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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 20 May 2014 09:20:16 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/May/20/t14005920320fgwxsesfi3j5v6.htm/, Retrieved Wed, 15 May 2024 15:15:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234986, Retrieved Wed, 15 May 2024 15:15:13 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

136

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

-     [Standard Deviation Plot] [] [2014-04-28 15:57:15] [ccb4fa85fbb66dbee3adf4746bc114a3]
- RMPD    [Classical Decomposition] [] [2014-05-20 13:20:16] [c97636ecf0aef6cf672ffb6fe15d6b60] [Current]

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Dataseries X:

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2,79
3,08
3,89
3,7
4,61
5,07
5,22
4,93
5,15
4,8
3,89
3,54
3,34
2,8
1,6
1,53
0,69
-0,11
-0,67
-0,2
-0,62
-0,58
-0,31
-0,25
-0,08
0,13
0,94
1,05
1,59
2,03
2,15
2,06
2,56
2,55
2,53
2,6
2,71
2,82
2,93
2,88
2,89
3,27
3,32
3,14
3,04
3,08
3,39
3,23
3,38
3,41
3,14
2,96
2,73
2,21
2,23
2,56
2,39
2,49
2,17
2,16
1,48
1,09
1,25
1,26
1,39
1,69
1,55
1,19
1,08
0,93
0,98
1,01

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	'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234986&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234986&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	3 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.79	NA	NA	-0.0163403	NA
2	3.08	NA	NA	-0.0705903	NA
3	3.89	NA	NA	-0.0835069	NA
4	3.7	NA	NA	-0.0533403	NA
5	4.61	NA	NA	-0.0748403	NA
6	5.07	NA	NA	-0.0695069	NA
7	5.22	4.24374	4.24542	-0.00167361	0.976257
8	4.93	4.33049	4.25667	0.0738264	0.599507
9	5.15	4.26799	4.14958	0.11841	0.882007
10	4.8	4.08849	3.96375	0.124743	0.711507
11	3.89	3.74791	3.71	0.0379097	0.14209
12	3.54	3.34574	3.33083	0.0149097	0.194257
13	3.34	2.85324	2.86958	-0.0163403	0.486757
14	2.8	2.33983	2.41042	-0.0705903	0.460174
15	1.6	1.87274	1.95625	-0.0835069	-0.272743
16	1.53	1.43833	1.49167	-0.0533403	0.0916736
17	0.69	1.01766	1.0925	-0.0748403	-0.32766
18	-0.11	0.690076	0.759583	-0.0695069	-0.800076
19	-0.67	0.457493	0.459167	-0.00167361	-1.12749
20	-0.2	0.279243	0.205417	0.0738264	-0.479243
21	-0.62	0.185076	0.0666667	0.11841	-0.805076
22	-0.58	0.14391	0.0191667	0.124743	-0.72391
23	-0.31	0.0745764	0.0366667	0.0379097	-0.384576
24	-0.25	0.178243	0.163333	0.0149097	-0.428243
25	-0.08	0.35366	0.37	-0.0163403	-0.43366
26	0.13	0.511076	0.581667	-0.0705903	-0.381076
27	0.94	0.724826	0.808333	-0.0835069	0.215174
28	1.05	1.01791	1.07125	-0.0533403	0.0320903
29	1.59	1.24516	1.32	-0.0748403	0.34484
30	2.03	1.48758	1.55708	-0.0695069	0.542424
31	2.15	1.79041	1.79208	-0.00167361	0.35959
