Apr 2024 20:17:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232601, Retrieved Tue, 16 Apr 2024 20:17:32 +0000

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No (this computation is public)

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Estimated Impact

134

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

-       [Classical Decomposition] [] [2013-12-23 17:05:57] [4a6145c727f9c0eb5ad6c1d4f2919b3e] [Current]
- R PD    [Classical Decomposition] [] [2014-01-12 23:52:48] [ed8109c700ca2a37c253822187bef503] 

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Dataseries X:

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1,94
1,82
1,8
1,79
1,79
1,78
1,81
1,84
1,87
1,87
1,87
1,84
1,82
1,83
1,83
1,82
1,83
1,87
1,88
1,9
1,98
2,03
2,14
2,42
2,73
2,84
2,85
2,94
3,06
3,24
3,18
3,01
2,87
2,73
2,63
2,39
2,26
2,11
2,01
1,99
1,96
1,93
1,98
2,07
2,24
2,31
2,23
2,26
2,28
2,3
2,33
2,26
2,24
2,47
2,55
2,89
3,21
3,21
2,92
2,68
2,4
2,28
2,24
2,2
2,18
2,23
2,24
2,25
2,23
2,25
2,23
2,21
2,17
2,17
2,13
2,12
2,13
2,17
2,33
2,5
2,57
2,59
2,58
2,31

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232601&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232601&T=0

As an alternative you can also use a QR Code:

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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.94	NA	NA	-0.0188368	NA
2	1.82	NA	NA	-0.0486979	NA
3	1.8	NA	NA	-0.0814757	NA
4	1.79	NA	NA	-0.101337	NA
5	1.79	NA	NA	-0.0996007	NA
6	1.78	NA	NA	-0.0227951	NA
7	1.81	1.8372	1.83	0.00720486	-0.0272049
8	1.84	1.88193	1.82542	0.0565104	-0.0419271
9	1.87	1.9522	1.82708	0.125122	-0.0822049
10	1.87	1.95012	1.82958	0.120538	-0.0801215
11	1.87	1.88505	1.8325	0.0525521	-0.0150521
12	1.84	1.84873	1.83792	0.010816	-0.00873264
13	1.82	1.82575	1.84458	-0.0188368	-0.00574653
14	1.83	1.8013	1.85	-0.0486979	0.0286979
15	1.83	1.77561	1.85708	-0.0814757	0.0543924
16	1.82	1.767	1.86833	-0.101337	0.0530035
17	1.83	1.78665	1.88625	-0.0996007	0.0433507
18	1.87	1.89887	1.92167	-0.0227951	-0.0288715
19	1.88	1.99095	1.98375	0.00720486	-0.110955
20	1.9	2.12026	2.06375	0.0565104	-0.22026
21	1.98	2.27345	2.14833	0.125122	-0.293455
22	2.03	2.35804	2.2375	0.120538	-0.328038
23	2.14	2.38797	2.33542	0.0525521	-0.247969
24	2.42	2.45457	2.44375	0.010816	-0.034566
25	2.73	2.53616	2.555	-0.0188368	0.193837
26	2.84	2.60672	2.65542	-0.0486979	0.233281
27	2.85	2.65727	2.73875	-0.0814757	0.192726
28	2.94	2.70366	2.805	-0.101337	0.236337
29	3.06	2.75498	2.85458	-0.0996007	0.305017
30	3.24	2.85095	2.87375	-0.0227951	0.389045
31	3.18	2.86012	2.85292	0.00720486	0.319878
32	3.01	2.85943	2.80292	0.0565104	0.150573
33	2.87	2.86262	2.7375	0.125122	0.00737847
34	2.73	2.78345	2.66292	0.120538	-0.0534549
