Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 01 Apr 2015 20:36:37 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/01/t1427917045dz610re28wqudu6.htm/, Retrieved Thu, 09 May 2024 07:53:27 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278533, Retrieved Thu, 09 May 2024 07:53:27 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

131

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

-       [Classical Decomposition] [] [2015-04-01 19:36:37] [70e23d918d09c907c02097a361cd6415] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

-23,5
5,9
8,4
7,8
4,8
3,5
8,7
6,8
6
3,6
8,7
8,9
8,1
7
7,9
8
7,5
6,3
7,6
8,4
6,8
8,8
8,7
8,7
7,4
2,8
4,8
-21,1
8,5
9,4
1,8
4,8
5,8
3,3
-9
-6
-0,9
-17,3
-9,2
-8,1
-20,9
-14,6
-13,9
-20,8
-16,1
-5
-7,2
-9,7
-1,4
0,2
2,6
-4,8
-6,2
-2
-0,8
-3,1
0,6
0,2
0,3
-0,1
4,3
-3,2
-1,3
1,5
2,5
-2,2
1,7
5,7
2,7
-4,8
-3,1
-0,5
-3,4
-4,7
-5,6
-1,7
-1,8
-5,4
-4,8
-2,8
-4,9
-6,8
-7,6
-6,6
-5,6
-1,4
0,1
-3,7
-5,6
-3,1
-3,8
-5,1
-4,1
-0,3
-0,3
-2,4

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	'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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278533&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278533&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278533&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	-23.5	NA	NA	2.21642	NA
2	5.9	NA	NA	-1.22406	NA
3	8.4	NA	NA	1.17832	NA
4	7.8	NA	NA	-2.90977	NA
5	4.8	NA	NA	-0.847272	NA
6	3.5	NA	NA	-0.0978671	NA
7	8.7	6.00213	5.45	0.552133	2.69787
8	6.8	7.11582	6.8125	0.303323	-0.315823
9	6	7.50511	6.8375	0.667609	-1.50511
10	3.6	7.38189	6.825	0.556895	-3.78189
11	8.7	6.4188	6.94583	-0.527034	2.2812
12	8.9	7.3063	7.175	0.1313	1.5937
13	8.1	9.46225	7.24583	2.21642	-1.36225
14	7	6.04261	7.26667	-1.22406	0.957391
15	7.9	8.54499	7.36667	1.17832	-0.64499
16	8	4.70689	7.61667	-2.90977	3.29311
17	7.5	6.98606	7.83333	-0.847272	0.513938
18	6.3	7.72713	7.825	-0.0978671	-1.42713
19	7.6	8.33963	7.7875	0.552133	-0.739633
20	8.4	7.88666	7.58333	0.303323	0.513343
21	6.8	7.94678	7.27917	0.667609	-1.14678
22	8.8	6.49439	5.9375	0.556895	2.30561
23	8.7	4.23963	4.76667	-0.527034	4.46037
24	8.7	5.0688	4.9375	0.1313	3.6312
25	7.4	7.04142	4.825	2.21642	0.358581
26	2.8	3.20928	4.43333	-1.22406	-0.409276
27	4.8	5.41999	4.24167	1.17832	-0.61999
28	-21.1	1.06106	3.97083	-2.90977	-22.1611
29	8.5	2.15689	3.00417	-0.847272	6.34311
30	9.4	1.5563	1.65417	-0.0978671	7.8437
31	1.8	1.24797	0.695833	0.552133	0.552034
32	4.8	-0.184177	-0.4875	0.303323	4.98418
33	5.8	-1.24072	-1.90833	0.667609	7.04072
34	3.3	-1.39311	-1.95	0.556895	4.69311
35	-9	-3.16037	-2.63333	-0.527034	-5.83963
36	-6	-4.72703	-4.85833	0.1313	-1.27297
37	-0.9	-4.29608	-6.5125	2.21642	3.39608
38	-17.3	-9.45739	-8.23333	-1.22406	-7.84261
39	-9.2	-9.03418	-10.2125	1.17832	-0.165823
40	-8.1	-14.3806	-11.4708	-2.90977	6.28061
41	-20.9	-12.5889	-11.7417	-0.847272	-8.31106
42	-14.6	-11.9187	-11.8208	-0.0978671	-2.6813
43	-13.9	-11.4437	-11.9958	0.552133	-2.4563
44	-20.8	-10.9842	-11.2875	0.303323	-9.81582
