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

Tue, 31 Mar 2015 17:21:26 +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/Mar/31/t14278189444v1z95fhvz3155b.htm/, Retrieved Sun, 19 May 2024 14:55:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278487, Retrieved Sun, 19 May 2024 14:55:48 +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

157

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

-       [Classical Decomposition] [] [2015-03-31 16:21:26] [3b0947f879d0db9a6034293524e1b6d0] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

6
6,7
-0,6
5,8
16,4
1,5
5,1
14,7
4,3
1,5
9,1
4,3
5,7
13
14,5
9,7
-4,7
7,3
5,2
-2,5
11,5
4,9
-2,4
-0,3
4,4
7,9
-9,7
-4,1
16,4
-4,9
3,5
3,8
-0,2
3,1
0,7
-2,8
5,9
-5,3
-2,9
6,6
-8,1
1,3
6,9
-7,2
-1,9
4
-5,7
3,9
-7,6
-0,9
7,3
-3,7
-2,5
9,3
1,3
9,5
11,3
-1,7
8
-4,8
1,6
1,9
-0,9
5,5
1,7
-5,4
1,9
0,2
-13,3
-8,2
0,2
5,7
-1,2
-2,8
5,5
-17,3
1,4
-2,2
-8,6
-5
4,1
0,7
-4,2
-2,3
-3,4
-4,2
-14,2
1,6
-4,9
-1,8
-0,5
-2,3
-5,3
-0,2
5,1
-1,5

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=278487&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=278487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278487&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	6	NA	NA	10.5056	NA
2	6.7	NA	NA	-1.06526	NA
3	-0.6	NA	NA	1.43928	NA
4	5.8	NA	NA	-2.43813	NA
5	16.4	NA	NA	2.18748	NA
6	1.5	NA	NA	0.500978	NA
7	5.1	-1.92042	6.22083	-0.308708	-2.65567
8	14.7	9.51034	6.47083	1.46972	1.54569
9	4.3	14.6027	7.3625	1.98339	0.294465
10	1.5	0.768434	8.15417	0.0942382	1.95202
11	9.1	8.195	7.4375	1.10185	1.11043
12	4.3	-23.5989	6.8	-3.47043	-0.182212
13	5.7	74.0206	7.04583	10.5056	0.0770056
14	13	-6.74667	6.33333	-1.06526	-1.92688
15	14.5	8.51575	5.91667	1.43928	1.70273
16	9.7	-15.5024	6.35833	-2.43813	-0.625708
17	-4.7	13.1705	6.02083	2.18748	-0.356859
18	7.3	2.68023	5.35	0.500978	2.72364
19	5.2	-1.5757	5.10417	-0.308708	-3.30013
20	-2.5	7.10979	4.8375	1.46972	-0.351628
21	11.5	7.17328	3.61667	1.98339	1.60317
22	4.9	0.191618	2.03333	0.0942382	25.5718
23	-2.4	2.57557	2.3375	1.10185	-0.931832
24	-0.3	-9.39908	2.70833	-3.47043	0.031918
25	4.4	22.3681	2.12917	10.5056	0.196708
26	7.9	-2.4723	2.32083	-1.06526	-3.19541
27	-9.7	3.01649	2.09583	1.43928	-3.21565
28	-4.1	-3.73847	1.53333	-2.43813	1.09671
29	16.4	3.47263	1.5875	2.18748	4.72265
30	-4.9	0.807828	1.6125	0.500978	-6.06565
31	3.5	-0.484928	1.57083	-0.308708	-7.21756
32	3.8	1.5922	1.08333	1.46972	2.38663
33	-0.2	1.61977	0.816667	1.98339	-0.123474
34	3.1	0.145676	1.54583	0.0942382	21.28
35	0.7	1.06971	0.970833	1.10185	0.654382
36	-2.8	-0.723006	0.208333	-3.47043	3.87272
37	5.9	6.3909	0.608333	10.5056	0.923188
38	-5.3	-0.310702	0.291667	-1.06526	17.0582
39	-2.9	-0.341829	-0.2375	1.43928	8.48377
40	6.6	0.660327	-0.270833	-2.43813	9.99505
41	-8.1	-1.09374	-0.5	2.18748	7.40578
42	1.3	-0.244227	-0.4875	0.500978	-5.32292
43	6.9	0.237962	-0.770833	-0.308708	28.9962
44	-7.2	-1.69018	-1.15	1.46972	4.25989
45	-1.9	-1.07434	-0.541667	1.98339	1.76853