35	2.63	2.63005	2.5775	0.0525521	-5.20833e-05
36	2.39	2.4879	2.47708	0.010816	-0.0978993
37	2.26	2.35366	2.3725	-0.0188368	-0.0936632
38	2.11	2.23464	2.28333	-0.0486979	-0.124635
39	2.01	2.13644	2.21792	-0.0814757	-0.126441
40	1.99	2.07283	2.17417	-0.101337	-0.0828299
41	1.96	2.0404	2.14	-0.0996007	-0.0803993
42	1.93	2.09512	2.11792	-0.0227951	-0.165122
43	1.98	2.12054	2.11333	0.00720486	-0.140538
44	2.07	2.17859	2.12208	0.0565104	-0.108594
45	2.24	2.26845	2.14333	0.125122	-0.0284549
46	2.31	2.28845	2.16792	0.120538	0.0215451
47	2.23	2.24339	2.19083	0.0525521	-0.0133854
48	2.26	2.23582	2.225	0.010816	0.024184
49	2.28	2.25241	2.27125	-0.0188368	0.0275868
50	2.3	2.28047	2.32917	-0.0486979	0.0195312
51	2.33	2.32227	2.40375	-0.0814757	0.00772569
52	2.26	2.38033	2.48167	-0.101337	-0.12033
53	2.24	2.44832	2.54792	-0.0996007	-0.208316
54	2.47	2.57137	2.59417	-0.0227951	-0.101372
55	2.55	2.62387	2.61667	0.00720486	-0.0738715
56	2.89	2.67734	2.62083	0.0565104	0.212656
57	3.21	2.74137	2.61625	0.125122	0.468628
58	3.21	2.73054	2.61	0.120538	0.479462
59	2.92	2.65755	2.605	0.0525521	0.262448
60	2.68	2.60332	2.5925	0.010816	0.076684
61	2.4	2.55075	2.56958	-0.0188368	-0.150747
62	2.28	2.4813	2.53	-0.0486979	-0.201302
63	2.24	2.38102	2.4625	-0.0814757	-0.141024
64	2.2	2.28033	2.38167	-0.101337	-0.0803299
65	2.18	2.21332	2.31292	-0.0996007	-0.033316
66	2.23	2.24179	2.26458	-0.0227951	-0.0117882
67	2.24	2.24262	2.23542	0.00720486	-0.00262153
68	2.25	2.27776	2.22125	0.0565104	-0.0277604
69	2.23	2.3372	2.21208	0.125122	-0.107205
70	2.25	2.3247	2.20417	0.120538	-0.0747049
71	2.23	2.2513	2.19875	0.0525521	-0.0213021
72	2.21	2.20498	2.19417	0.010816	0.00501736
73	2.17	2.17658	2.19542	-0.0188368	-0.00657986
74	2.17	2.16089	2.20958	-0.0486979	0.00911458
75	2.13	2.15269	2.23417	-0.0814757	-0.022691
76	2.12	2.16116	2.2625	-0.101337	-0.0411632
77	2.13	2.19165	2.29125	-0.0996007	-0.0616493
78	2.17	2.2872	2.31	-0.0227951	-0.117205
79	2.33	NA	NA	0.00720486	NA
80	2.5	NA	NA	0.0565104	NA
81	2.57	NA	NA	0.125122	NA
82	2.59	NA	NA	0.120538	NA
83	2.58	NA	NA	0.0525521	NA
84	2.31	NA	NA	0.010816	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.94 & NA & NA & -0.0188368 & NA \tabularnewline
2 & 1.82 & NA & NA & -0.0486979 & NA \tabularnewline
3 & 1.8 & NA & NA & -0.0814757 & NA \tabularnewline
4 & 1.79 & NA & NA & -0.101337 & NA \tabularnewline
5 & 1.79 & NA & NA & -0.0996007 & NA \tabularnewline
6 & 1.78 & NA & NA & -0.0227951 & NA \tabularnewline
7 & 1.81 & 1.8372 & 1.83 & 0.00720486 & -0.0272049 \tabularnewline
8 & 1.84 & 1.88193 & 1.82542 & 0.0565104 & -0.0419271 \tabularnewline
9 & 1.87 & 1.9522 & 1.82708 & 0.125122 & -0.0822049 \tabularnewline
10 & 1.87 & 1.95012 & 1.82958 & 0.120538 & -0.0801215 \tabularnewline