45	-16.1	-9.39906	-10.0667	0.667609	-6.70094
46	-5	-8.88061	-9.4375	0.556895	3.88061
47	-7.2	-9.21453	-8.6875	-0.527034	2.01453
48	-9.7	-7.4187	-7.55	0.1313	-2.2813
49	-1.4	-4.26275	-6.47917	2.21642	2.86275
50	0.2	-6.41989	-5.19583	-1.22406	6.61989
51	2.6	-2.58418	-3.7625	1.17832	5.18418
52	-4.8	-5.75977	-2.85	-2.90977	0.959772
53	-6.2	-3.16811	-2.32083	-0.847272	-3.03189
54	-2	-1.7062	-1.60833	-0.0978671	-0.2938
55	-0.8	-0.4187	-0.970833	0.552133	-0.3813
56	-3.1	-0.571677	-0.875	0.303323	-2.52832
57	0.6	-0.511558	-1.17917	0.667609	1.11156
58	0.2	-0.522272	-1.07917	0.556895	0.722272
59	0.3	-0.9812	-0.454167	-0.527034	1.2812
60	-0.1	0.0312996	-0.1	0.1313	-0.1313
61	4.3	2.21225	-0.00416667	2.21642	2.08775
62	-3.2	-0.757391	0.466667	-1.22406	-2.44261
63	-1.3	2.09916	0.920833	1.17832	-3.39916
64	1.5	-2.10977	0.8	-2.90977	3.60977
65	2.5	-0.397272	0.45	-0.847272	2.89727
66	-2.2	0.1938	0.291667	-0.0978671	-2.3938
67	1.7	0.5063	-0.0458333	0.552133	1.1937
68	5.7	-0.125843	-0.429167	0.303323	5.82584
69	2.7	-0.00322421	-0.670833	0.667609	2.70322
70	-4.8	-0.426438	-0.983333	0.556895	-4.37356
71	-3.1	-1.82287	-1.29583	-0.527034	-1.27713
72	-0.5	-1.47703	-1.60833	0.1313	0.977034
73	-3.4	0.203919	-2.0125	2.21642	-3.60392
74	-4.7	-3.86156	-2.6375	-1.22406	-0.838442
75	-5.6	-2.13001	-3.30833	1.17832	-3.46999
76	-1.7	-6.61811	-3.70833	-2.90977	4.91811
77	-1.8	-4.82644	-3.97917	-0.847272	3.02644
78	-5.4	-4.5187	-4.42083	-0.0978671	-0.8813
79	-4.8	-4.21453	-4.76667	0.552133	-0.585466
80	-2.8	-4.41751	-4.72083	0.303323	1.61751
81	-4.9	-3.67822	-4.34583	0.667609	-1.22178
82	-6.8	-3.63477	-4.19167	0.556895	-3.16523
83	-7.6	-4.96037	-4.43333	-0.527034	-2.63963
84	-6.6	-4.36453	-4.49583	0.1313	-2.23547
85	-5.6	-2.14191	-4.35833	2.21642	-3.45809
86	-1.4	-5.63656	-4.4125	-1.22406	4.23656
87	0.1	-3.29668	-4.475	1.17832	3.39668
88	-3.7	-7.08061	-4.17083	-2.90977	3.38061
89	-5.6	-4.44311	-3.59583	-0.847272	-1.15689
90	-3.1	-3.21453	-3.11667	-0.0978671	0.114534
91	-3.8	NA	NA	0.552133	NA
92	-5.1	NA	NA	0.303323	NA
93	-4.1	NA	NA	0.667609	NA
94	-0.3	NA	NA	0.556895	NA
95	-0.3	NA	NA	-0.527034	NA
96	-2.4	NA	NA	0.1313	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & -23.5 & NA & NA & 2.21642 & NA \tabularnewline
2 & 5.9 & NA & NA & -1.22406 & NA \tabularnewline
3 & 8.4 & NA & NA & 1.17832 & NA \tabularnewline
4 & 7.8 & NA & NA & -2.90977 & NA \tabularnewline
5 & 4.8 & NA & NA & -0.847272 & NA \tabularnewline
6 & 3.5 & NA & NA & -0.0978671 & NA \tabularnewline
7 & 8.7 & 6.00213 & 5.45 & 0.552133 & 2.69787 \tabularnewline
8 & 6.8 & 7.11582 & 6.8125 & 0.303323 & -0.315823 \tabularnewline
9 & 6 & 7.50511 & 6.8375 & 0.667609 & -1.50511 \tabularnewline
10 & 3.6 & 7.38189 & 6.825 & 0.556895 & -3.78189 \tabularnewline
11 & 8.7 & 6.4188 & 6.94583 & -0.527034 & 2.2812 \tabularnewline
12 & 8.9 & 7.3063 & 7.175 & 0.1313 & 1.5937 \tabularnewline
13 & 8.1 & 9.46225 & 7.24583 & 2.21642 & -1.36225 \tabularnewline
14 & 7 & 6.04261 & 7.26667 & -1.22406 & 0.957391 \tabularnewline
15 & 7.9 & 8.54499 & 7.36667 & 1.17832 & -0.64499 \tabularnewline
