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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 02 Apr 2015 14:27:32 +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/2015/Apr/02/t14279812987qrzf48d6h3dnrx.htm/, Retrieved Thu, 09 May 2024 07:53:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278554, Retrieved Thu, 09 May 2024 07:53:36 +0000

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

-       [Classical Decomposition] [Classical Deompos...] [2015-04-02 13:27:32] [fe7f0d9da4a60fe1aade911e6a24ddc7] [Current]

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Dataseries X:

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2,08
2,09
2,36
2,99
2,75
1,58
1,69
1,3
1,97
1,84
1,96
1,86
2,75
2,62
2,41
3,61
2,03
1,45
1,4
1,3
1,58
2,1
2,27
2,54
2,55
2,05
2,32
2,6
2,1
1,61
1,55
1,12
1,39
2,18
1,94
2,27
2,41
2,2
2,58
2,9
2,12
1,34
1,07
0,86
1
1,54
1,29
1,44
2,6
2,77
3,31
3,2
2,07
1,42
1,43
1,28
1,59
1,68
2,01
2,52
2,74
3,06
2,69
2,32
1,67
1,04
0,98
0,86
0,97
1,3
1,82
1,99
2,7
2,86
2,91
2,56
2,05
1,62
1,26
1,44
1,27
1,64
1,84
2,1
2,79
2,84
2,76
2,67
2,1
1,55
1,42
1,12
1,12
1,41
1,56
1,8

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278554&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278554&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278554&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	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.08	NA	NA	0.652237	NA
2	2.09	NA	NA	0.634916	NA
3	2.36	NA	NA	0.723904	NA
4	2.99	NA	NA	0.857237	NA
5	2.75	NA	NA	0.0450347	NA
6	1.58	NA	NA	-0.53937	NA
7	1.69	1.41515	2.06708	-0.65193	0.274846
8	1.3	1.28218	2.11708	-0.834906	0.0178224
9	1.97	1.5295	2.14125	-0.611751	0.440501
10	1.84	1.91551	2.16917	-0.253656	-0.0755109
11	1.96	2.03855	2.165	-0.126453	-0.0785466
12	1.86	2.23432	2.12958	0.104737	-0.37432
13	2.75	2.76432	2.11208	0.652237	-0.0143204
14	2.62	2.73492	2.1	0.634916	-0.114916
15	2.41	2.80765	2.08375	0.723904	-0.397654
16	3.61	2.93557	2.07833	0.857237	0.67443
17	2.03	2.14712	2.10208	0.0450347	-0.117118
18	1.45	1.60396	2.14333	-0.53937	-0.153963
19	1.4	1.5114	2.16333	-0.65193	-0.111404
20	1.3	1.29634	2.13125	-0.834906	0.00365575
21	1.58	1.492	2.10375	-0.611751	0.088001
22	2.1	1.80426	2.05792	-0.253656	0.295739
23	2.27	1.8923	2.01875	-0.126453	0.377703
24	2.54	2.13307	2.02833	0.104737	0.40693
25	2.55	2.69349	2.04125	0.652237	-0.143487
26	2.05	2.67492	2.04	0.634916	-0.624916
27	2.32	2.74849	2.02458	0.723904	-0.428487
28	2.6	2.87724	2.02	0.857237	-0.277237
29	2.1	2.05462	2.00958	0.0450347	0.0453819
30	1.61	1.44521	1.98458	-0.53937	0.164787
31	1.55	1.31557	1.9675	-0.65193	0.23443
32	1.12	1.13301	1.96792	-0.834906	-0.0130109
33	1.39	1.37325	1.985	-0.611751	0.016751
34	2.18	1.75468	2.00833	-0.253656	0.425322
35	1.94	1.89521	2.02167	-0.126453	0.0447867
36	2.27	2.11599	2.01125	0.104737	0.154013
37	2.41	2.63224	1.98	0.652237	-0.222237
38	2.2	2.58408	1.94917	0.634916	-0.384082
39	2.58	2.64599	1.92208	0.723904	-0.0659871
40	2.9	2.7364	1.87917	0.857237	0.163596
41	2.12	1.87045	1.82542	0.0450347	0.249549
42	1.34	1.22438	1.76375	-0.53937	0.11562