11 & 1.87 & 1.88505 & 1.8325 & 0.0525521 & -0.0150521 \tabularnewline
12 & 1.84 & 1.84873 & 1.83792 & 0.010816 & -0.00873264 \tabularnewline
13 & 1.82 & 1.82575 & 1.84458 & -0.0188368 & -0.00574653 \tabularnewline
14 & 1.83 & 1.8013 & 1.85 & -0.0486979 & 0.0286979 \tabularnewline
15 & 1.83 & 1.77561 & 1.85708 & -0.0814757 & 0.0543924 \tabularnewline
16 & 1.82 & 1.767 & 1.86833 & -0.101337 & 0.0530035 \tabularnewline
17 & 1.83 & 1.78665 & 1.88625 & -0.0996007 & 0.0433507 \tabularnewline
18 & 1.87 & 1.89887 & 1.92167 & -0.0227951 & -0.0288715 \tabularnewline
19 & 1.88 & 1.99095 & 1.98375 & 0.00720486 & -0.110955 \tabularnewline
20 & 1.9 & 2.12026 & 2.06375 & 0.0565104 & -0.22026 \tabularnewline
21 & 1.98 & 2.27345 & 2.14833 & 0.125122 & -0.293455 \tabularnewline
22 & 2.03 & 2.35804 & 2.2375 & 0.120538 & -0.328038 \tabularnewline
23 & 2.14 & 2.38797 & 2.33542 & 0.0525521 & -0.247969 \tabularnewline
24 & 2.42 & 2.45457 & 2.44375 & 0.010816 & -0.034566 \tabularnewline
25 & 2.73 & 2.53616 & 2.555 & -0.0188368 & 0.193837 \tabularnewline
26 & 2.84 & 2.60672 & 2.65542 & -0.0486979 & 0.233281 \tabularnewline
27 & 2.85 & 2.65727 & 2.73875 & -0.0814757 & 0.192726 \tabularnewline
28 & 2.94 & 2.70366 & 2.805 & -0.101337 & 0.236337 \tabularnewline
29 & 3.06 & 2.75498 & 2.85458 & -0.0996007 & 0.305017 \tabularnewline
30 & 3.24 & 2.85095 & 2.87375 & -0.0227951 & 0.389045 \tabularnewline
31 & 3.18 & 2.86012 & 2.85292 & 0.00720486 & 0.319878 \tabularnewline
32 & 3.01 & 2.85943 & 2.80292 & 0.0565104 & 0.150573 \tabularnewline
33 & 2.87 & 2.86262 & 2.7375 & 0.125122 & 0.00737847 \tabularnewline
34 & 2.73 & 2.78345 & 2.66292 & 0.120538 & -0.0534549 \tabularnewline
35 & 2.63 & 2.63005 & 2.5775 & 0.0525521 & -5.20833e-05 \tabularnewline
36 & 2.39 & 2.4879 & 2.47708 & 0.010816 & -0.0978993 \tabularnewline
37 & 2.26 & 2.35366 & 2.3725 & -0.0188368 & -0.0936632 \tabularnewline
38 & 2.11 & 2.23464 & 2.28333 & -0.0486979 & -0.124635 \tabularnewline
39 & 2.01 & 2.13644 & 2.21792 & -0.0814757 & -0.126441 \tabularnewline
40 & 1.99 & 2.07283 & 2.17417 & -0.101337 & -0.0828299 \tabularnewline
41 & 1.96 & 2.0404 & 2.14 & -0.0996007 & -0.0803993 \tabularnewline
42 & 1.93 & 2.09512 & 2.11792 & -0.0227951 & -0.165122 \tabularnewline
43 & 1.98 & 2.12054 & 2.11333 & 0.00720486 & -0.140538 \tabularnewline
44 & 2.07 & 2.17859 & 2.12208 & 0.0565104 & -0.108594 \tabularnewline
45 & 2.24 & 2.26845 & 2.14333 & 0.125122 & -0.0284549 \tabularnewline
46 & 2.31 & 2.28845 & 2.16792 & 0.120538 & 0.0215451 \tabularnewline
47 & 2.23 & 2.24339 & 2.19083 & 0.0525521 & -0.0133854 \tabularnewline
48 & 2.26 & 2.23582 & 2.225 & 0.010816 & 0.024184 \tabularnewline
49 & 2.28 & 2.25241 & 2.27125 & -0.0188368 & 0.0275868 \tabularnewline