46	4	-0.0514383	-0.545833	0.0942382	-77.763
47	-5.7	-0.817204	-0.741667	1.10185	6.975
48	3.9	0.607325	-0.175	-3.47043	6.4216
49	-7.6	-0.787919	-0.075	10.5056	9.64566
50	-0.9	-0.41279	0.3875	-1.06526	2.18029
51	7.3	2.35083	1.63333	1.43928	3.10529
52	-3.7	-4.74419	1.94583	-2.43813	0.7799
53	-2.5	4.98563	2.27917	2.18748	-0.501441
54	9.3	1.24618	2.4875	0.500978	7.46278
55	1.3	-0.774342	2.50833	-0.308708	-1.67884
56	9.5	4.42142	3.00833	1.46972	2.14863
57	11.3	5.52045	2.78333	1.98339	2.04693
58	-1.7	0.266223	2.825	0.0942382	-6.38563
59	8	3.72792	3.38333	1.10185	2.14597
60	-4.8	-10.2233	2.94583	-3.47043	0.469515
61	1.6	24.7757	2.35833	10.5056	0.0645795
62	1.9	-2.12609	1.99583	-1.06526	-0.89366
63	-0.9	0.839581	0.583333	1.43928	-1.07196
64	5.5	1.73717	-0.7125	-2.43813	3.16607
65	1.7	-2.86195	-1.30833	2.18748	-0.594
66	-5.4	-0.599087	-1.19583	0.500978	9.01372
67	1.9	0.270119	-0.875	-0.308708	7.03393
68	0.2	-1.7453	-1.1875	1.46972	-0.114594
69	-13.3	-2.21479	-1.11667	1.98339	6.00508
70	-8.2	-0.169629	-1.8	0.0942382	48.3409
71	0.2	-3.04386	-2.7625	1.10185	-0.0657061
72	5.7	9.16772	-2.64167	-3.47043	0.621747
73	-1.2	-30.9477	-2.94583	10.5056	0.0387751
74	-2.8	3.83495	-3.6	-1.06526	-0.730127
75	5.5	-4.44978	-3.09167	1.43928	-1.23602
76	-17.3	4.8661	-1.99583	-2.43813	-3.55521
77	1.4	-3.9557	-1.80833	2.18748	-0.35392
78	-2.2	-1.16477	-2.325	0.500978	1.88878
79	-8.6	0.848946	-2.75	-0.308708	-10.1302
80	-5	-4.2622	-2.9	1.46972	1.1731
81	4.1	-7.49558	-3.77917	1.98339	-0.546989
82	0.7	-0.359283	-3.8125	0.0942382	-1.94833
83	-4.2	-3.62233	-3.2875	1.10185	1.15948
84	-2.3	12.2622	-3.53333	-3.47043	-0.187569
85	-3.4	-33.399	-3.17917	10.5056	0.101799
86	-4.2	2.90728	-2.72917	-1.06526	-1.44465
87	-14.2	-4.32984	-3.00833	1.43928	3.27957
88	1.6	8.38107	-3.4375	-2.43813	0.190906
89	-4.9	-6.75385	-3.0875	2.18748	0.725512
90	-1.8	-1.33594	-2.66667	0.500978	1.34736
91	-0.5	NA	NA	-0.308708	NA
92	-2.3	NA	NA	1.46972	NA
93	-5.3	NA	NA	1.98339	NA
94	-0.2	NA	NA	0.0942382	NA
95	5.1	NA	NA	1.10185	NA
96	-1.5	NA	NA	-3.47043	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 6 & NA & NA & 10.5056 & NA \tabularnewline
2 & 6.7 & NA & NA & -1.06526 & NA \tabularnewline
3 & -0.6 & NA & NA & 1.43928 & NA \tabularnewline
4 & 5.8 & NA & NA & -2.43813 & NA \tabularnewline
5 & 16.4 & NA & NA & 2.18748 & NA \tabularnewline
6 & 1.5 & NA & NA & 0.500978 & NA \tabularnewline
7 & 5.1 & -1.92042 & 6.22083 & -0.308708 & -2.65567 \tabularnewline
8 & 14.7 & 9.51034 & 6.47083 & 1.46972 & 1.54569 \tabularnewline
9 & 4.3 & 14.6027 & 7.3625 & 1.98339 & 0.294465 \tabularnewline
10 & 1.5 & 0.768434 & 8.15417 & 0.0942382 & 1.95202 \tabularnewline
11 & 9.1 & 8.195 & 7.4375 & 1.10185 & 1.11043 \tabularnewline
12 & 4.3 & -23.5989 & 6.8 & -3.47043 & -0.182212 \tabularnewline
13 & 5.7 & 74.0206 & 7.04583 & 10.5056 & 0.0770056 \tabularnewline
14 & 13 & -6.74667 & 6.33333 & -1.06526 & -1.92688 \tabularnewline
15 & 14.5 & 8.51575 & 5.91667 & 1.43928 & 1.70273 \tabularnewline
16 & 9.7 & -15.5024 & 6.35833 & -2.43813 & -0.625708 \tabularnewline