43	1.07	1.08515	1.73708	-0.65193	-0.0151538
44	0.86	0.933844	1.76875	-0.834906	-0.0738442
45	1	1.21117	1.82292	-0.611751	-0.211166
46	1.54	1.61218	1.86583	-0.253656	-0.0721776
47	1.29	1.7498	1.87625	-0.126453	-0.459797
48	1.44	1.98224	1.8775	0.104737	-0.542237
49	2.6	2.54807	1.89583	0.652237	0.0519296
50	2.77	2.56325	1.92833	0.634916	0.206751
51	3.31	2.69432	1.97042	0.723904	0.61568
52	3.2	2.85807	2.00083	0.857237	0.34193
53	2.07	2.0817	2.03667	0.0450347	-0.0117014
54	1.42	1.5723	2.11167	-0.53937	-0.152297
55	1.43	1.51057	2.1625	-0.65193	-0.0805704
56	1.28	1.34551	2.18042	-0.834906	-0.0655109
57	1.59	1.55492	2.16667	-0.611751	0.0350843
58	1.68	1.85051	2.10417	-0.253656	-0.170511
59	2.01	1.92438	2.05083	-0.126453	0.08562
60	2.52	2.12307	2.01833	0.104737	0.39693
61	2.74	2.63599	1.98375	0.652237	0.104013
62	3.06	2.58242	1.9475	0.634916	0.477584
63	2.69	2.62807	1.90417	0.723904	0.0619296
64	2.32	2.71974	1.8625	0.857237	-0.399737
65	1.67	1.88378	1.83875	0.0450347	-0.213785
66	1.04	1.26938	1.80875	-0.53937	-0.22938
67	0.98	1.13307	1.785	-0.65193	-0.15307
68	0.86	0.940094	1.775	-0.834906	-0.0800942
69	0.97	1.16408	1.77583	-0.611751	-0.194082
70	1.3	1.54134	1.795	-0.253656	-0.241344
71	1.82	1.69438	1.82083	-0.126453	0.12562
72	1.99	1.96557	1.86083	0.104737	0.0244296
73	2.7	2.5489	1.89667	0.652237	0.151096
74	2.86	2.56742	1.9325	0.634916	0.292584
75	2.91	2.69307	1.96917	0.723904	0.21693
76	2.56	2.85307	1.99583	0.857237	-0.29307
77	2.05	2.05587	2.01083	0.0450347	-0.00586806
78	1.62	1.47688	2.01625	-0.53937	0.14312
79	1.26	1.37265	2.02458	-0.65193	-0.112654
80	1.44	1.19259	2.0275	-0.834906	0.247406
81	1.27	1.40867	2.02042	-0.611751	-0.138666
82	1.64	1.76509	2.01875	-0.253656	-0.125094
83	1.84	1.89896	2.02542	-0.126453	-0.0589633
84	2.1	2.12932	2.02458	0.104737	-0.0293204
85	2.79	2.68057	2.02833	0.652237	0.10943
86	2.84	2.65658	2.02167	0.634916	0.183418
87	2.76	2.72599	2.00208	0.723904	0.0340129
88	2.67	2.84349	1.98625	0.857237	-0.173487
89	2.1	2.01003	1.965	0.0450347	0.0899653
90	1.55	1.40146	1.94083	-0.53937	0.148537
91	1.42	NA	NA	-0.65193	NA
92	1.12	NA	NA	-0.834906	NA
93	1.12	NA	NA	-0.611751	NA
94	1.41	NA	NA	-0.253656	NA
95	1.56	NA	NA	-0.126453	NA
96	1.8	NA	NA	0.104737	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.08 & NA & NA & 0.652237 & NA \tabularnewline
2 & 2.09 & NA & NA & 0.634916 & NA \tabularnewline
3 & 2.36 & NA & NA & 0.723904 & NA \tabularnewline
4 & 2.99 & NA & NA & 0.857237 & NA \tabularnewline
5 & 2.75 & NA & NA & 0.0450347 & NA \tabularnewline
6 & 1.58 & NA & NA & -0.53937 & NA \tabularnewline
7 & 1.69 & 1.41515 & 2.06708 & -0.65193 & 0.274846 \tabularnewline
8 & 1.3 & 1.28218 & 2.11708 & -0.834906 & 0.0178224 \tabularnewline
9 & 1.97 & 1.5295 & 2.14125 & -0.611751 & 0.440501 \tabularnewline
10 & 1.84 & 1.91551 & 2.16917 & -0.253656 & -0.0755109 \tabularnewline
11 & 1.96 & 2.03855 & 2.165 & -0.126453 & -0.0785466 \tabularnewline
12 & 1.86 & 2.23432 & 2.12958 & 0.104737 & -0.37432 \tabularnewline
13 & 2.75 & 2.76432 & 2.11208 & 0.652237 & -0.0143204 \tabularnewline