50 & 2.3 & 2.28047 & 2.32917 & -0.0486979 & 0.0195312 \tabularnewline
51 & 2.33 & 2.32227 & 2.40375 & -0.0814757 & 0.00772569 \tabularnewline
52 & 2.26 & 2.38033 & 2.48167 & -0.101337 & -0.12033 \tabularnewline
53 & 2.24 & 2.44832 & 2.54792 & -0.0996007 & -0.208316 \tabularnewline
54 & 2.47 & 2.57137 & 2.59417 & -0.0227951 & -0.101372 \tabularnewline
55 & 2.55 & 2.62387 & 2.61667 & 0.00720486 & -0.0738715 \tabularnewline
56 & 2.89 & 2.67734 & 2.62083 & 0.0565104 & 0.212656 \tabularnewline
57 & 3.21 & 2.74137 & 2.61625 & 0.125122 & 0.468628 \tabularnewline
58 & 3.21 & 2.73054 & 2.61 & 0.120538 & 0.479462 \tabularnewline
59 & 2.92 & 2.65755 & 2.605 & 0.0525521 & 0.262448 \tabularnewline
60 & 2.68 & 2.60332 & 2.5925 & 0.010816 & 0.076684 \tabularnewline
61 & 2.4 & 2.55075 & 2.56958 & -0.0188368 & -0.150747 \tabularnewline
62 & 2.28 & 2.4813 & 2.53 & -0.0486979 & -0.201302 \tabularnewline
63 & 2.24 & 2.38102 & 2.4625 & -0.0814757 & -0.141024 \tabularnewline
64 & 2.2 & 2.28033 & 2.38167 & -0.101337 & -0.0803299 \tabularnewline
65 & 2.18 & 2.21332 & 2.31292 & -0.0996007 & -0.033316 \tabularnewline
66 & 2.23 & 2.24179 & 2.26458 & -0.0227951 & -0.0117882 \tabularnewline
67 & 2.24 & 2.24262 & 2.23542 & 0.00720486 & -0.00262153 \tabularnewline
68 & 2.25 & 2.27776 & 2.22125 & 0.0565104 & -0.0277604 \tabularnewline
69 & 2.23 & 2.3372 & 2.21208 & 0.125122 & -0.107205 \tabularnewline
70 & 2.25 & 2.3247 & 2.20417 & 0.120538 & -0.0747049 \tabularnewline
71 & 2.23 & 2.2513 & 2.19875 & 0.0525521 & -0.0213021 \tabularnewline
72 & 2.21 & 2.20498 & 2.19417 & 0.010816 & 0.00501736 \tabularnewline
73 & 2.17 & 2.17658 & 2.19542 & -0.0188368 & -0.00657986 \tabularnewline
74 & 2.17 & 2.16089 & 2.20958 & -0.0486979 & 0.00911458 \tabularnewline
75 & 2.13 & 2.15269 & 2.23417 & -0.0814757 & -0.022691 \tabularnewline
76 & 2.12 & 2.16116 & 2.2625 & -0.101337 & -0.0411632 \tabularnewline
77 & 2.13 & 2.19165 & 2.29125 & -0.0996007 & -0.0616493 \tabularnewline
78 & 2.17 & 2.2872 & 2.31 & -0.0227951 & -0.117205 \tabularnewline
79 & 2.33 & NA & NA & 0.00720486 & NA \tabularnewline
80 & 2.5 & NA & NA & 0.0565104 & NA \tabularnewline
81 & 2.57 & NA & NA & 0.125122 & NA \tabularnewline
82 & 2.59 & NA & NA & 0.120538 & NA \tabularnewline
83 & 2.58 & NA & NA & 0.0525521 & NA \tabularnewline
84 & 2.31 & NA & NA & 0.010816 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232601&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]1.94[/C][C]NA[/C][C]NA[/C][C]-0.0188368[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.82[/C][C]NA[/C][C]NA[/C][C]-0.0486979[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]-0.0814757[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.79[/C][C]NA[/C][C]NA[/C][C]-0.101337[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.79[/C][C]NA[/C][C]NA[/C][C]-0.0996007[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.78[/C][C]NA[/C][C]NA[/C][C]-0.0227951[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.81[/C][C]1.8372[/C][C]1.83[/C][C]0.00720486[/C][C]-0.0272049[/C][/ROW]