32	2.06	2.09424	2.02042	0.0738264	-0.0342431
33	2.56	2.33383	2.21542	0.11841	0.226174
34	2.55	2.49933	2.37458	0.124743	0.0506736
35	2.53	2.54291	2.505	0.0379097	-0.0129097
36	2.6	2.62574	2.61083	0.0149097	-0.0257431
37	2.71	2.69491	2.71125	-0.0163403	0.0150903
38	2.82	2.73441	2.805	-0.0705903	0.0855903
39	2.93	2.78649	2.87	-0.0835069	0.143507
40	2.88	2.85874	2.91208	-0.0533403	0.0212569
41	2.89	2.89516	2.97	-0.0748403	-0.00515972
42	3.27	2.96258	3.03208	-0.0695069	0.307424
43	3.32	3.08458	3.08625	-0.00167361	0.235424
44	3.14	3.21258	3.13875	0.0738264	-0.0725764
45	3.04	3.29049	3.17208	0.11841	-0.250493
46	3.08	3.30891	3.18417	0.124743	-0.22891
47	3.39	3.21874	3.18083	0.0379097	0.171257
48	3.23	3.14491	3.13	0.0149097	0.0850903
49	3.38	3.02408	3.04042	-0.0163403	0.355924
50	3.41	2.90024	2.97083	-0.0705903	0.509757
51	3.14	2.83608	2.91958	-0.0835069	0.303924
52	2.96	2.81458	2.86792	-0.0533403	0.145424
53	2.73	2.71766	2.7925	-0.0748403	0.0123403
54	2.21	2.62758	2.69708	-0.0695069	-0.417576
55	2.23	2.57166	2.57333	-0.00167361	-0.34166
56	2.56	2.47133	2.3975	0.0738264	0.0886736
57	2.39	2.34049	2.22208	0.11841	0.0495069
58	2.49	2.19724	2.0725	0.124743	0.292757
59	2.17	1.98374	1.94583	0.0379097	0.186257
60	2.16	1.88324	1.86833	0.0149097	0.276757
61	1.48	1.80199	1.81833	-0.0163403	-0.321993
62	1.09	1.66233	1.73292	-0.0705903	-0.572326
63	1.25	1.53774	1.62125	-0.0835069	-0.287743
64	1.26	1.44833	1.50167	-0.0533403	-0.188326
65	1.39	1.31224	1.38708	-0.0748403	0.0777569
66	1.69	1.22008	1.28958	-0.0695069	0.469924
67	1.55	NA	NA	-0.00167361	NA
68	1.19	NA	NA	0.0738264	NA
69	1.08	NA	NA	0.11841	NA
70	0.93	NA	NA	0.124743	NA
71	0.98	NA	NA	0.0379097	NA
72	1.01	NA	NA	0.0149097	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.79 & NA & NA & -0.0163403 & NA \tabularnewline
2 & 3.08 & NA & NA & -0.0705903 & NA \tabularnewline
3 & 3.89 & NA & NA & -0.0835069 & NA \tabularnewline
4 & 3.7 & NA & NA & -0.0533403 & NA \tabularnewline
5 & 4.61 & NA & NA & -0.0748403 & NA \tabularnewline
6 & 5.07 & NA & NA & -0.0695069 & NA \tabularnewline
7 & 5.22 & 4.24374 & 4.24542 & -0.00167361 & 0.976257 \tabularnewline
8 & 4.93 & 4.33049 & 4.25667 & 0.0738264 & 0.599507 \tabularnewline
9 & 5.15 & 4.26799 & 4.14958 & 0.11841 & 0.882007 \tabularnewline
10 & 4.8 & 4.08849 & 3.96375 & 0.124743 & 0.711507 \tabularnewline
11 & 3.89 & 3.74791 & 3.71 & 0.0379097 & 0.14209 \tabularnewline
12 & 3.54 & 3.34574 & 3.33083 & 0.0149097 & 0.194257 \tabularnewline
13 & 3.34 & 2.85324 & 2.86958 & -0.0163403 & 0.486757 \tabularnewline
14 & 2.8 & 2.33983 & 2.41042 & -0.0705903 & 0.460174 \tabularnewline
15 & 1.6 & 1.87274 & 1.95625 & -0.0835069 & -0.272743 \tabularnewline
16 & 1.53 & 1.43833 & 1.49167 & -0.0533403 & 0.0916736 \tabularnewline