14 & 2.62 & 2.73492 & 2.1 & 0.634916 & -0.114916 \tabularnewline
15 & 2.41 & 2.80765 & 2.08375 & 0.723904 & -0.397654 \tabularnewline
16 & 3.61 & 2.93557 & 2.07833 & 0.857237 & 0.67443 \tabularnewline
17 & 2.03 & 2.14712 & 2.10208 & 0.0450347 & -0.117118 \tabularnewline
18 & 1.45 & 1.60396 & 2.14333 & -0.53937 & -0.153963 \tabularnewline
19 & 1.4 & 1.5114 & 2.16333 & -0.65193 & -0.111404 \tabularnewline
20 & 1.3 & 1.29634 & 2.13125 & -0.834906 & 0.00365575 \tabularnewline
21 & 1.58 & 1.492 & 2.10375 & -0.611751 & 0.088001 \tabularnewline
22 & 2.1 & 1.80426 & 2.05792 & -0.253656 & 0.295739 \tabularnewline
23 & 2.27 & 1.8923 & 2.01875 & -0.126453 & 0.377703 \tabularnewline
24 & 2.54 & 2.13307 & 2.02833 & 0.104737 & 0.40693 \tabularnewline
25 & 2.55 & 2.69349 & 2.04125 & 0.652237 & -0.143487 \tabularnewline
26 & 2.05 & 2.67492 & 2.04 & 0.634916 & -0.624916 \tabularnewline
27 & 2.32 & 2.74849 & 2.02458 & 0.723904 & -0.428487 \tabularnewline
28 & 2.6 & 2.87724 & 2.02 & 0.857237 & -0.277237 \tabularnewline
29 & 2.1 & 2.05462 & 2.00958 & 0.0450347 & 0.0453819 \tabularnewline
30 & 1.61 & 1.44521 & 1.98458 & -0.53937 & 0.164787 \tabularnewline
31 & 1.55 & 1.31557 & 1.9675 & -0.65193 & 0.23443 \tabularnewline
32 & 1.12 & 1.13301 & 1.96792 & -0.834906 & -0.0130109 \tabularnewline
33 & 1.39 & 1.37325 & 1.985 & -0.611751 & 0.016751 \tabularnewline
34 & 2.18 & 1.75468 & 2.00833 & -0.253656 & 0.425322 \tabularnewline
35 & 1.94 & 1.89521 & 2.02167 & -0.126453 & 0.0447867 \tabularnewline
36 & 2.27 & 2.11599 & 2.01125 & 0.104737 & 0.154013 \tabularnewline
37 & 2.41 & 2.63224 & 1.98 & 0.652237 & -0.222237 \tabularnewline
38 & 2.2 & 2.58408 & 1.94917 & 0.634916 & -0.384082 \tabularnewline
39 & 2.58 & 2.64599 & 1.92208 & 0.723904 & -0.0659871 \tabularnewline
40 & 2.9 & 2.7364 & 1.87917 & 0.857237 & 0.163596 \tabularnewline
41 & 2.12 & 1.87045 & 1.82542 & 0.0450347 & 0.249549 \tabularnewline
42 & 1.34 & 1.22438 & 1.76375 & -0.53937 & 0.11562 \tabularnewline
43 & 1.07 & 1.08515 & 1.73708 & -0.65193 & -0.0151538 \tabularnewline
44 & 0.86 & 0.933844 & 1.76875 & -0.834906 & -0.0738442 \tabularnewline
45 & 1 & 1.21117 & 1.82292 & -0.611751 & -0.211166 \tabularnewline
46 & 1.54 & 1.61218 & 1.86583 & -0.253656 & -0.0721776 \tabularnewline
47 & 1.29 & 1.7498 & 1.87625 & -0.126453 & -0.459797 \tabularnewline
48 & 1.44 & 1.98224 & 1.8775 & 0.104737 & -0.542237 \tabularnewline
49 & 2.6 & 2.54807 & 1.89583 & 0.652237 & 0.0519296 \tabularnewline
50 & 2.77 & 2.56325 & 1.92833 & 0.634916 & 0.206751 \tabularnewline
51 & 3.31 & 2.69432 & 1.97042 & 0.723904 & 0.61568 \tabularnewline
52 & 3.2 & 2.85807 & 2.00083 & 0.857237 & 0.34193 \tabularnewline
53 & 2.07 & 2.0817 & 2.03667 & 0.0450347 & -0.0117014 \tabularnewline
54 & 1.42 & 1.5723 & 2.11167 & -0.53937 & -0.152297 \tabularnewline
55 & 1.43 & 1.51057 & 2.1625 & -0.65193 & -0.0805704 \tabularnewline
56 & 1.28 & 1.34551 & 2.18042 & -0.834906 & -0.0655109 \tabularnewline
57 & 1.59 & 1.55492 & 2.16667 & -0.611751 & 0.0350843 \tabularnewline
58 & 1.68 & 1.85051 & 2.10417 & -0.253656 & -0.170511 \tabularnewline