[ROW][C]8[/C][C]1.84[/C][C]1.88193[/C][C]1.82542[/C][C]0.0565104[/C][C]-0.0419271[/C][/ROW]
[ROW][C]9[/C][C]1.87[/C][C]1.9522[/C][C]1.82708[/C][C]0.125122[/C][C]-0.0822049[/C][/ROW]
[ROW][C]10[/C][C]1.87[/C][C]1.95012[/C][C]1.82958[/C][C]0.120538[/C][C]-0.0801215[/C][/ROW]
[ROW][C]11[/C][C]1.87[/C][C]1.88505[/C][C]1.8325[/C][C]0.0525521[/C][C]-0.0150521[/C][/ROW]
[ROW][C]12[/C][C]1.84[/C][C]1.84873[/C][C]1.83792[/C][C]0.010816[/C][C]-0.00873264[/C][/ROW]
[ROW][C]13[/C][C]1.82[/C][C]1.82575[/C][C]1.84458[/C][C]-0.0188368[/C][C]-0.00574653[/C][/ROW]
[ROW][C]14[/C][C]1.83[/C][C]1.8013[/C][C]1.85[/C][C]-0.0486979[/C][C]0.0286979[/C][/ROW]
[ROW][C]15[/C][C]1.83[/C][C]1.77561[/C][C]1.85708[/C][C]-0.0814757[/C][C]0.0543924[/C][/ROW]
[ROW][C]16[/C][C]1.82[/C][C]1.767[/C][C]1.86833[/C][C]-0.101337[/C][C]0.0530035[/C][/ROW]
[ROW][C]17[/C][C]1.83[/C][C]1.78665[/C][C]1.88625[/C][C]-0.0996007[/C][C]0.0433507[/C][/ROW]
[ROW][C]18[/C][C]1.87[/C][C]1.89887[/C][C]1.92167[/C][C]-0.0227951[/C][C]-0.0288715[/C][/ROW]
[ROW][C]19[/C][C]1.88[/C][C]1.99095[/C][C]1.98375[/C][C]0.00720486[/C][C]-0.110955[/C][/ROW]
[ROW][C]20[/C][C]1.9[/C][C]2.12026[/C][C]2.06375[/C][C]0.0565104[/C][C]-0.22026[/C][/ROW]
[ROW][C]21[/C][C]1.98[/C][C]2.27345[/C][C]2.14833[/C][C]0.125122[/C][C]-0.293455[/C][/ROW]
[ROW][C]22[/C][C]2.03[/C][C]2.35804[/C][C]2.2375[/C][C]0.120538[/C][C]-0.328038[/C][/ROW]
[ROW][C]23[/C][C]2.14[/C][C]2.38797[/C][C]2.33542[/C][C]0.0525521[/C][C]-0.247969[/C][/ROW]
[ROW][C]24[/C][C]2.42[/C][C]2.45457[/C][C]2.44375[/C][C]0.010816[/C][C]-0.034566[/C][/ROW]
[ROW][C]25[/C][C]2.73[/C][C]2.53616[/C][C]2.555[/C][C]-0.0188368[/C][C]0.193837[/C][/ROW]
[ROW][C]26[/C][C]2.84[/C][C]2.60672[/C][C]2.65542[/C][C]-0.0486979[/C][C]0.233281[/C][/ROW]
[ROW][C]27[/C][C]2.85[/C][C]2.65727[/C][C]2.73875[/C][C]-0.0814757[/C][C]0.192726[/C][/ROW]
[ROW][C]28[/C][C]2.94[/C][C]2.70366[/C][C]2.805[/C][C]-0.101337[/C][C]0.236337[/C][/ROW]
[ROW][C]29[/C][C]3.06[/C][C]2.75498[/C][C]2.85458[/C][C]-0.0996007[/C][C]0.305017[/C][/ROW]
[ROW][C]30[/C][C]3.24[/C][C]2.85095[/C][C]2.87375[/C][C]-0.0227951[/C][C]0.389045[/C][/ROW]
[ROW][C]31[/C][C]3.18[/C][C]2.86012[/C][C]2.85292[/C][C]0.00720486[/C][C]0.319878[/C][/ROW]
[ROW][C]32[/C][C]3.01[/C][C]2.85943[/C][C]2.80292[/C][C]0.0565104[/C][C]0.150573[/C][/ROW]
[ROW][C]33[/C][C]2.87[/C][C]2.86262[/C][C]2.7375[/C][C]0.125122[/C][C]0.00737847[/C][/ROW]
[ROW][C]34[/C][C]2.73[/C][C]2.78345[/C][C]2.66292[/C][C]0.120538[/C][C]-0.0534549[/C][/ROW]