17 & -4.7 & 13.1705 & 6.02083 & 2.18748 & -0.356859 \tabularnewline
18 & 7.3 & 2.68023 & 5.35 & 0.500978 & 2.72364 \tabularnewline
19 & 5.2 & -1.5757 & 5.10417 & -0.308708 & -3.30013 \tabularnewline
20 & -2.5 & 7.10979 & 4.8375 & 1.46972 & -0.351628 \tabularnewline
21 & 11.5 & 7.17328 & 3.61667 & 1.98339 & 1.60317 \tabularnewline
22 & 4.9 & 0.191618 & 2.03333 & 0.0942382 & 25.5718 \tabularnewline
23 & -2.4 & 2.57557 & 2.3375 & 1.10185 & -0.931832 \tabularnewline
24 & -0.3 & -9.39908 & 2.70833 & -3.47043 & 0.031918 \tabularnewline
25 & 4.4 & 22.3681 & 2.12917 & 10.5056 & 0.196708 \tabularnewline
26 & 7.9 & -2.4723 & 2.32083 & -1.06526 & -3.19541 \tabularnewline
27 & -9.7 & 3.01649 & 2.09583 & 1.43928 & -3.21565 \tabularnewline
28 & -4.1 & -3.73847 & 1.53333 & -2.43813 & 1.09671 \tabularnewline
29 & 16.4 & 3.47263 & 1.5875 & 2.18748 & 4.72265 \tabularnewline
30 & -4.9 & 0.807828 & 1.6125 & 0.500978 & -6.06565 \tabularnewline
31 & 3.5 & -0.484928 & 1.57083 & -0.308708 & -7.21756 \tabularnewline
32 & 3.8 & 1.5922 & 1.08333 & 1.46972 & 2.38663 \tabularnewline
33 & -0.2 & 1.61977 & 0.816667 & 1.98339 & -0.123474 \tabularnewline
34 & 3.1 & 0.145676 & 1.54583 & 0.0942382 & 21.28 \tabularnewline
35 & 0.7 & 1.06971 & 0.970833 & 1.10185 & 0.654382 \tabularnewline
36 & -2.8 & -0.723006 & 0.208333 & -3.47043 & 3.87272 \tabularnewline
37 & 5.9 & 6.3909 & 0.608333 & 10.5056 & 0.923188 \tabularnewline
38 & -5.3 & -0.310702 & 0.291667 & -1.06526 & 17.0582 \tabularnewline
39 & -2.9 & -0.341829 & -0.2375 & 1.43928 & 8.48377 \tabularnewline
40 & 6.6 & 0.660327 & -0.270833 & -2.43813 & 9.99505 \tabularnewline
41 & -8.1 & -1.09374 & -0.5 & 2.18748 & 7.40578 \tabularnewline
42 & 1.3 & -0.244227 & -0.4875 & 0.500978 & -5.32292 \tabularnewline
43 & 6.9 & 0.237962 & -0.770833 & -0.308708 & 28.9962 \tabularnewline
44 & -7.2 & -1.69018 & -1.15 & 1.46972 & 4.25989 \tabularnewline
45 & -1.9 & -1.07434 & -0.541667 & 1.98339 & 1.76853 \tabularnewline
46 & 4 & -0.0514383 & -0.545833 & 0.0942382 & -77.763 \tabularnewline
47 & -5.7 & -0.817204 & -0.741667 & 1.10185 & 6.975 \tabularnewline
48 & 3.9 & 0.607325 & -0.175 & -3.47043 & 6.4216 \tabularnewline
49 & -7.6 & -0.787919 & -0.075 & 10.5056 & 9.64566 \tabularnewline
50 & -0.9 & -0.41279 & 0.3875 & -1.06526 & 2.18029 \tabularnewline
51 & 7.3 & 2.35083 & 1.63333 & 1.43928 & 3.10529 \tabularnewline
52 & -3.7 & -4.74419 & 1.94583 & -2.43813 & 0.7799 \tabularnewline
53 & -2.5 & 4.98563 & 2.27917 & 2.18748 & -0.501441 \tabularnewline
54 & 9.3 & 1.24618 & 2.4875 & 0.500978 & 7.46278 \tabularnewline
55 & 1.3 & -0.774342 & 2.50833 & -0.308708 & -1.67884 \tabularnewline
56 & 9.5 & 4.42142 & 3.00833 & 1.46972 & 2.14863 \tabularnewline
57 & 11.3 & 5.52045 & 2.78333 & 1.98339 & 2.04693 \tabularnewline
58 & -1.7 & 0.266223 & 2.825 & 0.0942382 & -6.38563 \tabularnewline
59 & 8 & 3.72792 & 3.38333 & 1.10185 & 2.14597 \tabularnewline
60 & -4.8 & -10.2233 & 2.94583 & -3.47043 & 0.469515 \tabularnewline