59 & 2.01 & 1.92438 & 2.05083 & -0.126453 & 0.08562 \tabularnewline
60 & 2.52 & 2.12307 & 2.01833 & 0.104737 & 0.39693 \tabularnewline
61 & 2.74 & 2.63599 & 1.98375 & 0.652237 & 0.104013 \tabularnewline
62 & 3.06 & 2.58242 & 1.9475 & 0.634916 & 0.477584 \tabularnewline
63 & 2.69 & 2.62807 & 1.90417 & 0.723904 & 0.0619296 \tabularnewline
64 & 2.32 & 2.71974 & 1.8625 & 0.857237 & -0.399737 \tabularnewline
65 & 1.67 & 1.88378 & 1.83875 & 0.0450347 & -0.213785 \tabularnewline
66 & 1.04 & 1.26938 & 1.80875 & -0.53937 & -0.22938 \tabularnewline
67 & 0.98 & 1.13307 & 1.785 & -0.65193 & -0.15307 \tabularnewline
68 & 0.86 & 0.940094 & 1.775 & -0.834906 & -0.0800942 \tabularnewline
69 & 0.97 & 1.16408 & 1.77583 & -0.611751 & -0.194082 \tabularnewline
70 & 1.3 & 1.54134 & 1.795 & -0.253656 & -0.241344 \tabularnewline
71 & 1.82 & 1.69438 & 1.82083 & -0.126453 & 0.12562 \tabularnewline
72 & 1.99 & 1.96557 & 1.86083 & 0.104737 & 0.0244296 \tabularnewline
73 & 2.7 & 2.5489 & 1.89667 & 0.652237 & 0.151096 \tabularnewline
74 & 2.86 & 2.56742 & 1.9325 & 0.634916 & 0.292584 \tabularnewline
75 & 2.91 & 2.69307 & 1.96917 & 0.723904 & 0.21693 \tabularnewline
76 & 2.56 & 2.85307 & 1.99583 & 0.857237 & -0.29307 \tabularnewline
77 & 2.05 & 2.05587 & 2.01083 & 0.0450347 & -0.00586806 \tabularnewline
78 & 1.62 & 1.47688 & 2.01625 & -0.53937 & 0.14312 \tabularnewline
79 & 1.26 & 1.37265 & 2.02458 & -0.65193 & -0.112654 \tabularnewline
80 & 1.44 & 1.19259 & 2.0275 & -0.834906 & 0.247406 \tabularnewline
81 & 1.27 & 1.40867 & 2.02042 & -0.611751 & -0.138666 \tabularnewline
82 & 1.64 & 1.76509 & 2.01875 & -0.253656 & -0.125094 \tabularnewline
83 & 1.84 & 1.89896 & 2.02542 & -0.126453 & -0.0589633 \tabularnewline
84 & 2.1 & 2.12932 & 2.02458 & 0.104737 & -0.0293204 \tabularnewline
85 & 2.79 & 2.68057 & 2.02833 & 0.652237 & 0.10943 \tabularnewline
86 & 2.84 & 2.65658 & 2.02167 & 0.634916 & 0.183418 \tabularnewline
87 & 2.76 & 2.72599 & 2.00208 & 0.723904 & 0.0340129 \tabularnewline
88 & 2.67 & 2.84349 & 1.98625 & 0.857237 & -0.173487 \tabularnewline
89 & 2.1 & 2.01003 & 1.965 & 0.0450347 & 0.0899653 \tabularnewline
90 & 1.55 & 1.40146 & 1.94083 & -0.53937 & 0.148537 \tabularnewline
91 & 1.42 & NA & NA & -0.65193 & NA \tabularnewline
92 & 1.12 & NA & NA & -0.834906 & NA \tabularnewline
93 & 1.12 & NA & NA & -0.611751 & NA \tabularnewline
94 & 1.41 & NA & NA & -0.253656 & NA \tabularnewline
95 & 1.56 & NA & NA & -0.126453 & NA \tabularnewline
96 & 1.8 & NA & NA & 0.104737 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278554&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]2.08[/C][C]NA[/C][C]NA[/C][C]0.652237[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.09[/C][C]NA[/C][C]NA[/C][C]0.634916[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.36[/C][C]NA[/C][C]NA[/C][C]0.723904[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.99[/C][C]NA[/C][C]NA[/C][C]0.857237[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.75[/C][C]NA[/C][C]NA[/C][C]0.0450347[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.58[/C][C]NA[/C][C]NA[/C][C]-0.53937[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.69[/C][C]1.41515[/C][C]2.06708[/C][C]-0.65193[/C][C]0.274846[/C][/ROW]