[ROW][C]35[/C][C]2.63[/C][C]2.63005[/C][C]2.5775[/C][C]0.0525521[/C][C]-5.20833e-05[/C][/ROW]
[ROW][C]36[/C][C]2.39[/C][C]2.4879[/C][C]2.47708[/C][C]0.010816[/C][C]-0.0978993[/C][/ROW]
[ROW][C]37[/C][C]2.26[/C][C]2.35366[/C][C]2.3725[/C][C]-0.0188368[/C][C]-0.0936632[/C][/ROW]
[ROW][C]38[/C][C]2.11[/C][C]2.23464[/C][C]2.28333[/C][C]-0.0486979[/C][C]-0.124635[/C][/ROW]
[ROW][C]39[/C][C]2.01[/C][C]2.13644[/C][C]2.21792[/C][C]-0.0814757[/C][C]-0.126441[/C][/ROW]
[ROW][C]40[/C][C]1.99[/C][C]2.07283[/C][C]2.17417[/C][C]-0.101337[/C][C]-0.0828299[/C][/ROW]
[ROW][C]41[/C][C]1.96[/C][C]2.0404[/C][C]2.14[/C][C]-0.0996007[/C][C]-0.0803993[/C][/ROW]
[ROW][C]42[/C][C]1.93[/C][C]2.09512[/C][C]2.11792[/C][C]-0.0227951[/C][C]-0.165122[/C][/ROW]
[ROW][C]43[/C][C]1.98[/C][C]2.12054[/C][C]2.11333[/C][C]0.00720486[/C][C]-0.140538[/C][/ROW]
[ROW][C]44[/C][C]2.07[/C][C]2.17859[/C][C]2.12208[/C][C]0.0565104[/C][C]-0.108594[/C][/ROW]
[ROW][C]45[/C][C]2.24[/C][C]2.26845[/C][C]2.14333[/C][C]0.125122[/C][C]-0.0284549[/C][/ROW]
[ROW][C]46[/C][C]2.31[/C][C]2.28845[/C][C]2.16792[/C][C]0.120538[/C][C]0.0215451[/C][/ROW]
[ROW][C]47[/C][C]2.23[/C][C]2.24339[/C][C]2.19083[/C][C]0.0525521[/C][C]-0.0133854[/C][/ROW]
[ROW][C]48[/C][C]2.26[/C][C]2.23582[/C][C]2.225[/C][C]0.010816[/C][C]0.024184[/C][/ROW]
[ROW][C]49[/C][C]2.28[/C][C]2.25241[/C][C]2.27125[/C][C]-0.0188368[/C][C]0.0275868[/C][/ROW]
[ROW][C]50[/C][C]2.3[/C][C]2.28047[/C][C]2.32917[/C][C]-0.0486979[/C][C]0.0195312[/C][/ROW]
[ROW][C]51[/C][C]2.33[/C][C]2.32227[/C][C]2.40375[/C][C]-0.0814757[/C][C]0.00772569[/C][/ROW]
[ROW][C]52[/C][C]2.26[/C][C]2.38033[/C][C]2.48167[/C][C]-0.101337[/C][C]-0.12033[/C][/ROW]
[ROW][C]53[/C][C]2.24[/C][C]2.44832[/C][C]2.54792[/C][C]-0.0996007[/C][C]-0.208316[/C][/ROW]
[ROW][C]54[/C][C]2.47[/C][C]2.57137[/C][C]2.59417[/C][C]-0.0227951[/C][C]-0.101372[/C][/ROW]
[ROW][C]55[/C][C]2.55[/C][C]2.62387[/C][C]2.61667[/C][C]0.00720486[/C][C]-0.0738715[/C][/ROW]
[ROW][C]56[/C][C]2.89[/C][C]2.67734[/C][C]2.62083[/C][C]0.0565104[/C][C]0.212656[/C][/ROW]
[ROW][C]57[/C][C]3.21[/C][C]2.74137[/C][C]2.61625[/C][C]0.125122[/C][C]0.468628[/C][/ROW]
[ROW][C]58[/C][C]3.21[/C][C]2.73054[/C][C]2.61[/C][C]0.120538[/C][C]0.479462[/C][/ROW]
[ROW][C]59[/C][C]2.92[/C][C]2.65755[/C][C]2.605[/C][C]0.0525521[/C][C]0.262448[/C][/ROW]
[ROW][C]60[/C][C]2.68[/C][C]2.60332[/C][C]2.5925[/C][C]0.010816[/C][C]0.076684[/C][/ROW]
[ROW][C]61[/C][C]2.4[/C][C]2.55075[/C][C]2.56958[/C][C]-0.0188368[/C][C]-0.150747[/C][/ROW]
[ROW][C]62[/C][C]2.28[/C][C]2.4813[/C][C]2.53[/C][C]-0.0486979[/C][C]-0.201302[/C][/ROW]
[ROW][C]63[/C][C]2.24[/C][C]2.38102[/C][C]2.4625[/C][C]-0.0814757[/C][C]-0.141024[/C][/ROW]
[ROW][C]64[/C][C]2.2[/C][C]2.28033[/C][C]2.38167[/C][C]-0.101337[/C][C]-0.0803299[/C][/ROW]