61 & 1.6 & 24.7757 & 2.35833 & 10.5056 & 0.0645795 \tabularnewline
62 & 1.9 & -2.12609 & 1.99583 & -1.06526 & -0.89366 \tabularnewline
63 & -0.9 & 0.839581 & 0.583333 & 1.43928 & -1.07196 \tabularnewline
64 & 5.5 & 1.73717 & -0.7125 & -2.43813 & 3.16607 \tabularnewline
65 & 1.7 & -2.86195 & -1.30833 & 2.18748 & -0.594 \tabularnewline
66 & -5.4 & -0.599087 & -1.19583 & 0.500978 & 9.01372 \tabularnewline
67 & 1.9 & 0.270119 & -0.875 & -0.308708 & 7.03393 \tabularnewline
68 & 0.2 & -1.7453 & -1.1875 & 1.46972 & -0.114594 \tabularnewline
69 & -13.3 & -2.21479 & -1.11667 & 1.98339 & 6.00508 \tabularnewline
70 & -8.2 & -0.169629 & -1.8 & 0.0942382 & 48.3409 \tabularnewline
71 & 0.2 & -3.04386 & -2.7625 & 1.10185 & -0.0657061 \tabularnewline
72 & 5.7 & 9.16772 & -2.64167 & -3.47043 & 0.621747 \tabularnewline
73 & -1.2 & -30.9477 & -2.94583 & 10.5056 & 0.0387751 \tabularnewline
74 & -2.8 & 3.83495 & -3.6 & -1.06526 & -0.730127 \tabularnewline
75 & 5.5 & -4.44978 & -3.09167 & 1.43928 & -1.23602 \tabularnewline
76 & -17.3 & 4.8661 & -1.99583 & -2.43813 & -3.55521 \tabularnewline
77 & 1.4 & -3.9557 & -1.80833 & 2.18748 & -0.35392 \tabularnewline
78 & -2.2 & -1.16477 & -2.325 & 0.500978 & 1.88878 \tabularnewline
79 & -8.6 & 0.848946 & -2.75 & -0.308708 & -10.1302 \tabularnewline
80 & -5 & -4.2622 & -2.9 & 1.46972 & 1.1731 \tabularnewline
81 & 4.1 & -7.49558 & -3.77917 & 1.98339 & -0.546989 \tabularnewline
82 & 0.7 & -0.359283 & -3.8125 & 0.0942382 & -1.94833 \tabularnewline
83 & -4.2 & -3.62233 & -3.2875 & 1.10185 & 1.15948 \tabularnewline
84 & -2.3 & 12.2622 & -3.53333 & -3.47043 & -0.187569 \tabularnewline
85 & -3.4 & -33.399 & -3.17917 & 10.5056 & 0.101799 \tabularnewline
86 & -4.2 & 2.90728 & -2.72917 & -1.06526 & -1.44465 \tabularnewline
87 & -14.2 & -4.32984 & -3.00833 & 1.43928 & 3.27957 \tabularnewline
88 & 1.6 & 8.38107 & -3.4375 & -2.43813 & 0.190906 \tabularnewline
89 & -4.9 & -6.75385 & -3.0875 & 2.18748 & 0.725512 \tabularnewline
90 & -1.8 & -1.33594 & -2.66667 & 0.500978 & 1.34736 \tabularnewline
91 & -0.5 & NA & NA & -0.308708 & NA \tabularnewline
92 & -2.3 & NA & NA & 1.46972 & NA \tabularnewline
93 & -5.3 & NA & NA & 1.98339 & NA \tabularnewline
94 & -0.2 & NA & NA & 0.0942382 & NA \tabularnewline
95 & 5.1 & NA & NA & 1.10185 & NA \tabularnewline
96 & -1.5 & NA & NA & -3.47043 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278487&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]6[/C][C]NA[/C][C]NA[/C][C]10.5056[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]6.7[/C][C]NA[/C][C]NA[/C][C]-1.06526[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]-0.6[/C][C]NA[/C][C]NA[/C][C]1.43928[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]-2.43813[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]16.4[/C][C]NA[/C][C]NA[/C][C]2.18748[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.5[/C][C]NA[/C][C]NA[/C][C]0.500978[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.1[/C][C]-1.92042[/C][C]6.22083[/C][C]-0.308708[/C][C]-2.65567[/C][/ROW]