17 & 0.69 & 1.01766 & 1.0925 & -0.0748403 & -0.32766 \tabularnewline
18 & -0.11 & 0.690076 & 0.759583 & -0.0695069 & -0.800076 \tabularnewline
19 & -0.67 & 0.457493 & 0.459167 & -0.00167361 & -1.12749 \tabularnewline
20 & -0.2 & 0.279243 & 0.205417 & 0.0738264 & -0.479243 \tabularnewline
21 & -0.62 & 0.185076 & 0.0666667 & 0.11841 & -0.805076 \tabularnewline
22 & -0.58 & 0.14391 & 0.0191667 & 0.124743 & -0.72391 \tabularnewline
23 & -0.31 & 0.0745764 & 0.0366667 & 0.0379097 & -0.384576 \tabularnewline
24 & -0.25 & 0.178243 & 0.163333 & 0.0149097 & -0.428243 \tabularnewline
25 & -0.08 & 0.35366 & 0.37 & -0.0163403 & -0.43366 \tabularnewline
26 & 0.13 & 0.511076 & 0.581667 & -0.0705903 & -0.381076 \tabularnewline
27 & 0.94 & 0.724826 & 0.808333 & -0.0835069 & 0.215174 \tabularnewline
28 & 1.05 & 1.01791 & 1.07125 & -0.0533403 & 0.0320903 \tabularnewline
29 & 1.59 & 1.24516 & 1.32 & -0.0748403 & 0.34484 \tabularnewline
30 & 2.03 & 1.48758 & 1.55708 & -0.0695069 & 0.542424 \tabularnewline
31 & 2.15 & 1.79041 & 1.79208 & -0.00167361 & 0.35959 \tabularnewline
32 & 2.06 & 2.09424 & 2.02042 & 0.0738264 & -0.0342431 \tabularnewline
33 & 2.56 & 2.33383 & 2.21542 & 0.11841 & 0.226174 \tabularnewline
34 & 2.55 & 2.49933 & 2.37458 & 0.124743 & 0.0506736 \tabularnewline
35 & 2.53 & 2.54291 & 2.505 & 0.0379097 & -0.0129097 \tabularnewline
36 & 2.6 & 2.62574 & 2.61083 & 0.0149097 & -0.0257431 \tabularnewline
37 & 2.71 & 2.69491 & 2.71125 & -0.0163403 & 0.0150903 \tabularnewline
38 & 2.82 & 2.73441 & 2.805 & -0.0705903 & 0.0855903 \tabularnewline
39 & 2.93 & 2.78649 & 2.87 & -0.0835069 & 0.143507 \tabularnewline
40 & 2.88 & 2.85874 & 2.91208 & -0.0533403 & 0.0212569 \tabularnewline
41 & 2.89 & 2.89516 & 2.97 & -0.0748403 & -0.00515972 \tabularnewline
42 & 3.27 & 2.96258 & 3.03208 & -0.0695069 & 0.307424 \tabularnewline
43 & 3.32 & 3.08458 & 3.08625 & -0.00167361 & 0.235424 \tabularnewline
44 & 3.14 & 3.21258 & 3.13875 & 0.0738264 & -0.0725764 \tabularnewline
45 & 3.04 & 3.29049 & 3.17208 & 0.11841 & -0.250493 \tabularnewline
46 & 3.08 & 3.30891 & 3.18417 & 0.124743 & -0.22891 \tabularnewline
47 & 3.39 & 3.21874 & 3.18083 & 0.0379097 & 0.171257 \tabularnewline
48 & 3.23 & 3.14491 & 3.13 & 0.0149097 & 0.0850903 \tabularnewline
49 & 3.38 & 3.02408 & 3.04042 & -0.0163403 & 0.355924 \tabularnewline
50 & 3.41 & 2.90024 & 2.97083 & -0.0705903 & 0.509757 \tabularnewline
51 & 3.14 & 2.83608 & 2.91958 & -0.0835069 & 0.303924 \tabularnewline
52 & 2.96 & 2.81458 & 2.86792 & -0.0533403 & 0.145424 \tabularnewline
53 & 2.73 & 2.71766 & 2.7925 & -0.0748403 & 0.0123403 \tabularnewline
54 & 2.21 & 2.62758 & 2.69708 & -0.0695069 & -0.417576 \tabularnewline
55 & 2.23 & 2.57166 & 2.57333 & -0.00167361 & -0.34166 \tabularnewline