16 & 8 & 4.70689 & 7.61667 & -2.90977 & 3.29311 \tabularnewline
17 & 7.5 & 6.98606 & 7.83333 & -0.847272 & 0.513938 \tabularnewline
18 & 6.3 & 7.72713 & 7.825 & -0.0978671 & -1.42713 \tabularnewline
19 & 7.6 & 8.33963 & 7.7875 & 0.552133 & -0.739633 \tabularnewline
20 & 8.4 & 7.88666 & 7.58333 & 0.303323 & 0.513343 \tabularnewline
21 & 6.8 & 7.94678 & 7.27917 & 0.667609 & -1.14678 \tabularnewline
22 & 8.8 & 6.49439 & 5.9375 & 0.556895 & 2.30561 \tabularnewline
23 & 8.7 & 4.23963 & 4.76667 & -0.527034 & 4.46037 \tabularnewline
24 & 8.7 & 5.0688 & 4.9375 & 0.1313 & 3.6312 \tabularnewline
25 & 7.4 & 7.04142 & 4.825 & 2.21642 & 0.358581 \tabularnewline
26 & 2.8 & 3.20928 & 4.43333 & -1.22406 & -0.409276 \tabularnewline
27 & 4.8 & 5.41999 & 4.24167 & 1.17832 & -0.61999 \tabularnewline
28 & -21.1 & 1.06106 & 3.97083 & -2.90977 & -22.1611 \tabularnewline
29 & 8.5 & 2.15689 & 3.00417 & -0.847272 & 6.34311 \tabularnewline
30 & 9.4 & 1.5563 & 1.65417 & -0.0978671 & 7.8437 \tabularnewline
31 & 1.8 & 1.24797 & 0.695833 & 0.552133 & 0.552034 \tabularnewline
32 & 4.8 & -0.184177 & -0.4875 & 0.303323 & 4.98418 \tabularnewline
33 & 5.8 & -1.24072 & -1.90833 & 0.667609 & 7.04072 \tabularnewline
34 & 3.3 & -1.39311 & -1.95 & 0.556895 & 4.69311 \tabularnewline
35 & -9 & -3.16037 & -2.63333 & -0.527034 & -5.83963 \tabularnewline
36 & -6 & -4.72703 & -4.85833 & 0.1313 & -1.27297 \tabularnewline
37 & -0.9 & -4.29608 & -6.5125 & 2.21642 & 3.39608 \tabularnewline
38 & -17.3 & -9.45739 & -8.23333 & -1.22406 & -7.84261 \tabularnewline
39 & -9.2 & -9.03418 & -10.2125 & 1.17832 & -0.165823 \tabularnewline
40 & -8.1 & -14.3806 & -11.4708 & -2.90977 & 6.28061 \tabularnewline
41 & -20.9 & -12.5889 & -11.7417 & -0.847272 & -8.31106 \tabularnewline
42 & -14.6 & -11.9187 & -11.8208 & -0.0978671 & -2.6813 \tabularnewline
43 & -13.9 & -11.4437 & -11.9958 & 0.552133 & -2.4563 \tabularnewline
44 & -20.8 & -10.9842 & -11.2875 & 0.303323 & -9.81582 \tabularnewline
45 & -16.1 & -9.39906 & -10.0667 & 0.667609 & -6.70094 \tabularnewline
46 & -5 & -8.88061 & -9.4375 & 0.556895 & 3.88061 \tabularnewline
47 & -7.2 & -9.21453 & -8.6875 & -0.527034 & 2.01453 \tabularnewline
48 & -9.7 & -7.4187 & -7.55 & 0.1313 & -2.2813 \tabularnewline
49 & -1.4 & -4.26275 & -6.47917 & 2.21642 & 2.86275 \tabularnewline
50 & 0.2 & -6.41989 & -5.19583 & -1.22406 & 6.61989 \tabularnewline
51 & 2.6 & -2.58418 & -3.7625 & 1.17832 & 5.18418 \tabularnewline
52 & -4.8 & -5.75977 & -2.85 & -2.90977 & 0.959772 \tabularnewline
53 & -6.2 & -3.16811 & -2.32083 & -0.847272 & -3.03189 \tabularnewline
54 & -2 & -1.7062 & -1.60833 & -0.0978671 & -0.2938 \tabularnewline
55 & -0.8 & -0.4187 & -0.970833 & 0.552133 & -0.3813 \tabularnewline
56 & -3.1 & -0.571677 & -0.875 & 0.303323 & -2.52832 \tabularnewline
57 & 0.6 & -0.511558 & -1.17917 & 0.667609 & 1.11156 \tabularnewline
58 & 0.2 & -0.522272 & -1.07917 & 0.556895 & 0.722272 \tabularnewline
59 & 0.3 & -0.9812 & -0.454167 & -0.527034 & 1.2812 \tabularnewline