[ROW][C]8[/C][C]14.7[/C][C]9.51034[/C][C]6.47083[/C][C]1.46972[/C][C]1.54569[/C][/ROW]
[ROW][C]9[/C][C]4.3[/C][C]14.6027[/C][C]7.3625[/C][C]1.98339[/C][C]0.294465[/C][/ROW]
[ROW][C]10[/C][C]1.5[/C][C]0.768434[/C][C]8.15417[/C][C]0.0942382[/C][C]1.95202[/C][/ROW]
[ROW][C]11[/C][C]9.1[/C][C]8.195[/C][C]7.4375[/C][C]1.10185[/C][C]1.11043[/C][/ROW]
[ROW][C]12[/C][C]4.3[/C][C]-23.5989[/C][C]6.8[/C][C]-3.47043[/C][C]-0.182212[/C][/ROW]
[ROW][C]13[/C][C]5.7[/C][C]74.0206[/C][C]7.04583[/C][C]10.5056[/C][C]0.0770056[/C][/ROW]
[ROW][C]14[/C][C]13[/C][C]-6.74667[/C][C]6.33333[/C][C]-1.06526[/C][C]-1.92688[/C][/ROW]
[ROW][C]15[/C][C]14.5[/C][C]8.51575[/C][C]5.91667[/C][C]1.43928[/C][C]1.70273[/C][/ROW]
[ROW][C]16[/C][C]9.7[/C][C]-15.5024[/C][C]6.35833[/C][C]-2.43813[/C][C]-0.625708[/C][/ROW]
[ROW][C]17[/C][C]-4.7[/C][C]13.1705[/C][C]6.02083[/C][C]2.18748[/C][C]-0.356859[/C][/ROW]
[ROW][C]18[/C][C]7.3[/C][C]2.68023[/C][C]5.35[/C][C]0.500978[/C][C]2.72364[/C][/ROW]
[ROW][C]19[/C][C]5.2[/C][C]-1.5757[/C][C]5.10417[/C][C]-0.308708[/C][C]-3.30013[/C][/ROW]
[ROW][C]20[/C][C]-2.5[/C][C]7.10979[/C][C]4.8375[/C][C]1.46972[/C][C]-0.351628[/C][/ROW]
[ROW][C]21[/C][C]11.5[/C][C]7.17328[/C][C]3.61667[/C][C]1.98339[/C][C]1.60317[/C][/ROW]
[ROW][C]22[/C][C]4.9[/C][C]0.191618[/C][C]2.03333[/C][C]0.0942382[/C][C]25.5718[/C][/ROW]
[ROW][C]23[/C][C]-2.4[/C][C]2.57557[/C][C]2.3375[/C][C]1.10185[/C][C]-0.931832[/C][/ROW]
[ROW][C]24[/C][C]-0.3[/C][C]-9.39908[/C][C]2.70833[/C][C]-3.47043[/C][C]0.031918[/C][/ROW]
[ROW][C]25[/C][C]4.4[/C][C]22.3681[/C][C]2.12917[/C][C]10.5056[/C][C]0.196708[/C][/ROW]
[ROW][C]26[/C][C]7.9[/C][C]-2.4723[/C][C]2.32083[/C][C]-1.06526[/C][C]-3.19541[/C][/ROW]
[ROW][C]27[/C][C]-9.7[/C][C]3.01649[/C][C]2.09583[/C][C]1.43928[/C][C]-3.21565[/C][/ROW]
[ROW][C]28[/C][C]-4.1[/C][C]-3.73847[/C][C]1.53333[/C][C]-2.43813[/C][C]1.09671[/C][/ROW]
[ROW][C]29[/C][C]16.4[/C][C]3.47263[/C][C]1.5875[/C][C]2.18748[/C][C]4.72265[/C][/ROW]
[ROW][C]30[/C][C]-4.9[/C][C]0.807828[/C][C]1.6125[/C][C]0.500978[/C][C]-6.06565[/C][/ROW]
[ROW][C]31[/C][C]3.5[/C][C]-0.484928[/C][C]1.57083[/C][C]-0.308708[/C][C]-7.21756[/C][/ROW]
[ROW][C]32[/C][C]3.8[/C][C]1.5922[/C][C]1.08333[/C][C]1.46972[/C][C]2.38663[/C][/ROW]
[ROW][C]33[/C][C]-0.2[/C][C]1.61977[/C][C]0.816667[/C][C]1.98339[/C][C]-0.123474[/C][/ROW]
[ROW][C]34[/C][C]3.1[/C][C]0.145676[/C][C]1.54583[/C][C]0.0942382[/C][C]21.28[/C][/ROW]
[ROW][C]35[/C][C]0.7[/C][C]1.06971[/C][C]0.970833[/C][C]1.10185[/C][C]0.654382[/C][/ROW]
[ROW][C]36[/C][C]-2.8[/C][C]-0.723006[/C][C]0.208333[/C][C]-3.47043[/C][C]3.87272[/C][/ROW]
[ROW][C]37[/C][C]5.9[/C][C]6.3909[/C][C]0.608333[/C][C]10.5056[/C][C]0.923188[/C][/ROW]
[ROW][C]38[/C][C]-5.3[/C][C]-0.310702[/C][C]0.291667[/C][C]-1.06526[/C][C]17.0582[/C][/ROW]
[ROW][C]39[/C][C]-2.9[/C][C]-0.341829[/C][C]-0.2375[/C][C]1.43928[/C][C]8.48377[/C][/ROW]
[ROW][C]40[/C][C]6.6[/C][C]0.660327[/C][C]-0.270833[/C][C]-2.43813[/C][C]9.99505[/C][/ROW]