56 & 2.56 & 2.47133 & 2.3975 & 0.0738264 & 0.0886736 \tabularnewline
57 & 2.39 & 2.34049 & 2.22208 & 0.11841 & 0.0495069 \tabularnewline
58 & 2.49 & 2.19724 & 2.0725 & 0.124743 & 0.292757 \tabularnewline
59 & 2.17 & 1.98374 & 1.94583 & 0.0379097 & 0.186257 \tabularnewline
60 & 2.16 & 1.88324 & 1.86833 & 0.0149097 & 0.276757 \tabularnewline
61 & 1.48 & 1.80199 & 1.81833 & -0.0163403 & -0.321993 \tabularnewline
62 & 1.09 & 1.66233 & 1.73292 & -0.0705903 & -0.572326 \tabularnewline
63 & 1.25 & 1.53774 & 1.62125 & -0.0835069 & -0.287743 \tabularnewline
64 & 1.26 & 1.44833 & 1.50167 & -0.0533403 & -0.188326 \tabularnewline
65 & 1.39 & 1.31224 & 1.38708 & -0.0748403 & 0.0777569 \tabularnewline
66 & 1.69 & 1.22008 & 1.28958 & -0.0695069 & 0.469924 \tabularnewline
67 & 1.55 & NA & NA & -0.00167361 & NA \tabularnewline
68 & 1.19 & NA & NA & 0.0738264 & NA \tabularnewline
69 & 1.08 & NA & NA & 0.11841 & NA \tabularnewline
70 & 0.93 & NA & NA & 0.124743 & NA \tabularnewline
71 & 0.98 & NA & NA & 0.0379097 & NA \tabularnewline
72 & 1.01 & NA & NA & 0.0149097 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234986&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]2.79[/C][C]NA[/C][C]NA[/C][C]-0.0163403[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3.08[/C][C]NA[/C][C]NA[/C][C]-0.0705903[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.89[/C][C]NA[/C][C]NA[/C][C]-0.0835069[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3.7[/C][C]NA[/C][C]NA[/C][C]-0.0533403[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]4.61[/C][C]NA[/C][C]NA[/C][C]-0.0748403[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.07[/C][C]NA[/C][C]NA[/C][C]-0.0695069[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.22[/C][C]4.24374[/C][C]4.24542[/C][C]-0.00167361[/C][C]0.976257[/C][/ROW]
[ROW][C]8[/C][C]4.93[/C][C]4.33049[/C][C]4.25667[/C][C]0.0738264[/C][C]0.599507[/C][/ROW]
[ROW][C]9[/C][C]5.15[/C][C]4.26799[/C][C]4.14958[/C][C]0.11841[/C][C]0.882007[/C][/ROW]
[ROW][C]10[/C][C]4.8[/C][C]4.08849[/C][C]3.96375[/C][C]0.124743[/C][C]0.711507[/C][/ROW]
[ROW][C]11[/C][C]3.89[/C][C]3.74791[/C][C]3.71[/C][C]0.0379097[/C][C]0.14209[/C][/ROW]
[ROW][C]12[/C][C]3.54[/C][C]3.34574[/C][C]3.33083[/C][C]0.0149097[/C][C]0.194257[/C][/ROW]
[ROW][C]13[/C][C]3.34[/C][C]2.85324[/C][C]2.86958[/C][C]-0.0163403[/C][C]0.486757[/C][/ROW]
[ROW][C]14[/C][C]2.8[/C][C]2.33983[/C][C]2.41042[/C][C]-0.0705903[/C][C]0.460174[/C][/ROW]
[ROW][C]15[/C][C]1.6[/C][C]1.87274[/C][C]1.95625[/C][C]-0.0835069[/C][C]-0.272743[/C][/ROW]
[ROW][C]16[/C][C]1.53[/C][C]1.43833[/C][C]1.49167[/C][C]-0.0533403[/C][C]0.0916736[/C][/ROW]
[ROW][C]17[/C][C]0.69[/C][C]1.01766[/C][C]1.0925[/C][C]-0.0748403[/C][C]-0.32766[/C][/ROW]