[ROW][C]8[/C][C]1.3[/C][C]1.28218[/C][C]2.11708[/C][C]-0.834906[/C][C]0.0178224[/C][/ROW]
[ROW][C]9[/C][C]1.97[/C][C]1.5295[/C][C]2.14125[/C][C]-0.611751[/C][C]0.440501[/C][/ROW]
[ROW][C]10[/C][C]1.84[/C][C]1.91551[/C][C]2.16917[/C][C]-0.253656[/C][C]-0.0755109[/C][/ROW]
[ROW][C]11[/C][C]1.96[/C][C]2.03855[/C][C]2.165[/C][C]-0.126453[/C][C]-0.0785466[/C][/ROW]
[ROW][C]12[/C][C]1.86[/C][C]2.23432[/C][C]2.12958[/C][C]0.104737[/C][C]-0.37432[/C][/ROW]
[ROW][C]13[/C][C]2.75[/C][C]2.76432[/C][C]2.11208[/C][C]0.652237[/C][C]-0.0143204[/C][/ROW]
[ROW][C]14[/C][C]2.62[/C][C]2.73492[/C][C]2.1[/C][C]0.634916[/C][C]-0.114916[/C][/ROW]
[ROW][C]15[/C][C]2.41[/C][C]2.80765[/C][C]2.08375[/C][C]0.723904[/C][C]-0.397654[/C][/ROW]
[ROW][C]16[/C][C]3.61[/C][C]2.93557[/C][C]2.07833[/C][C]0.857237[/C][C]0.67443[/C][/ROW]
[ROW][C]17[/C][C]2.03[/C][C]2.14712[/C][C]2.10208[/C][C]0.0450347[/C][C]-0.117118[/C][/ROW]
[ROW][C]18[/C][C]1.45[/C][C]1.60396[/C][C]2.14333[/C][C]-0.53937[/C][C]-0.153963[/C][/ROW]
[ROW][C]19[/C][C]1.4[/C][C]1.5114[/C][C]2.16333[/C][C]-0.65193[/C][C]-0.111404[/C][/ROW]
[ROW][C]20[/C][C]1.3[/C][C]1.29634[/C][C]2.13125[/C][C]-0.834906[/C][C]0.00365575[/C][/ROW]
[ROW][C]21[/C][C]1.58[/C][C]1.492[/C][C]2.10375[/C][C]-0.611751[/C][C]0.088001[/C][/ROW]
[ROW][C]22[/C][C]2.1[/C][C]1.80426[/C][C]2.05792[/C][C]-0.253656[/C][C]0.295739[/C][/ROW]
[ROW][C]23[/C][C]2.27[/C][C]1.8923[/C][C]2.01875[/C][C]-0.126453[/C][C]0.377703[/C][/ROW]
[ROW][C]24[/C][C]2.54[/C][C]2.13307[/C][C]2.02833[/C][C]0.104737[/C][C]0.40693[/C][/ROW]
[ROW][C]25[/C][C]2.55[/C][C]2.69349[/C][C]2.04125[/C][C]0.652237[/C][C]-0.143487[/C][/ROW]
[ROW][C]26[/C][C]2.05[/C][C]2.67492[/C][C]2.04[/C][C]0.634916[/C][C]-0.624916[/C][/ROW]
[ROW][C]27[/C][C]2.32[/C][C]2.74849[/C][C]2.02458[/C][C]0.723904[/C][C]-0.428487[/C][/ROW]
[ROW][C]28[/C][C]2.6[/C][C]2.87724[/C][C]2.02[/C][C]0.857237[/C][C]-0.277237[/C][/ROW]
[ROW][C]29[/C][C]2.1[/C][C]2.05462[/C][C]2.00958[/C][C]0.0450347[/C][C]0.0453819[/C][/ROW]
[ROW][C]30[/C][C]1.61[/C][C]1.44521[/C][C]1.98458[/C][C]-0.53937[/C][C]0.164787[/C][/ROW]
[ROW][C]31[/C][C]1.55[/C][C]1.31557[/C][C]1.9675[/C][C]-0.65193[/C][C]0.23443[/C][/ROW]
[ROW][C]32[/C][C]1.12[/C][C]1.13301[/C][C]1.96792[/C][C]-0.834906[/C][C]-0.0130109[/C][/ROW]
[ROW][C]33[/C][C]1.39[/C][C]1.37325[/C][C]1.985[/C][C]-0.611751[/C][C]0.016751[/C][/ROW]
[ROW][C]34[/C][C]2.18[/C][C]1.75468[/C][C]2.00833[/C][C]-0.253656[/C][C]0.425322[/C][/ROW]
[ROW][C]35[/C][C]1.94[/C][C]1.89521[/C][C]2.02167[/C][C]-0.126453[/C][C]0.0447867[/C][/ROW]
[ROW][C]36[/C][C]2.27[/C][C]2.11599[/C][C]2.01125[/C][C]0.104737[/C][C]0.154013[/C][/ROW]
[ROW][C]37[/C][C]2.41[/C][C]2.63224[/C][C]1.98[/C][C]0.652237[/C][C]-0.222237[/C][/ROW]
[ROW][C]38[/C][C]2.2[/C][C]2.58408[/C][C]1.94917[/C][C]0.634916[/C][C]-0.384082[/C][/ROW]
[ROW][C]39[/C][C]2.58[/C][C]2.64599[/C][C]1.92208[/C][C]0.723904[/C][C]-0.0659871[/C][/ROW]