60 & -0.1 & 0.0312996 & -0.1 & 0.1313 & -0.1313 \tabularnewline
61 & 4.3 & 2.21225 & -0.00416667 & 2.21642 & 2.08775 \tabularnewline
62 & -3.2 & -0.757391 & 0.466667 & -1.22406 & -2.44261 \tabularnewline
63 & -1.3 & 2.09916 & 0.920833 & 1.17832 & -3.39916 \tabularnewline
64 & 1.5 & -2.10977 & 0.8 & -2.90977 & 3.60977 \tabularnewline
65 & 2.5 & -0.397272 & 0.45 & -0.847272 & 2.89727 \tabularnewline
66 & -2.2 & 0.1938 & 0.291667 & -0.0978671 & -2.3938 \tabularnewline
67 & 1.7 & 0.5063 & -0.0458333 & 0.552133 & 1.1937 \tabularnewline
68 & 5.7 & -0.125843 & -0.429167 & 0.303323 & 5.82584 \tabularnewline
69 & 2.7 & -0.00322421 & -0.670833 & 0.667609 & 2.70322 \tabularnewline
70 & -4.8 & -0.426438 & -0.983333 & 0.556895 & -4.37356 \tabularnewline
71 & -3.1 & -1.82287 & -1.29583 & -0.527034 & -1.27713 \tabularnewline
72 & -0.5 & -1.47703 & -1.60833 & 0.1313 & 0.977034 \tabularnewline
73 & -3.4 & 0.203919 & -2.0125 & 2.21642 & -3.60392 \tabularnewline
74 & -4.7 & -3.86156 & -2.6375 & -1.22406 & -0.838442 \tabularnewline
75 & -5.6 & -2.13001 & -3.30833 & 1.17832 & -3.46999 \tabularnewline
76 & -1.7 & -6.61811 & -3.70833 & -2.90977 & 4.91811 \tabularnewline
77 & -1.8 & -4.82644 & -3.97917 & -0.847272 & 3.02644 \tabularnewline
78 & -5.4 & -4.5187 & -4.42083 & -0.0978671 & -0.8813 \tabularnewline
79 & -4.8 & -4.21453 & -4.76667 & 0.552133 & -0.585466 \tabularnewline
80 & -2.8 & -4.41751 & -4.72083 & 0.303323 & 1.61751 \tabularnewline
81 & -4.9 & -3.67822 & -4.34583 & 0.667609 & -1.22178 \tabularnewline
82 & -6.8 & -3.63477 & -4.19167 & 0.556895 & -3.16523 \tabularnewline
83 & -7.6 & -4.96037 & -4.43333 & -0.527034 & -2.63963 \tabularnewline
84 & -6.6 & -4.36453 & -4.49583 & 0.1313 & -2.23547 \tabularnewline
85 & -5.6 & -2.14191 & -4.35833 & 2.21642 & -3.45809 \tabularnewline
86 & -1.4 & -5.63656 & -4.4125 & -1.22406 & 4.23656 \tabularnewline
87 & 0.1 & -3.29668 & -4.475 & 1.17832 & 3.39668 \tabularnewline
88 & -3.7 & -7.08061 & -4.17083 & -2.90977 & 3.38061 \tabularnewline
89 & -5.6 & -4.44311 & -3.59583 & -0.847272 & -1.15689 \tabularnewline
90 & -3.1 & -3.21453 & -3.11667 & -0.0978671 & 0.114534 \tabularnewline
91 & -3.8 & NA & NA & 0.552133 & NA \tabularnewline
92 & -5.1 & NA & NA & 0.303323 & NA \tabularnewline
93 & -4.1 & NA & NA & 0.667609 & NA \tabularnewline
94 & -0.3 & NA & NA & 0.556895 & NA \tabularnewline
95 & -0.3 & NA & NA & -0.527034 & NA \tabularnewline
96 & -2.4 & NA & NA & 0.1313 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278533&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]-23.5[/C][C]NA[/C][C]NA[/C][C]2.21642[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5.9[/C][C]NA[/C][C]NA[/C][C]-1.22406[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.4[/C][C]NA[/C][C]NA[/C][C]1.17832[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]7.8[/C][C]NA[/C][C]NA[/C][C]-2.90977[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]4.8[/C][C]NA[/C][C]NA[/C][C]-0.847272[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3.5[/C][C]NA[/C][C]NA[/C][C]-0.0978671[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.7[/C][C]6.00213[/C][C]5.45[/C][C]0.552133[/C][C]2.69787[/C][/ROW]