[ROW][C]18[/C][C]-0.11[/C][C]0.690076[/C][C]0.759583[/C][C]-0.0695069[/C][C]-0.800076[/C][/ROW]
[ROW][C]19[/C][C]-0.67[/C][C]0.457493[/C][C]0.459167[/C][C]-0.00167361[/C][C]-1.12749[/C][/ROW]
[ROW][C]20[/C][C]-0.2[/C][C]0.279243[/C][C]0.205417[/C][C]0.0738264[/C][C]-0.479243[/C][/ROW]
[ROW][C]21[/C][C]-0.62[/C][C]0.185076[/C][C]0.0666667[/C][C]0.11841[/C][C]-0.805076[/C][/ROW]
[ROW][C]22[/C][C]-0.58[/C][C]0.14391[/C][C]0.0191667[/C][C]0.124743[/C][C]-0.72391[/C][/ROW]
[ROW][C]23[/C][C]-0.31[/C][C]0.0745764[/C][C]0.0366667[/C][C]0.0379097[/C][C]-0.384576[/C][/ROW]
[ROW][C]24[/C][C]-0.25[/C][C]0.178243[/C][C]0.163333[/C][C]0.0149097[/C][C]-0.428243[/C][/ROW]
[ROW][C]25[/C][C]-0.08[/C][C]0.35366[/C][C]0.37[/C][C]-0.0163403[/C][C]-0.43366[/C][/ROW]
[ROW][C]26[/C][C]0.13[/C][C]0.511076[/C][C]0.581667[/C][C]-0.0705903[/C][C]-0.381076[/C][/ROW]
[ROW][C]27[/C][C]0.94[/C][C]0.724826[/C][C]0.808333[/C][C]-0.0835069[/C][C]0.215174[/C][/ROW]
[ROW][C]28[/C][C]1.05[/C][C]1.01791[/C][C]1.07125[/C][C]-0.0533403[/C][C]0.0320903[/C][/ROW]
[ROW][C]29[/C][C]1.59[/C][C]1.24516[/C][C]1.32[/C][C]-0.0748403[/C][C]0.34484[/C][/ROW]
[ROW][C]30[/C][C]2.03[/C][C]1.48758[/C][C]1.55708[/C][C]-0.0695069[/C][C]0.542424[/C][/ROW]
[ROW][C]31[/C][C]2.15[/C][C]1.79041[/C][C]1.79208[/C][C]-0.00167361[/C][C]0.35959[/C][/ROW]
[ROW][C]32[/C][C]2.06[/C][C]2.09424[/C][C]2.02042[/C][C]0.0738264[/C][C]-0.0342431[/C][/ROW]
[ROW][C]33[/C][C]2.56[/C][C]2.33383[/C][C]2.21542[/C][C]0.11841[/C][C]0.226174[/C][/ROW]
[ROW][C]34[/C][C]2.55[/C][C]2.49933[/C][C]2.37458[/C][C]0.124743[/C][C]0.0506736[/C][/ROW]
[ROW][C]35[/C][C]2.53[/C][C]2.54291[/C][C]2.505[/C][C]0.0379097[/C][C]-0.0129097[/C][/ROW]
[ROW][C]36[/C][C]2.6[/C][C]2.62574[/C][C]2.61083[/C][C]0.0149097[/C][C]-0.0257431[/C][/ROW]
[ROW][C]37[/C][C]2.71[/C][C]2.69491[/C][C]2.71125[/C][C]-0.0163403[/C][C]0.0150903[/C][/ROW]
[ROW][C]38[/C][C]2.82[/C][C]2.73441[/C][C]2.805[/C][C]-0.0705903[/C][C]0.0855903[/C][/ROW]
[ROW][C]39[/C][C]2.93[/C][C]2.78649[/C][C]2.87[/C][C]-0.0835069[/C][C]0.143507[/C][/ROW]
[ROW][C]40[/C][C]2.88[/C][C]2.85874[/C][C]2.91208[/C][C]-0.0533403[/C][C]0.0212569[/C][/ROW]
[ROW][C]41[/C][C]2.89[/C][C]2.89516[/C][C]2.97[/C][C]-0.0748403[/C][C]-0.00515972[/C][/ROW]
[ROW][C]42[/C][C]3.27[/C][C]2.96258[/C][C]3.03208[/C][C]-0.0695069[/C][C]0.307424[/C][/ROW]
[ROW][C]43[/C][C]3.32[/C][C]3.08458[/C][C]3.08625[/C][C]-0.00167361[/C][C]0.235424[/C][/ROW]
[ROW][C]44[/C][C]3.14[/C][C]3.21258[/C][C]3.13875[/C][C]0.0738264[/C][C]-0.0725764[/C][/ROW]
[ROW][C]45[/C][C]3.04[/C][C]3.29049[/C][C]3.17208[/C][C]0.11841[/C][C]-0.250493[/C][/ROW]
[ROW][C]46[/C][C]3.08[/C][C]3.30891[/C][C]3.18417[/C][C]0.124743[/C][C]-0.22891[/C][/ROW]