[ROW][C]40[/C][C]2.9[/C][C]2.7364[/C][C]1.87917[/C][C]0.857237[/C][C]0.163596[/C][/ROW]
[ROW][C]41[/C][C]2.12[/C][C]1.87045[/C][C]1.82542[/C][C]0.0450347[/C][C]0.249549[/C][/ROW]
[ROW][C]42[/C][C]1.34[/C][C]1.22438[/C][C]1.76375[/C][C]-0.53937[/C][C]0.11562[/C][/ROW]
[ROW][C]43[/C][C]1.07[/C][C]1.08515[/C][C]1.73708[/C][C]-0.65193[/C][C]-0.0151538[/C][/ROW]
[ROW][C]44[/C][C]0.86[/C][C]0.933844[/C][C]1.76875[/C][C]-0.834906[/C][C]-0.0738442[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]1.21117[/C][C]1.82292[/C][C]-0.611751[/C][C]-0.211166[/C][/ROW]
[ROW][C]46[/C][C]1.54[/C][C]1.61218[/C][C]1.86583[/C][C]-0.253656[/C][C]-0.0721776[/C][/ROW]
[ROW][C]47[/C][C]1.29[/C][C]1.7498[/C][C]1.87625[/C][C]-0.126453[/C][C]-0.459797[/C][/ROW]
[ROW][C]48[/C][C]1.44[/C][C]1.98224[/C][C]1.8775[/C][C]0.104737[/C][C]-0.542237[/C][/ROW]
[ROW][C]49[/C][C]2.6[/C][C]2.54807[/C][C]1.89583[/C][C]0.652237[/C][C]0.0519296[/C][/ROW]
[ROW][C]50[/C][C]2.77[/C][C]2.56325[/C][C]1.92833[/C][C]0.634916[/C][C]0.206751[/C][/ROW]
[ROW][C]51[/C][C]3.31[/C][C]2.69432[/C][C]1.97042[/C][C]0.723904[/C][C]0.61568[/C][/ROW]
[ROW][C]52[/C][C]3.2[/C][C]2.85807[/C][C]2.00083[/C][C]0.857237[/C][C]0.34193[/C][/ROW]
[ROW][C]53[/C][C]2.07[/C][C]2.0817[/C][C]2.03667[/C][C]0.0450347[/C][C]-0.0117014[/C][/ROW]
[ROW][C]54[/C][C]1.42[/C][C]1.5723[/C][C]2.11167[/C][C]-0.53937[/C][C]-0.152297[/C][/ROW]
[ROW][C]55[/C][C]1.43[/C][C]1.51057[/C][C]2.1625[/C][C]-0.65193[/C][C]-0.0805704[/C][/ROW]
[ROW][C]56[/C][C]1.28[/C][C]1.34551[/C][C]2.18042[/C][C]-0.834906[/C][C]-0.0655109[/C][/ROW]
[ROW][C]57[/C][C]1.59[/C][C]1.55492[/C][C]2.16667[/C][C]-0.611751[/C][C]0.0350843[/C][/ROW]
[ROW][C]58[/C][C]1.68[/C][C]1.85051[/C][C]2.10417[/C][C]-0.253656[/C][C]-0.170511[/C][/ROW]
[ROW][C]59[/C][C]2.01[/C][C]1.92438[/C][C]2.05083[/C][C]-0.126453[/C][C]0.08562[/C][/ROW]
[ROW][C]60[/C][C]2.52[/C][C]2.12307[/C][C]2.01833[/C][C]0.104737[/C][C]0.39693[/C][/ROW]
[ROW][C]61[/C][C]2.74[/C][C]2.63599[/C][C]1.98375[/C][C]0.652237[/C][C]0.104013[/C][/ROW]
[ROW][C]62[/C][C]3.06[/C][C]2.58242[/C][C]1.9475[/C][C]0.634916[/C][C]0.477584[/C][/ROW]
[ROW][C]63[/C][C]2.69[/C][C]2.62807[/C][C]1.90417[/C][C]0.723904[/C][C]0.0619296[/C][/ROW]
[ROW][C]64[/C][C]2.32[/C][C]2.71974[/C][C]1.8625[/C][C]0.857237[/C][C]-0.399737[/C][/ROW]
[ROW][C]65[/C][C]1.67[/C][C]1.88378[/C][C]1.83875[/C][C]0.0450347[/C][C]-0.213785[/C][/ROW]
[ROW][C]66[/C][C]1.04[/C][C]1.26938[/C][C]1.80875[/C][C]-0.53937[/C][C]-0.22938[/C][/ROW]
[ROW][C]67[/C][C]0.98[/C][C]1.13307[/C][C]1.785[/C][C]-0.65193[/C][C]-0.15307[/C][/ROW]
[ROW][C]68[/C][C]0.86[/C][C]0.940094[/C][C]1.775[/C][C]-0.834906[/C][C]-0.0800942[/C][/ROW]
[ROW][C]69[/C][C]0.97[/C][C]1.16408[/C][C]1.77583[/C][C]-0.611751[/C][C]-0.194082[/C][/ROW]
[ROW][C]70[/C][C]1.3[/C][C]1.54134[/C][C]1.795[/C][C]-0.253656[/C][C]-0.241344[/C][/ROW]
[ROW][C]71[/C][C]1.82[/C][C]1.69438[/C][C]1.82083[/C][C]-0.126453[/C][C]0.12562[/C][/ROW]
[ROW][C]72[/C][C]1.99[/C][C]1.96557[/C][C]1.86083[/C][C]0.104737[/C][C]0.0244296[/C][/ROW]
[ROW][C]73[/C][C]2.7[/C][C]2.5489[/C][C]1.89667[/C][C]0.652237[/C][C]0.151096[/C][/ROW]