[ROW][C]8[/C][C]6.8[/C][C]7.11582[/C][C]6.8125[/C][C]0.303323[/C][C]-0.315823[/C][/ROW]
[ROW][C]9[/C][C]6[/C][C]7.50511[/C][C]6.8375[/C][C]0.667609[/C][C]-1.50511[/C][/ROW]
[ROW][C]10[/C][C]3.6[/C][C]7.38189[/C][C]6.825[/C][C]0.556895[/C][C]-3.78189[/C][/ROW]
[ROW][C]11[/C][C]8.7[/C][C]6.4188[/C][C]6.94583[/C][C]-0.527034[/C][C]2.2812[/C][/ROW]
[ROW][C]12[/C][C]8.9[/C][C]7.3063[/C][C]7.175[/C][C]0.1313[/C][C]1.5937[/C][/ROW]
[ROW][C]13[/C][C]8.1[/C][C]9.46225[/C][C]7.24583[/C][C]2.21642[/C][C]-1.36225[/C][/ROW]
[ROW][C]14[/C][C]7[/C][C]6.04261[/C][C]7.26667[/C][C]-1.22406[/C][C]0.957391[/C][/ROW]
[ROW][C]15[/C][C]7.9[/C][C]8.54499[/C][C]7.36667[/C][C]1.17832[/C][C]-0.64499[/C][/ROW]
[ROW][C]16[/C][C]8[/C][C]4.70689[/C][C]7.61667[/C][C]-2.90977[/C][C]3.29311[/C][/ROW]
[ROW][C]17[/C][C]7.5[/C][C]6.98606[/C][C]7.83333[/C][C]-0.847272[/C][C]0.513938[/C][/ROW]
[ROW][C]18[/C][C]6.3[/C][C]7.72713[/C][C]7.825[/C][C]-0.0978671[/C][C]-1.42713[/C][/ROW]
[ROW][C]19[/C][C]7.6[/C][C]8.33963[/C][C]7.7875[/C][C]0.552133[/C][C]-0.739633[/C][/ROW]
[ROW][C]20[/C][C]8.4[/C][C]7.88666[/C][C]7.58333[/C][C]0.303323[/C][C]0.513343[/C][/ROW]
[ROW][C]21[/C][C]6.8[/C][C]7.94678[/C][C]7.27917[/C][C]0.667609[/C][C]-1.14678[/C][/ROW]
[ROW][C]22[/C][C]8.8[/C][C]6.49439[/C][C]5.9375[/C][C]0.556895[/C][C]2.30561[/C][/ROW]
[ROW][C]23[/C][C]8.7[/C][C]4.23963[/C][C]4.76667[/C][C]-0.527034[/C][C]4.46037[/C][/ROW]
[ROW][C]24[/C][C]8.7[/C][C]5.0688[/C][C]4.9375[/C][C]0.1313[/C][C]3.6312[/C][/ROW]
[ROW][C]25[/C][C]7.4[/C][C]7.04142[/C][C]4.825[/C][C]2.21642[/C][C]0.358581[/C][/ROW]
[ROW][C]26[/C][C]2.8[/C][C]3.20928[/C][C]4.43333[/C][C]-1.22406[/C][C]-0.409276[/C][/ROW]
[ROW][C]27[/C][C]4.8[/C][C]5.41999[/C][C]4.24167[/C][C]1.17832[/C][C]-0.61999[/C][/ROW]
[ROW][C]28[/C][C]-21.1[/C][C]1.06106[/C][C]3.97083[/C][C]-2.90977[/C][C]-22.1611[/C][/ROW]
[ROW][C]29[/C][C]8.5[/C][C]2.15689[/C][C]3.00417[/C][C]-0.847272[/C][C]6.34311[/C][/ROW]
[ROW][C]30[/C][C]9.4[/C][C]1.5563[/C][C]1.65417[/C][C]-0.0978671[/C][C]7.8437[/C][/ROW]
[ROW][C]31[/C][C]1.8[/C][C]1.24797[/C][C]0.695833[/C][C]0.552133[/C][C]0.552034[/C][/ROW]
[ROW][C]32[/C][C]4.8[/C][C]-0.184177[/C][C]-0.4875[/C][C]0.303323[/C][C]4.98418[/C][/ROW]
[ROW][C]33[/C][C]5.8[/C][C]-1.24072[/C][C]-1.90833[/C][C]0.667609[/C][C]7.04072[/C][/ROW]
[ROW][C]34[/C][C]3.3[/C][C]-1.39311[/C][C]-1.95[/C][C]0.556895[/C][C]4.69311[/C][/ROW]
[ROW][C]35[/C][C]-9[/C][C]-3.16037[/C][C]-2.63333[/C][C]-0.527034[/C][C]-5.83963[/C][/ROW]
[ROW][C]36[/C][C]-6[/C][C]-4.72703[/C][C]-4.85833[/C][C]0.1313[/C][C]-1.27297[/C][/ROW]
[ROW][C]37[/C][C]-0.9[/C][C]-4.29608[/C][C]-6.5125[/C][C]2.21642[/C][C]3.39608[/C][/ROW]
[ROW][C]38[/C][C]-17.3[/C][C]-9.45739[/C][C]-8.23333[/C][C]-1.22406[/C][C]-7.84261[/C][/ROW]
[ROW][C]39[/C][C]-9.2[/C][C]-9.03418[/C][C]-10.2125[/C][C]1.17832[/C][C]-0.165823[/C][/ROW]
[ROW][C]40[/C][C]-8.1[/C][C]-14.3806[/C][C]-11.4708[/C][C]-2.90977[/C][C]6.28061[/C][/ROW]