[ROW][C]47[/C][C]3.39[/C][C]3.21874[/C][C]3.18083[/C][C]0.0379097[/C][C]0.171257[/C][/ROW]
[ROW][C]48[/C][C]3.23[/C][C]3.14491[/C][C]3.13[/C][C]0.0149097[/C][C]0.0850903[/C][/ROW]
[ROW][C]49[/C][C]3.38[/C][C]3.02408[/C][C]3.04042[/C][C]-0.0163403[/C][C]0.355924[/C][/ROW]
[ROW][C]50[/C][C]3.41[/C][C]2.90024[/C][C]2.97083[/C][C]-0.0705903[/C][C]0.509757[/C][/ROW]
[ROW][C]51[/C][C]3.14[/C][C]2.83608[/C][C]2.91958[/C][C]-0.0835069[/C][C]0.303924[/C][/ROW]
[ROW][C]52[/C][C]2.96[/C][C]2.81458[/C][C]2.86792[/C][C]-0.0533403[/C][C]0.145424[/C][/ROW]
[ROW][C]53[/C][C]2.73[/C][C]2.71766[/C][C]2.7925[/C][C]-0.0748403[/C][C]0.0123403[/C][/ROW]
[ROW][C]54[/C][C]2.21[/C][C]2.62758[/C][C]2.69708[/C][C]-0.0695069[/C][C]-0.417576[/C][/ROW]
[ROW][C]55[/C][C]2.23[/C][C]2.57166[/C][C]2.57333[/C][C]-0.00167361[/C][C]-0.34166[/C][/ROW]
[ROW][C]56[/C][C]2.56[/C][C]2.47133[/C][C]2.3975[/C][C]0.0738264[/C][C]0.0886736[/C][/ROW]
[ROW][C]57[/C][C]2.39[/C][C]2.34049[/C][C]2.22208[/C][C]0.11841[/C][C]0.0495069[/C][/ROW]
[ROW][C]58[/C][C]2.49[/C][C]2.19724[/C][C]2.0725[/C][C]0.124743[/C][C]0.292757[/C][/ROW]
[ROW][C]59[/C][C]2.17[/C][C]1.98374[/C][C]1.94583[/C][C]0.0379097[/C][C]0.186257[/C][/ROW]
[ROW][C]60[/C][C]2.16[/C][C]1.88324[/C][C]1.86833[/C][C]0.0149097[/C][C]0.276757[/C][/ROW]
[ROW][C]61[/C][C]1.48[/C][C]1.80199[/C][C]1.81833[/C][C]-0.0163403[/C][C]-0.321993[/C][/ROW]
[ROW][C]62[/C][C]1.09[/C][C]1.66233[/C][C]1.73292[/C][C]-0.0705903[/C][C]-0.572326[/C][/ROW]
[ROW][C]63[/C][C]1.25[/C][C]1.53774[/C][C]1.62125[/C][C]-0.0835069[/C][C]-0.287743[/C][/ROW]
[ROW][C]64[/C][C]1.26[/C][C]1.44833[/C][C]1.50167[/C][C]-0.0533403[/C][C]-0.188326[/C][/ROW]
[ROW][C]65[/C][C]1.39[/C][C]1.31224[/C][C]1.38708[/C][C]-0.0748403[/C][C]0.0777569[/C][/ROW]
[ROW][C]66[/C][C]1.69[/C][C]1.22008[/C][C]1.28958[/C][C]-0.0695069[/C][C]0.469924[/C][/ROW]
[ROW][C]67[/C][C]1.55[/C][C]NA[/C][C]NA[/C][C]-0.00167361[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.19[/C][C]NA[/C][C]NA[/C][C]0.0738264[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.08[/C][C]NA[/C][C]NA[/C][C]0.11841[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]0.93[/C][C]NA[/C][C]NA[/C][C]0.124743[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]0.98[/C][C]NA[/C][C]NA[/C][C]0.0379097[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.01[/C][C]NA[/C][C]NA[/C][C]0.0149097[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234986&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	2.79	NA	NA	-0.0163403	NA
2	3.08	NA	NA	-0.0705903	NA
3	3.89	NA	NA	-0.0835069	NA
4	3.7	NA	NA	-0.0533403	NA
5	4.61	NA	NA	-0.0748403	NA
6	5.07	NA	NA	-0.0695069	NA
7	5.22	4.24374	4.24542	-0.00167361	0.976257
8	4.93	4.33049	4.25667	0.0738264	0.599507
9	5.15	4.26799	4.14958	0.11841	0.882007