[ROW][C]41[/C][C]-8.1[/C][C]-1.09374[/C][C]-0.5[/C][C]2.18748[/C][C]7.40578[/C][/ROW]
[ROW][C]42[/C][C]1.3[/C][C]-0.244227[/C][C]-0.4875[/C][C]0.500978[/C][C]-5.32292[/C][/ROW]
[ROW][C]43[/C][C]6.9[/C][C]0.237962[/C][C]-0.770833[/C][C]-0.308708[/C][C]28.9962[/C][/ROW]
[ROW][C]44[/C][C]-7.2[/C][C]-1.69018[/C][C]-1.15[/C][C]1.46972[/C][C]4.25989[/C][/ROW]
[ROW][C]45[/C][C]-1.9[/C][C]-1.07434[/C][C]-0.541667[/C][C]1.98339[/C][C]1.76853[/C][/ROW]
[ROW][C]46[/C][C]4[/C][C]-0.0514383[/C][C]-0.545833[/C][C]0.0942382[/C][C]-77.763[/C][/ROW]
[ROW][C]47[/C][C]-5.7[/C][C]-0.817204[/C][C]-0.741667[/C][C]1.10185[/C][C]6.975[/C][/ROW]
[ROW][C]48[/C][C]3.9[/C][C]0.607325[/C][C]-0.175[/C][C]-3.47043[/C][C]6.4216[/C][/ROW]
[ROW][C]49[/C][C]-7.6[/C][C]-0.787919[/C][C]-0.075[/C][C]10.5056[/C][C]9.64566[/C][/ROW]
[ROW][C]50[/C][C]-0.9[/C][C]-0.41279[/C][C]0.3875[/C][C]-1.06526[/C][C]2.18029[/C][/ROW]
[ROW][C]51[/C][C]7.3[/C][C]2.35083[/C][C]1.63333[/C][C]1.43928[/C][C]3.10529[/C][/ROW]
[ROW][C]52[/C][C]-3.7[/C][C]-4.74419[/C][C]1.94583[/C][C]-2.43813[/C][C]0.7799[/C][/ROW]
[ROW][C]53[/C][C]-2.5[/C][C]4.98563[/C][C]2.27917[/C][C]2.18748[/C][C]-0.501441[/C][/ROW]
[ROW][C]54[/C][C]9.3[/C][C]1.24618[/C][C]2.4875[/C][C]0.500978[/C][C]7.46278[/C][/ROW]
[ROW][C]55[/C][C]1.3[/C][C]-0.774342[/C][C]2.50833[/C][C]-0.308708[/C][C]-1.67884[/C][/ROW]
[ROW][C]56[/C][C]9.5[/C][C]4.42142[/C][C]3.00833[/C][C]1.46972[/C][C]2.14863[/C][/ROW]
[ROW][C]57[/C][C]11.3[/C][C]5.52045[/C][C]2.78333[/C][C]1.98339[/C][C]2.04693[/C][/ROW]
[ROW][C]58[/C][C]-1.7[/C][C]0.266223[/C][C]2.825[/C][C]0.0942382[/C][C]-6.38563[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]3.72792[/C][C]3.38333[/C][C]1.10185[/C][C]2.14597[/C][/ROW]
[ROW][C]60[/C][C]-4.8[/C][C]-10.2233[/C][C]2.94583[/C][C]-3.47043[/C][C]0.469515[/C][/ROW]
[ROW][C]61[/C][C]1.6[/C][C]24.7757[/C][C]2.35833[/C][C]10.5056[/C][C]0.0645795[/C][/ROW]
[ROW][C]62[/C][C]1.9[/C][C]-2.12609[/C][C]1.99583[/C][C]-1.06526[/C][C]-0.89366[/C][/ROW]
[ROW][C]63[/C][C]-0.9[/C][C]0.839581[/C][C]0.583333[/C][C]1.43928[/C][C]-1.07196[/C][/ROW]
[ROW][C]64[/C][C]5.5[/C][C]1.73717[/C][C]-0.7125[/C][C]-2.43813[/C][C]3.16607[/C][/ROW]
[ROW][C]65[/C][C]1.7[/C][C]-2.86195[/C][C]-1.30833[/C][C]2.18748[/C][C]-0.594[/C][/ROW]
[ROW][C]66[/C][C]-5.4[/C][C]-0.599087[/C][C]-1.19583[/C][C]0.500978[/C][C]9.01372[/C][/ROW]
[ROW][C]67[/C][C]1.9[/C][C]0.270119[/C][C]-0.875[/C][C]-0.308708[/C][C]7.03393[/C][/ROW]
[ROW][C]68[/C][C]0.2[/C][C]-1.7453[/C][C]-1.1875[/C][C]1.46972[/C][C]-0.114594[/C][/ROW]
[ROW][C]69[/C][C]-13.3[/C][C]-2.21479[/C][C]-1.11667[/C][C]1.98339[/C][C]6.00508[/C][/ROW]
[ROW][C]70[/C][C]-8.2[/C][C]-0.169629[/C][C]-1.8[/C][C]0.0942382[/C][C]48.3409[/C][/ROW]
[ROW][C]71[/C][C]0.2[/C][C]-3.04386[/C][C]-2.7625[/C][C]1.10185[/C][C]-0.0657061[/C][/ROW]
[ROW][C]72[/C][C]5.7[/C][C]9.16772[/C][C]-2.64167[/C][C]-3.47043[/C][C]0.621747[/C][/ROW]
[ROW][C]73[/C][C]-1.2[/C][C]-30.9477[/C][C]-2.94583[/C][C]10.5056[/C][C]0.0387751[/C][/ROW]