[ROW][C]74[/C][C]2.86[/C][C]2.56742[/C][C]1.9325[/C][C]0.634916[/C][C]0.292584[/C][/ROW]
[ROW][C]75[/C][C]2.91[/C][C]2.69307[/C][C]1.96917[/C][C]0.723904[/C][C]0.21693[/C][/ROW]
[ROW][C]76[/C][C]2.56[/C][C]2.85307[/C][C]1.99583[/C][C]0.857237[/C][C]-0.29307[/C][/ROW]
[ROW][C]77[/C][C]2.05[/C][C]2.05587[/C][C]2.01083[/C][C]0.0450347[/C][C]-0.00586806[/C][/ROW]
[ROW][C]78[/C][C]1.62[/C][C]1.47688[/C][C]2.01625[/C][C]-0.53937[/C][C]0.14312[/C][/ROW]
[ROW][C]79[/C][C]1.26[/C][C]1.37265[/C][C]2.02458[/C][C]-0.65193[/C][C]-0.112654[/C][/ROW]
[ROW][C]80[/C][C]1.44[/C][C]1.19259[/C][C]2.0275[/C][C]-0.834906[/C][C]0.247406[/C][/ROW]
[ROW][C]81[/C][C]1.27[/C][C]1.40867[/C][C]2.02042[/C][C]-0.611751[/C][C]-0.138666[/C][/ROW]
[ROW][C]82[/C][C]1.64[/C][C]1.76509[/C][C]2.01875[/C][C]-0.253656[/C][C]-0.125094[/C][/ROW]
[ROW][C]83[/C][C]1.84[/C][C]1.89896[/C][C]2.02542[/C][C]-0.126453[/C][C]-0.0589633[/C][/ROW]
[ROW][C]84[/C][C]2.1[/C][C]2.12932[/C][C]2.02458[/C][C]0.104737[/C][C]-0.0293204[/C][/ROW]
[ROW][C]85[/C][C]2.79[/C][C]2.68057[/C][C]2.02833[/C][C]0.652237[/C][C]0.10943[/C][/ROW]
[ROW][C]86[/C][C]2.84[/C][C]2.65658[/C][C]2.02167[/C][C]0.634916[/C][C]0.183418[/C][/ROW]
[ROW][C]87[/C][C]2.76[/C][C]2.72599[/C][C]2.00208[/C][C]0.723904[/C][C]0.0340129[/C][/ROW]
[ROW][C]88[/C][C]2.67[/C][C]2.84349[/C][C]1.98625[/C][C]0.857237[/C][C]-0.173487[/C][/ROW]
[ROW][C]89[/C][C]2.1[/C][C]2.01003[/C][C]1.965[/C][C]0.0450347[/C][C]0.0899653[/C][/ROW]
[ROW][C]90[/C][C]1.55[/C][C]1.40146[/C][C]1.94083[/C][C]-0.53937[/C][C]0.148537[/C][/ROW]
[ROW][C]91[/C][C]1.42[/C][C]NA[/C][C]NA[/C][C]-0.65193[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]1.12[/C][C]NA[/C][C]NA[/C][C]-0.834906[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]1.12[/C][C]NA[/C][C]NA[/C][C]-0.611751[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]1.41[/C][C]NA[/C][C]NA[/C][C]-0.253656[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]1.56[/C][C]NA[/C][C]NA[/C][C]-0.126453[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]0.104737[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278554&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278554&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	2.08	NA	NA	0.652237	NA
2	2.09	NA	NA	0.634916	NA
3	2.36	NA	NA	0.723904	NA
4	2.99	NA	NA	0.857237	NA
5	2.75	NA	NA	0.0450347	NA
6	1.58	NA	NA	-0.53937	NA
7	1.69	1.41515	2.06708	-0.65193	0.274846
8	1.3	1.28218	2.11708	-0.834906	0.0178224
9	1.97	1.5295	2.14125	-0.611751	0.440501
10	1.84	1.91551	2.16917	-0.253656	-0.0755109
11	1.96	2.03855	2.165	-0.126453	-0.0785466
12	1.86	2.23432	2.12958	0.104737	-0.37432
13	2.75	2.76432	2.11208	0.652237	-0.0143204
14	2.62	2.73492	2.1	0.634916	-0.114916
15	2.41	2.80765	2.08375	0.723904	-0.397654
16	3.61	2.93557	2.07833	0.857237	0.67443
17	2.03	2.14712	2.10208	0.0450347	-0.117118
18	1.45	1.60396	2.14333	-0.53937	-0.153963
19	1.4	1.5114	2.16333	-0.65193	-0.111404
20	1.3	1.29634	2.13125	-0.834906	0.00365575
21	1.58	1.492	2.10375	-0.611751	0.088001
22	2.1	1.80426	2.05792	-0.253656	0.295739
23	2.27	1.8923	2.01875	-0.126453	0.377703