[ROW][C]41[/C][C]-20.9[/C][C]-12.5889[/C][C]-11.7417[/C][C]-0.847272[/C][C]-8.31106[/C][/ROW]
[ROW][C]42[/C][C]-14.6[/C][C]-11.9187[/C][C]-11.8208[/C][C]-0.0978671[/C][C]-2.6813[/C][/ROW]
[ROW][C]43[/C][C]-13.9[/C][C]-11.4437[/C][C]-11.9958[/C][C]0.552133[/C][C]-2.4563[/C][/ROW]
[ROW][C]44[/C][C]-20.8[/C][C]-10.9842[/C][C]-11.2875[/C][C]0.303323[/C][C]-9.81582[/C][/ROW]
[ROW][C]45[/C][C]-16.1[/C][C]-9.39906[/C][C]-10.0667[/C][C]0.667609[/C][C]-6.70094[/C][/ROW]
[ROW][C]46[/C][C]-5[/C][C]-8.88061[/C][C]-9.4375[/C][C]0.556895[/C][C]3.88061[/C][/ROW]
[ROW][C]47[/C][C]-7.2[/C][C]-9.21453[/C][C]-8.6875[/C][C]-0.527034[/C][C]2.01453[/C][/ROW]
[ROW][C]48[/C][C]-9.7[/C][C]-7.4187[/C][C]-7.55[/C][C]0.1313[/C][C]-2.2813[/C][/ROW]
[ROW][C]49[/C][C]-1.4[/C][C]-4.26275[/C][C]-6.47917[/C][C]2.21642[/C][C]2.86275[/C][/ROW]
[ROW][C]50[/C][C]0.2[/C][C]-6.41989[/C][C]-5.19583[/C][C]-1.22406[/C][C]6.61989[/C][/ROW]
[ROW][C]51[/C][C]2.6[/C][C]-2.58418[/C][C]-3.7625[/C][C]1.17832[/C][C]5.18418[/C][/ROW]
[ROW][C]52[/C][C]-4.8[/C][C]-5.75977[/C][C]-2.85[/C][C]-2.90977[/C][C]0.959772[/C][/ROW]
[ROW][C]53[/C][C]-6.2[/C][C]-3.16811[/C][C]-2.32083[/C][C]-0.847272[/C][C]-3.03189[/C][/ROW]
[ROW][C]54[/C][C]-2[/C][C]-1.7062[/C][C]-1.60833[/C][C]-0.0978671[/C][C]-0.2938[/C][/ROW]
[ROW][C]55[/C][C]-0.8[/C][C]-0.4187[/C][C]-0.970833[/C][C]0.552133[/C][C]-0.3813[/C][/ROW]
[ROW][C]56[/C][C]-3.1[/C][C]-0.571677[/C][C]-0.875[/C][C]0.303323[/C][C]-2.52832[/C][/ROW]
[ROW][C]57[/C][C]0.6[/C][C]-0.511558[/C][C]-1.17917[/C][C]0.667609[/C][C]1.11156[/C][/ROW]
[ROW][C]58[/C][C]0.2[/C][C]-0.522272[/C][C]-1.07917[/C][C]0.556895[/C][C]0.722272[/C][/ROW]
[ROW][C]59[/C][C]0.3[/C][C]-0.9812[/C][C]-0.454167[/C][C]-0.527034[/C][C]1.2812[/C][/ROW]
[ROW][C]60[/C][C]-0.1[/C][C]0.0312996[/C][C]-0.1[/C][C]0.1313[/C][C]-0.1313[/C][/ROW]
[ROW][C]61[/C][C]4.3[/C][C]2.21225[/C][C]-0.00416667[/C][C]2.21642[/C][C]2.08775[/C][/ROW]
[ROW][C]62[/C][C]-3.2[/C][C]-0.757391[/C][C]0.466667[/C][C]-1.22406[/C][C]-2.44261[/C][/ROW]
[ROW][C]63[/C][C]-1.3[/C][C]2.09916[/C][C]0.920833[/C][C]1.17832[/C][C]-3.39916[/C][/ROW]
[ROW][C]64[/C][C]1.5[/C][C]-2.10977[/C][C]0.8[/C][C]-2.90977[/C][C]3.60977[/C][/ROW]
[ROW][C]65[/C][C]2.5[/C][C]-0.397272[/C][C]0.45[/C][C]-0.847272[/C][C]2.89727[/C][/ROW]
[ROW][C]66[/C][C]-2.2[/C][C]0.1938[/C][C]0.291667[/C][C]-0.0978671[/C][C]-2.3938[/C][/ROW]
[ROW][C]67[/C][C]1.7[/C][C]0.5063[/C][C]-0.0458333[/C][C]0.552133[/C][C]1.1937[/C][/ROW]
[ROW][C]68[/C][C]5.7[/C][C]-0.125843[/C][C]-0.429167[/C][C]0.303323[/C][C]5.82584[/C][/ROW]
[ROW][C]69[/C][C]2.7[/C][C]-0.00322421[/C][C]-0.670833[/C][C]0.667609[/C][C]2.70322[/C][/ROW]
[ROW][C]70[/C][C]-4.8[/C][C]-0.426438[/C][C]-0.983333[/C][C]0.556895[/C][C]-4.37356[/C][/ROW]
[ROW][C]71[/C][C]-3.1[/C][C]-1.82287[/C][C]-1.29583[/C][C]-0.527034[/C][C]-1.27713[/C][/ROW]
[ROW][C]72[/C][C]-0.5[/C][C]-1.47703[/C][C]-1.60833[/C][C]0.1313[/C][C]0.977034[/C][/ROW]
[ROW][C]73[/C][C]-3.4[/C][C]0.203919[/C][C]-2.0125[/C][C]2.21642[/C][C]-3.60392[/C][/ROW]
[ROW][C]74[/C][C]-4.7[/C][C]-3.86156[/C][C]-2.6375[/C][C]-1.22406[/C][C]-0.838442[/C][/ROW]