[ROW][C]74[/C][C]-2.8[/C][C]3.83495[/C][C]-3.6[/C][C]-1.06526[/C][C]-0.730127[/C][/ROW]
[ROW][C]75[/C][C]5.5[/C][C]-4.44978[/C][C]-3.09167[/C][C]1.43928[/C][C]-1.23602[/C][/ROW]
[ROW][C]76[/C][C]-17.3[/C][C]4.8661[/C][C]-1.99583[/C][C]-2.43813[/C][C]-3.55521[/C][/ROW]
[ROW][C]77[/C][C]1.4[/C][C]-3.9557[/C][C]-1.80833[/C][C]2.18748[/C][C]-0.35392[/C][/ROW]
[ROW][C]78[/C][C]-2.2[/C][C]-1.16477[/C][C]-2.325[/C][C]0.500978[/C][C]1.88878[/C][/ROW]
[ROW][C]79[/C][C]-8.6[/C][C]0.848946[/C][C]-2.75[/C][C]-0.308708[/C][C]-10.1302[/C][/ROW]
[ROW][C]80[/C][C]-5[/C][C]-4.2622[/C][C]-2.9[/C][C]1.46972[/C][C]1.1731[/C][/ROW]
[ROW][C]81[/C][C]4.1[/C][C]-7.49558[/C][C]-3.77917[/C][C]1.98339[/C][C]-0.546989[/C][/ROW]
[ROW][C]82[/C][C]0.7[/C][C]-0.359283[/C][C]-3.8125[/C][C]0.0942382[/C][C]-1.94833[/C][/ROW]
[ROW][C]83[/C][C]-4.2[/C][C]-3.62233[/C][C]-3.2875[/C][C]1.10185[/C][C]1.15948[/C][/ROW]
[ROW][C]84[/C][C]-2.3[/C][C]12.2622[/C][C]-3.53333[/C][C]-3.47043[/C][C]-0.187569[/C][/ROW]
[ROW][C]85[/C][C]-3.4[/C][C]-33.399[/C][C]-3.17917[/C][C]10.5056[/C][C]0.101799[/C][/ROW]
[ROW][C]86[/C][C]-4.2[/C][C]2.90728[/C][C]-2.72917[/C][C]-1.06526[/C][C]-1.44465[/C][/ROW]
[ROW][C]87[/C][C]-14.2[/C][C]-4.32984[/C][C]-3.00833[/C][C]1.43928[/C][C]3.27957[/C][/ROW]
[ROW][C]88[/C][C]1.6[/C][C]8.38107[/C][C]-3.4375[/C][C]-2.43813[/C][C]0.190906[/C][/ROW]
[ROW][C]89[/C][C]-4.9[/C][C]-6.75385[/C][C]-3.0875[/C][C]2.18748[/C][C]0.725512[/C][/ROW]
[ROW][C]90[/C][C]-1.8[/C][C]-1.33594[/C][C]-2.66667[/C][C]0.500978[/C][C]1.34736[/C][/ROW]
[ROW][C]91[/C][C]-0.5[/C][C]NA[/C][C]NA[/C][C]-0.308708[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]-2.3[/C][C]NA[/C][C]NA[/C][C]1.46972[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]-5.3[/C][C]NA[/C][C]NA[/C][C]1.98339[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]-0.2[/C][C]NA[/C][C]NA[/C][C]0.0942382[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]5.1[/C][C]NA[/C][C]NA[/C][C]1.10185[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]-1.5[/C][C]NA[/C][C]NA[/C][C]-3.47043[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278487&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	6	NA	NA	10.5056	NA
2	6.7	NA	NA	-1.06526	NA
3	-0.6	NA	NA	1.43928	NA
4	5.8	NA	NA	-2.43813	NA
5	16.4	NA	NA	2.18748	NA
6	1.5	NA	NA	0.500978	NA
7	5.1	-1.92042	6.22083	-0.308708	-2.65567
8	14.7	9.51034	6.47083	1.46972	1.54569
9	4.3	14.6027	7.3625	1.98339	0.294465
10	1.5	0.768434	8.15417	0.0942382	1.95202
11	9.1	8.195	7.4375	1.10185	1.11043
12	4.3	-23.5989	6.8	-3.47043	-0.182212
13	5.7	74.0206	7.04583	10.5056	0.0770056
14	13	-6.74667	6.33333	-1.06526	-1.92688
15	14.5	8.51575	5.91667	1.43928	1.70273
16	9.7	-15.5024	6.35833	-2.43813	-0.625708
17	-4.7	13.1705	6.02083	2.18748	-0.356859
18	7.3	2.68023	5.35	0.500978	2.72364
19	5.2	-1.5757	5.10417	-0.308708	-3.30013
20	-2.5	7.10979	4.8375	1.46972	-0.351628
21	11.5	7.17328	3.61667	1.98339	1.60317
22	4.9	0.191618	2.03333	0.0942382	25.5718
23	-2.4	2.57557	2.3375	1.10185	-0.931832
24	-0.3	-9.39908	2.70833	-3.47043	0.031918