10	4.8	4.08849	3.96375	0.124743	0.711507
11	3.89	3.74791	3.71	0.0379097	0.14209
12	3.54	3.34574	3.33083	0.0149097	0.194257
13	3.34	2.85324	2.86958	-0.0163403	0.486757
14	2.8	2.33983	2.41042	-0.0705903	0.460174
15	1.6	1.87274	1.95625	-0.0835069	-0.272743
16	1.53	1.43833	1.49167	-0.0533403	0.0916736
17	0.69	1.01766	1.0925	-0.0748403	-0.32766
18	-0.11	0.690076	0.759583	-0.0695069	-0.800076
19	-0.67	0.457493	0.459167	-0.00167361	-1.12749
20	-0.2	0.279243	0.205417	0.0738264	-0.479243
21	-0.62	0.185076	0.0666667	0.11841	-0.805076
22	-0.58	0.14391	0.0191667	0.124743	-0.72391
23	-0.31	0.0745764	0.0366667	0.0379097	-0.384576
24	-0.25	0.178243	0.163333	0.0149097	-0.428243
25	-0.08	0.35366	0.37	-0.0163403	-0.43366
26	0.13	0.511076	0.581667	-0.0705903	-0.381076
27	0.94	0.724826	0.808333	-0.0835069	0.215174
28	1.05	1.01791	1.07125	-0.0533403	0.0320903
29	1.59	1.24516	1.32	-0.0748403	0.34484
30	2.03	1.48758	1.55708	-0.0695069	0.542424
31	2.15	1.79041	1.79208	-0.00167361	0.35959
32	2.06	2.09424	2.02042	0.0738264	-0.0342431
33	2.56	2.33383	2.21542	0.11841	0.226174
34	2.55	2.49933	2.37458	0.124743	0.0506736
35	2.53	2.54291	2.505	0.0379097	-0.0129097
36	2.6	2.62574	2.61083	0.0149097	-0.0257431
37	2.71	2.69491	2.71125	-0.0163403	0.0150903
38	2.82	2.73441	2.805	-0.0705903	0.0855903
39	2.93	2.78649	2.87	-0.0835069	0.143507
40	2.88	2.85874	2.91208	-0.0533403	0.0212569
41	2.89	2.89516	2.97	-0.0748403	-0.00515972
42	3.27	2.96258	3.03208	-0.0695069	0.307424
43	3.32	3.08458	3.08625	-0.00167361	0.235424
44	3.14	3.21258	3.13875	0.0738264	-0.0725764
45	3.04	3.29049	3.17208	0.11841	-0.250493
46	3.08	3.30891	3.18417	0.124743	-0.22891
47	3.39	3.21874	3.18083	0.0379097	0.171257
48	3.23	3.14491	3.13	0.0149097	0.0850903
49	3.38	3.02408	3.04042	-0.0163403	0.355924
50	3.41	2.90024	2.97083	-0.0705903	0.509757
51	3.14	2.83608	2.91958	-0.0835069	0.303924
52	2.96	2.81458	2.86792	-0.0533403	0.145424
53	2.73	2.71766	2.7925	-0.0748403	0.0123403
54	2.21	2.62758	2.69708	-0.0695069	-0.417576
55	2.23	2.57166	2.57333	-0.00167361	-0.34166
56	2.56	2.47133	2.3975	0.0738264	0.0886736
57	2.39	2.34049	2.22208	0.11841	0.0495069
58	2.49	2.19724	2.0725	0.124743	0.292757
59	2.17	1.98374	1.94583	0.0379097	0.186257
60	2.16	1.88324	1.86833	0.0149097	0.276757
61	1.48	1.80199	1.81833	-0.0163403	-0.321993
62	1.09	1.66233	1.73292	-0.0705903	-0.572326
63	1.25	1.53774	1.62125	-0.0835069	-0.287743
64	1.26	1.44833	1.50167	-0.0533403	-0.188326
65	1.39	1.31224	1.38708	-0.0748403	0.0777569
66	1.69	1.22008	1.28958	-0.0695069	0.469924
67	1.55	NA	NA	-0.00167361	NA
68	1.19	NA	NA	0.0738264	NA
69	1.08	NA	NA	0.11841	NA
70	0.93	NA	NA	0.124743	NA
71	0.98	NA	NA	0.0379097	NA
72	1.01	NA	NA	0.0149097	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