[ROW][C]75[/C][C]-5.6[/C][C]-2.13001[/C][C]-3.30833[/C][C]1.17832[/C][C]-3.46999[/C][/ROW]
[ROW][C]76[/C][C]-1.7[/C][C]-6.61811[/C][C]-3.70833[/C][C]-2.90977[/C][C]4.91811[/C][/ROW]
[ROW][C]77[/C][C]-1.8[/C][C]-4.82644[/C][C]-3.97917[/C][C]-0.847272[/C][C]3.02644[/C][/ROW]
[ROW][C]78[/C][C]-5.4[/C][C]-4.5187[/C][C]-4.42083[/C][C]-0.0978671[/C][C]-0.8813[/C][/ROW]
[ROW][C]79[/C][C]-4.8[/C][C]-4.21453[/C][C]-4.76667[/C][C]0.552133[/C][C]-0.585466[/C][/ROW]
[ROW][C]80[/C][C]-2.8[/C][C]-4.41751[/C][C]-4.72083[/C][C]0.303323[/C][C]1.61751[/C][/ROW]
[ROW][C]81[/C][C]-4.9[/C][C]-3.67822[/C][C]-4.34583[/C][C]0.667609[/C][C]-1.22178[/C][/ROW]
[ROW][C]82[/C][C]-6.8[/C][C]-3.63477[/C][C]-4.19167[/C][C]0.556895[/C][C]-3.16523[/C][/ROW]
[ROW][C]83[/C][C]-7.6[/C][C]-4.96037[/C][C]-4.43333[/C][C]-0.527034[/C][C]-2.63963[/C][/ROW]
[ROW][C]84[/C][C]-6.6[/C][C]-4.36453[/C][C]-4.49583[/C][C]0.1313[/C][C]-2.23547[/C][/ROW]
[ROW][C]85[/C][C]-5.6[/C][C]-2.14191[/C][C]-4.35833[/C][C]2.21642[/C][C]-3.45809[/C][/ROW]
[ROW][C]86[/C][C]-1.4[/C][C]-5.63656[/C][C]-4.4125[/C][C]-1.22406[/C][C]4.23656[/C][/ROW]
[ROW][C]87[/C][C]0.1[/C][C]-3.29668[/C][C]-4.475[/C][C]1.17832[/C][C]3.39668[/C][/ROW]
[ROW][C]88[/C][C]-3.7[/C][C]-7.08061[/C][C]-4.17083[/C][C]-2.90977[/C][C]3.38061[/C][/ROW]
[ROW][C]89[/C][C]-5.6[/C][C]-4.44311[/C][C]-3.59583[/C][C]-0.847272[/C][C]-1.15689[/C][/ROW]
[ROW][C]90[/C][C]-3.1[/C][C]-3.21453[/C][C]-3.11667[/C][C]-0.0978671[/C][C]0.114534[/C][/ROW]
[ROW][C]91[/C][C]-3.8[/C][C]NA[/C][C]NA[/C][C]0.552133[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]-5.1[/C][C]NA[/C][C]NA[/C][C]0.303323[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]-4.1[/C][C]NA[/C][C]NA[/C][C]0.667609[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]-0.3[/C][C]NA[/C][C]NA[/C][C]0.556895[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]-0.3[/C][C]NA[/C][C]NA[/C][C]-0.527034[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]-2.4[/C][C]NA[/C][C]NA[/C][C]0.1313[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278533&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278533&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	-23.5	NA	NA	2.21642	NA
2	5.9	NA	NA	-1.22406	NA
3	8.4	NA	NA	1.17832	NA
4	7.8	NA	NA	-2.90977	NA
5	4.8	NA	NA	-0.847272	NA
6	3.5	NA	NA	-0.0978671	NA
7	8.7	6.00213	5.45	0.552133	2.69787
8	6.8	7.11582	6.8125	0.303323	-0.315823
9	6	7.50511	6.8375	0.667609	-1.50511
10	3.6	7.38189	6.825	0.556895	-3.78189
11	8.7	6.4188	6.94583	-0.527034	2.2812
12	8.9	7.3063	7.175	0.1313	1.5937
13	8.1	9.46225	7.24583	2.21642	-1.36225
14	7	6.04261	7.26667	-1.22406	0.957391
15	7.9	8.54499	7.36667	1.17832	-0.64499
16	8	4.70689	7.61667	-2.90977	3.29311
17	7.5	6.98606	7.83333	-0.847272	0.513938
18	6.3	7.72713	7.825	-0.0978671	-1.42713
19	7.6	8.33963	7.7875	0.552133	-0.739633
20	8.4	7.88666	7.58333	0.303323	0.513343
21	6.8	7.94678	7.27917	0.667609	-1.14678
22	8.8	6.49439	5.9375	0.556895	2.30561
23	8.7	4.23963	4.76667	-0.527034	4.46037
24	8.7	5.0688	4.9375	0.1313	3.6312