[ROW][C]65[/C][C]2.18[/C][C]2.21332[/C][C]2.31292[/C][C]-0.0996007[/C][C]-0.033316[/C][/ROW]
[ROW][C]66[/C][C]2.23[/C][C]2.24179[/C][C]2.26458[/C][C]-0.0227951[/C][C]-0.0117882[/C][/ROW]
[ROW][C]67[/C][C]2.24[/C][C]2.24262[/C][C]2.23542[/C][C]0.00720486[/C][C]-0.00262153[/C][/ROW]
[ROW][C]68[/C][C]2.25[/C][C]2.27776[/C][C]2.22125[/C][C]0.0565104[/C][C]-0.0277604[/C][/ROW]
[ROW][C]69[/C][C]2.23[/C][C]2.3372[/C][C]2.21208[/C][C]0.125122[/C][C]-0.107205[/C][/ROW]
[ROW][C]70[/C][C]2.25[/C][C]2.3247[/C][C]2.20417[/C][C]0.120538[/C][C]-0.0747049[/C][/ROW]
[ROW][C]71[/C][C]2.23[/C][C]2.2513[/C][C]2.19875[/C][C]0.0525521[/C][C]-0.0213021[/C][/ROW]
[ROW][C]72[/C][C]2.21[/C][C]2.20498[/C][C]2.19417[/C][C]0.010816[/C][C]0.00501736[/C][/ROW]
[ROW][C]73[/C][C]2.17[/C][C]2.17658[/C][C]2.19542[/C][C]-0.0188368[/C][C]-0.00657986[/C][/ROW]
[ROW][C]74[/C][C]2.17[/C][C]2.16089[/C][C]2.20958[/C][C]-0.0486979[/C][C]0.00911458[/C][/ROW]
[ROW][C]75[/C][C]2.13[/C][C]2.15269[/C][C]2.23417[/C][C]-0.0814757[/C][C]-0.022691[/C][/ROW]
[ROW][C]76[/C][C]2.12[/C][C]2.16116[/C][C]2.2625[/C][C]-0.101337[/C][C]-0.0411632[/C][/ROW]
[ROW][C]77[/C][C]2.13[/C][C]2.19165[/C][C]2.29125[/C][C]-0.0996007[/C][C]-0.0616493[/C][/ROW]
[ROW][C]78[/C][C]2.17[/C][C]2.2872[/C][C]2.31[/C][C]-0.0227951[/C][C]-0.117205[/C][/ROW]
[ROW][C]79[/C][C]2.33[/C][C]NA[/C][C]NA[/C][C]0.00720486[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]0.0565104[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]2.57[/C][C]NA[/C][C]NA[/C][C]0.125122[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]2.59[/C][C]NA[/C][C]NA[/C][C]0.120538[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]2.58[/C][C]NA[/C][C]NA[/C][C]0.0525521[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]2.31[/C][C]NA[/C][C]NA[/C][C]0.010816[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232601&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	1.94	NA	NA	-0.0188368	NA
2	1.82	NA	NA	-0.0486979	NA
3	1.8	NA	NA	-0.0814757	NA
4	1.79	NA	NA	-0.101337	NA
5	1.79	NA	NA	-0.0996007	NA
6	1.78	NA	NA	-0.0227951	NA
7	1.81	1.8372	1.83	0.00720486	-0.0272049
8	1.84	1.88193	1.82542	0.0565104	-0.0419271
9	1.87	1.9522	1.82708	0.125122	-0.0822049
10	1.87	1.95012	1.82958	0.120538	-0.0801215
11	1.87	1.88505	1.8325	0.0525521	-0.0150521
12	1.84	1.84873	1.83792	0.010816	-0.00873264
13	1.82	1.82575	1.84458	-0.0188368	-0.00574653
14	1.83	1.8013	1.85	-0.0486979	0.0286979
15	1.83	1.77561	1.85708	-0.0814757	0.0543924
16	1.82	1.767	1.86833	-0.101337	0.0530035
17	1.83	1.78665	1.88625	-0.0996007	0.0433507
18	1.87	1.89887	1.92167	-0.0227951	-0.0288715
19	1.88	1.99095	1.98375	0.00720486	-0.110955
20	1.9	2.12026	2.06375	0.0565104	-0.22026