25	4.4	22.3681	2.12917	10.5056	0.196708
26	7.9	-2.4723	2.32083	-1.06526	-3.19541
27	-9.7	3.01649	2.09583	1.43928	-3.21565
28	-4.1	-3.73847	1.53333	-2.43813	1.09671
29	16.4	3.47263	1.5875	2.18748	4.72265
30	-4.9	0.807828	1.6125	0.500978	-6.06565
31	3.5	-0.484928	1.57083	-0.308708	-7.21756
32	3.8	1.5922	1.08333	1.46972	2.38663
33	-0.2	1.61977	0.816667	1.98339	-0.123474
34	3.1	0.145676	1.54583	0.0942382	21.28
35	0.7	1.06971	0.970833	1.10185	0.654382
36	-2.8	-0.723006	0.208333	-3.47043	3.87272
37	5.9	6.3909	0.608333	10.5056	0.923188
38	-5.3	-0.310702	0.291667	-1.06526	17.0582
39	-2.9	-0.341829	-0.2375	1.43928	8.48377
40	6.6	0.660327	-0.270833	-2.43813	9.99505
41	-8.1	-1.09374	-0.5	2.18748	7.40578
42	1.3	-0.244227	-0.4875	0.500978	-5.32292
43	6.9	0.237962	-0.770833	-0.308708	28.9962
44	-7.2	-1.69018	-1.15	1.46972	4.25989
45	-1.9	-1.07434	-0.541667	1.98339	1.76853
46	4	-0.0514383	-0.545833	0.0942382	-77.763
47	-5.7	-0.817204	-0.741667	1.10185	6.975
48	3.9	0.607325	-0.175	-3.47043	6.4216
49	-7.6	-0.787919	-0.075	10.5056	9.64566
50	-0.9	-0.41279	0.3875	-1.06526	2.18029
51	7.3	2.35083	1.63333	1.43928	3.10529
52	-3.7	-4.74419	1.94583	-2.43813	0.7799
53	-2.5	4.98563	2.27917	2.18748	-0.501441
54	9.3	1.24618	2.4875	0.500978	7.46278
55	1.3	-0.774342	2.50833	-0.308708	-1.67884
56	9.5	4.42142	3.00833	1.46972	2.14863
57	11.3	5.52045	2.78333	1.98339	2.04693
58	-1.7	0.266223	2.825	0.0942382	-6.38563
59	8	3.72792	3.38333	1.10185	2.14597
60	-4.8	-10.2233	2.94583	-3.47043	0.469515
61	1.6	24.7757	2.35833	10.5056	0.0645795
62	1.9	-2.12609	1.99583	-1.06526	-0.89366
63	-0.9	0.839581	0.583333	1.43928	-1.07196
64	5.5	1.73717	-0.7125	-2.43813	3.16607
65	1.7	-2.86195	-1.30833	2.18748	-0.594
66	-5.4	-0.599087	-1.19583	0.500978	9.01372
67	1.9	0.270119	-0.875	-0.308708	7.03393
68	0.2	-1.7453	-1.1875	1.46972	-0.114594
69	-13.3	-2.21479	-1.11667	1.98339	6.00508
70	-8.2	-0.169629	-1.8	0.0942382	48.3409
71	0.2	-3.04386	-2.7625	1.10185	-0.0657061
72	5.7	9.16772	-2.64167	-3.47043	0.621747
73	-1.2	-30.9477	-2.94583	10.5056	0.0387751
74	-2.8	3.83495	-3.6	-1.06526	-0.730127
75	5.5	-4.44978	-3.09167	1.43928	-1.23602
76	-17.3	4.8661	-1.99583	-2.43813	-3.55521
77	1.4	-3.9557	-1.80833	2.18748	-0.35392
78	-2.2	-1.16477	-2.325	0.500978	1.88878
79	-8.6	0.848946	-2.75	-0.308708	-10.1302
80	-5	-4.2622	-2.9	1.46972	1.1731
81	4.1	-7.49558	-3.77917	1.98339	-0.546989
82	0.7	-0.359283	-3.8125	0.0942382	-1.94833
83	-4.2	-3.62233	-3.2875	1.10185	1.15948
84	-2.3	12.2622	-3.53333	-3.47043	-0.187569
85	-3.4	-33.399	-3.17917	10.5056	0.101799
86	-4.2	2.90728	-2.72917	-1.06526	-1.44465
87	-14.2	-4.32984	-3.00833	1.43928	3.27957
88	1.6	8.38107	-3.4375	-2.43813	0.190906
89	-4.9	-6.75385	-3.0875	2.18748	0.725512
90	-1.8	-1.33594	-2.66667	0.500978	1.34736
91	-0.5	NA	NA	-0.308708	NA
92	-2.3	NA	NA	1.46972	NA
93	-5.3	NA	NA	1.98339	NA
94	-0.2	NA	NA	0.0942382	NA
95	5.1	NA	NA	1.10185	NA
96	-1.5	NA	NA	-3.47043	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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