25	7.4	7.04142	4.825	2.21642	0.358581
26	2.8	3.20928	4.43333	-1.22406	-0.409276
27	4.8	5.41999	4.24167	1.17832	-0.61999
28	-21.1	1.06106	3.97083	-2.90977	-22.1611
29	8.5	2.15689	3.00417	-0.847272	6.34311
30	9.4	1.5563	1.65417	-0.0978671	7.8437
31	1.8	1.24797	0.695833	0.552133	0.552034
32	4.8	-0.184177	-0.4875	0.303323	4.98418
33	5.8	-1.24072	-1.90833	0.667609	7.04072
34	3.3	-1.39311	-1.95	0.556895	4.69311
35	-9	-3.16037	-2.63333	-0.527034	-5.83963
36	-6	-4.72703	-4.85833	0.1313	-1.27297
37	-0.9	-4.29608	-6.5125	2.21642	3.39608
38	-17.3	-9.45739	-8.23333	-1.22406	-7.84261
39	-9.2	-9.03418	-10.2125	1.17832	-0.165823
40	-8.1	-14.3806	-11.4708	-2.90977	6.28061
41	-20.9	-12.5889	-11.7417	-0.847272	-8.31106
42	-14.6	-11.9187	-11.8208	-0.0978671	-2.6813
43	-13.9	-11.4437	-11.9958	0.552133	-2.4563
44	-20.8	-10.9842	-11.2875	0.303323	-9.81582
45	-16.1	-9.39906	-10.0667	0.667609	-6.70094
46	-5	-8.88061	-9.4375	0.556895	3.88061
47	-7.2	-9.21453	-8.6875	-0.527034	2.01453
48	-9.7	-7.4187	-7.55	0.1313	-2.2813
49	-1.4	-4.26275	-6.47917	2.21642	2.86275
50	0.2	-6.41989	-5.19583	-1.22406	6.61989
51	2.6	-2.58418	-3.7625	1.17832	5.18418
52	-4.8	-5.75977	-2.85	-2.90977	0.959772
53	-6.2	-3.16811	-2.32083	-0.847272	-3.03189
54	-2	-1.7062	-1.60833	-0.0978671	-0.2938
55	-0.8	-0.4187	-0.970833	0.552133	-0.3813
56	-3.1	-0.571677	-0.875	0.303323	-2.52832
57	0.6	-0.511558	-1.17917	0.667609	1.11156
58	0.2	-0.522272	-1.07917	0.556895	0.722272
59	0.3	-0.9812	-0.454167	-0.527034	1.2812
60	-0.1	0.0312996	-0.1	0.1313	-0.1313
61	4.3	2.21225	-0.00416667	2.21642	2.08775
62	-3.2	-0.757391	0.466667	-1.22406	-2.44261
63	-1.3	2.09916	0.920833	1.17832	-3.39916
64	1.5	-2.10977	0.8	-2.90977	3.60977
65	2.5	-0.397272	0.45	-0.847272	2.89727
66	-2.2	0.1938	0.291667	-0.0978671	-2.3938
67	1.7	0.5063	-0.0458333	0.552133	1.1937
68	5.7	-0.125843	-0.429167	0.303323	5.82584
69	2.7	-0.00322421	-0.670833	0.667609	2.70322
70	-4.8	-0.426438	-0.983333	0.556895	-4.37356
71	-3.1	-1.82287	-1.29583	-0.527034	-1.27713
72	-0.5	-1.47703	-1.60833	0.1313	0.977034
73	-3.4	0.203919	-2.0125	2.21642	-3.60392
74	-4.7	-3.86156	-2.6375	-1.22406	-0.838442
75	-5.6	-2.13001	-3.30833	1.17832	-3.46999
76	-1.7	-6.61811	-3.70833	-2.90977	4.91811
77	-1.8	-4.82644	-3.97917	-0.847272	3.02644
78	-5.4	-4.5187	-4.42083	-0.0978671	-0.8813
79	-4.8	-4.21453	-4.76667	0.552133	-0.585466
80	-2.8	-4.41751	-4.72083	0.303323	1.61751
81	-4.9	-3.67822	-4.34583	0.667609	-1.22178
82	-6.8	-3.63477	-4.19167	0.556895	-3.16523
83	-7.6	-4.96037	-4.43333	-0.527034	-2.63963
84	-6.6	-4.36453	-4.49583	0.1313	-2.23547
85	-5.6	-2.14191	-4.35833	2.21642	-3.45809
86	-1.4	-5.63656	-4.4125	-1.22406	4.23656
87	0.1	-3.29668	-4.475	1.17832	3.39668
88	-3.7	-7.08061	-4.17083	-2.90977	3.38061
89	-5.6	-4.44311	-3.59583	-0.847272	-1.15689
90	-3.1	-3.21453	-3.11667	-0.0978671	0.114534
91	-3.8	NA	NA	0.552133	NA
92	-5.1	NA	NA	0.303323	NA
93	-4.1	NA	NA	0.667609	NA
94	-0.3	NA	NA	0.556895	NA
95	-0.3	NA	NA	-0.527034	NA
96	-2.4	NA	NA	0.1313	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