21	1.98	2.27345	2.14833	0.125122	-0.293455
22	2.03	2.35804	2.2375	0.120538	-0.328038
23	2.14	2.38797	2.33542	0.0525521	-0.247969
24	2.42	2.45457	2.44375	0.010816	-0.034566
25	2.73	2.53616	2.555	-0.0188368	0.193837
26	2.84	2.60672	2.65542	-0.0486979	0.233281
27	2.85	2.65727	2.73875	-0.0814757	0.192726
28	2.94	2.70366	2.805	-0.101337	0.236337
29	3.06	2.75498	2.85458	-0.0996007	0.305017
30	3.24	2.85095	2.87375	-0.0227951	0.389045
31	3.18	2.86012	2.85292	0.00720486	0.319878
32	3.01	2.85943	2.80292	0.0565104	0.150573
33	2.87	2.86262	2.7375	0.125122	0.00737847
34	2.73	2.78345	2.66292	0.120538	-0.0534549
35	2.63	2.63005	2.5775	0.0525521	-5.20833e-05
36	2.39	2.4879	2.47708	0.010816	-0.0978993
37	2.26	2.35366	2.3725	-0.0188368	-0.0936632
38	2.11	2.23464	2.28333	-0.0486979	-0.124635
39	2.01	2.13644	2.21792	-0.0814757	-0.126441
40	1.99	2.07283	2.17417	-0.101337	-0.0828299
41	1.96	2.0404	2.14	-0.0996007	-0.0803993
42	1.93	2.09512	2.11792	-0.0227951	-0.165122
43	1.98	2.12054	2.11333	0.00720486	-0.140538
44	2.07	2.17859	2.12208	0.0565104	-0.108594
45	2.24	2.26845	2.14333	0.125122	-0.0284549
46	2.31	2.28845	2.16792	0.120538	0.0215451
47	2.23	2.24339	2.19083	0.0525521	-0.0133854
48	2.26	2.23582	2.225	0.010816	0.024184
49	2.28	2.25241	2.27125	-0.0188368	0.0275868
50	2.3	2.28047	2.32917	-0.0486979	0.0195312
51	2.33	2.32227	2.40375	-0.0814757	0.00772569
52	2.26	2.38033	2.48167	-0.101337	-0.12033
53	2.24	2.44832	2.54792	-0.0996007	-0.208316
54	2.47	2.57137	2.59417	-0.0227951	-0.101372
55	2.55	2.62387	2.61667	0.00720486	-0.0738715
56	2.89	2.67734	2.62083	0.0565104	0.212656
57	3.21	2.74137	2.61625	0.125122	0.468628
58	3.21	2.73054	2.61	0.120538	0.479462
59	2.92	2.65755	2.605	0.0525521	0.262448
60	2.68	2.60332	2.5925	0.010816	0.076684
61	2.4	2.55075	2.56958	-0.0188368	-0.150747
62	2.28	2.4813	2.53	-0.0486979	-0.201302
63	2.24	2.38102	2.4625	-0.0814757	-0.141024
64	2.2	2.28033	2.38167	-0.101337	-0.0803299
65	2.18	2.21332	2.31292	-0.0996007	-0.033316
66	2.23	2.24179	2.26458	-0.0227951	-0.0117882
67	2.24	2.24262	2.23542	0.00720486	-0.00262153
68	2.25	2.27776	2.22125	0.0565104	-0.0277604
69	2.23	2.3372	2.21208	0.125122	-0.107205
70	2.25	2.3247	2.20417	0.120538	-0.0747049
71	2.23	2.2513	2.19875	0.0525521	-0.0213021
72	2.21	2.20498	2.19417	0.010816	0.00501736
73	2.17	2.17658	2.19542	-0.0188368	-0.00657986
74	2.17	2.16089	2.20958	-0.0486979	0.00911458
75	2.13	2.15269	2.23417	-0.0814757	-0.022691
76	2.12	2.16116	2.2625	-0.101337	-0.0411632
77	2.13	2.19165	2.29125	-0.0996007	-0.0616493
78	2.17	2.2872	2.31	-0.0227951	-0.117205
79	2.33	NA	NA	0.00720486	NA
80	2.5	NA	NA	0.0565104	NA
81	2.57	NA	NA	0.125122	NA
82	2.59	NA	NA	0.120538	NA
83	2.58	NA	NA	0.0525521	NA
84	2.31	NA	NA	0.010816	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