24	2.54	2.13307	2.02833	0.104737	0.40693
25	2.55	2.69349	2.04125	0.652237	-0.143487
26	2.05	2.67492	2.04	0.634916	-0.624916
27	2.32	2.74849	2.02458	0.723904	-0.428487
28	2.6	2.87724	2.02	0.857237	-0.277237
29	2.1	2.05462	2.00958	0.0450347	0.0453819
30	1.61	1.44521	1.98458	-0.53937	0.164787
31	1.55	1.31557	1.9675	-0.65193	0.23443
32	1.12	1.13301	1.96792	-0.834906	-0.0130109
33	1.39	1.37325	1.985	-0.611751	0.016751
34	2.18	1.75468	2.00833	-0.253656	0.425322
35	1.94	1.89521	2.02167	-0.126453	0.0447867
36	2.27	2.11599	2.01125	0.104737	0.154013
37	2.41	2.63224	1.98	0.652237	-0.222237
38	2.2	2.58408	1.94917	0.634916	-0.384082
39	2.58	2.64599	1.92208	0.723904	-0.0659871
40	2.9	2.7364	1.87917	0.857237	0.163596
41	2.12	1.87045	1.82542	0.0450347	0.249549
42	1.34	1.22438	1.76375	-0.53937	0.11562
43	1.07	1.08515	1.73708	-0.65193	-0.0151538
44	0.86	0.933844	1.76875	-0.834906	-0.0738442
45	1	1.21117	1.82292	-0.611751	-0.211166
46	1.54	1.61218	1.86583	-0.253656	-0.0721776
47	1.29	1.7498	1.87625	-0.126453	-0.459797
48	1.44	1.98224	1.8775	0.104737	-0.542237
49	2.6	2.54807	1.89583	0.652237	0.0519296
50	2.77	2.56325	1.92833	0.634916	0.206751
51	3.31	2.69432	1.97042	0.723904	0.61568
52	3.2	2.85807	2.00083	0.857237	0.34193
53	2.07	2.0817	2.03667	0.0450347	-0.0117014
54	1.42	1.5723	2.11167	-0.53937	-0.152297
55	1.43	1.51057	2.1625	-0.65193	-0.0805704
56	1.28	1.34551	2.18042	-0.834906	-0.0655109
57	1.59	1.55492	2.16667	-0.611751	0.0350843
58	1.68	1.85051	2.10417	-0.253656	-0.170511
59	2.01	1.92438	2.05083	-0.126453	0.08562
60	2.52	2.12307	2.01833	0.104737	0.39693
61	2.74	2.63599	1.98375	0.652237	0.104013
62	3.06	2.58242	1.9475	0.634916	0.477584
63	2.69	2.62807	1.90417	0.723904	0.0619296
64	2.32	2.71974	1.8625	0.857237	-0.399737
65	1.67	1.88378	1.83875	0.0450347	-0.213785
66	1.04	1.26938	1.80875	-0.53937	-0.22938
67	0.98	1.13307	1.785	-0.65193	-0.15307
68	0.86	0.940094	1.775	-0.834906	-0.0800942
69	0.97	1.16408	1.77583	-0.611751	-0.194082
70	1.3	1.54134	1.795	-0.253656	-0.241344
71	1.82	1.69438	1.82083	-0.126453	0.12562
72	1.99	1.96557	1.86083	0.104737	0.0244296
73	2.7	2.5489	1.89667	0.652237	0.151096
74	2.86	2.56742	1.9325	0.634916	0.292584
75	2.91	2.69307	1.96917	0.723904	0.21693
76	2.56	2.85307	1.99583	0.857237	-0.29307
77	2.05	2.05587	2.01083	0.0450347	-0.00586806
78	1.62	1.47688	2.01625	-0.53937	0.14312
79	1.26	1.37265	2.02458	-0.65193	-0.112654
80	1.44	1.19259	2.0275	-0.834906	0.247406
81	1.27	1.40867	2.02042	-0.611751	-0.138666
82	1.64	1.76509	2.01875	-0.253656	-0.125094
83	1.84	1.89896	2.02542	-0.126453	-0.0589633
84	2.1	2.12932	2.02458	0.104737	-0.0293204
85	2.79	2.68057	2.02833	0.652237	0.10943
86	2.84	2.65658	2.02167	0.634916	0.183418
87	2.76	2.72599	2.00208	0.723904	0.0340129
88	2.67	2.84349	1.98625	0.857237	-0.173487
89	2.1	2.01003	1.965	0.0450347	0.0899653
90	1.55	1.40146	1.94083	-0.53937	0.148537
91	1.42	NA	NA	-0.65193	NA
92	1.12	NA	NA	-0.834906	NA
93	1.12	NA	NA	-0.611751	NA
94	1.41	NA	NA	-0.253656	NA
95	1.56	NA	NA	-0.126453	NA
96	1.8	NA	NA	0.104737	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