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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 11 May 2014 16:25:52 -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/11/t1399840002t3847lljarf480j.htm/, Retrieved Tue, 14 May 2024 04:09:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234799, Retrieved Tue, 14 May 2024 04:09:54 +0000

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Estimated Impact

139

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-       [Classical Decomposition] [] [2014-05-11 20:25:52] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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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

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=234799&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=234799&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234799&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	6	NA	NA	-0.0750579	NA
2	6.7	NA	NA	0.99022	NA
3	-0.6	NA	NA	1.12841	NA
4	5.8	NA	NA	-1.71464	NA
5	16.4	NA	NA	-0.366725	NA
6	1.5	NA	NA	-0.0285301	NA
7	5.1	7.88953	6.22083	1.66869	-2.78953
8	14.7	7.3555	6.47083	0.884664	7.3445
9	4.3	7.13744	7.3625	-0.225058	-2.83744
10	1.5	6.69716	8.15417	-1.457	-5.19716
11	9.1	7.29508	7.4375	-0.142419	1.80492
12	4.3	6.13744	6.8	-0.662558	-1.83744
13	5.7	6.97078	7.04583	-0.0750579	-1.27078
14	13	7.32355	6.33333	0.99022	5.67645
15	14.5	7.04508	5.91667	1.12841	7.45492
16	9.7	4.64369	6.35833	-1.71464	5.05631
17	-4.7	5.65411	6.02083	-0.366725	-10.3541
18	7.3	5.32147	5.35	-0.0285301	1.97853
19	5.2	6.77286	5.10417	1.66869	-1.57286
20	-2.5	5.72216	4.8375	0.884664	-8.22216
21	11.5	3.39161	3.61667	-0.225058	8.10839
22	4.9	0.576331	2.03333	-1.457	4.32367
23	-2.4	2.19508	2.3375	-0.142419	-4.59508
24	-0.3	2.04578	2.70833	-0.662558	-2.34578
25	4.4	2.05411	2.12917	-0.0750579	2.34589
26	7.9	3.31105	2.32083	0.99022	4.58895
27	-9.7	3.22425	2.09583	1.12841	-12.9242
28	-4.1	-0.181308	1.53333	-1.71464	-3.91869
29	16.4	1.22078	1.5875	-0.366725	15.1792
30	-4.9	1.58397	1.6125	-0.0285301	-6.48397
31	3.5	3.23953	1.57083	1.66869	0.260475
32	3.8	1.968	1.08333	0.884664	1.832
33	-0.2	0.591609	0.816667	-0.225058	-0.791609
34	3.1	0.088831	1.54583	-1.457	3.01117
35	0.7	0.828414	0.970833	-0.142419	-0.128414
36	-2.8	-0.454225	0.208333	-0.662558	-2.34578
37	5.9	0.533275	0.608333	-0.0750579	5.36672
38	-5.3	1.28189	0.291667	0.99022	-6.58189
39	-2.9	0.890914	-0.2375	1.12841	-3.79091
40	6.6	-1.98547	-0.270833	-1.71464	8.58547
41	-8.1	-0.866725	-0.5	-0.366725	-7.23328
42	1.3	-0.51603	-0.4875	-0.0285301	1.81603
43	6.9	0.897859	-0.770833	1.66869	6.00214
44	-7.2	-0.265336	-1.15	0.884664	-6.93466
45	-1.9	-0.766725	-0.541667	-0.225058	-1.13328
46	4	-2.00284	-0.545833	-1.457	6.00284
47	-5.7	-0.884086	-0.741667	-0.142419	-4.81591
48	3.9	-0.837558	-0.175	-0.662558	4.73756
49	-7.6	-0.150058	-0.075	-0.0750579	-7.44994
50	-0.9	1.37772	0.3875	0.99022	-2.27772
51	7.3	2.76175	1.63333	1.12841	4.53825
52	-3.7	0.231192	1.94583	-1.71464	-3.93119
53	-2.5	1.91244	2.27917	-0.366725	-4.41244
54	9.3	2.45897	2.4875	-0.0285301	6.84103
55	1.3	4.17703	2.50833	1.66869	-2.87703
56	9.5	3.893	3.00833	0.884664	5.607
57	11.3	2.55828	2.78333	-0.225058	8.74172
58	-1.7	1.368	2.825	-1.457	-3.068
59	8	3.24091	3.38333	-0.142419	4.75909
60	-4.8	2.28328	2.94583	-0.662558	-7.08328
61	1.6	2.28328	2.35833	-0.0750579	-0.683275
62	1.9	2.98605	1.99583	0.99022	-1.08605
63	-0.9	1.71175	0.583333	1.12841	-2.61175
64	5.5	-2.42714	-0.7125	-1.71464	7.92714
65	1.7	-1.67506	-1.30833	-0.366725	3.37506
66	-5.4	-1.22436	-1.19583	-0.0285301	-4.17564
67	1.9	0.793692	-0.875	1.66869	1.10631
68	0.2	-0.302836	-1.1875	0.884664	0.502836
69	-13.3	-1.34172	-1.11667	-0.225058	-11.9583
70	-8.2	-3.257	-1.8	-1.457	-4.943
71	0.2	-2.90492	-2.7625	-0.142419	3.10492
72	5.7	-3.30422	-2.64167	-0.662558	9.00422
73	-1.2	-3.02089	-2.94583	-0.0750579	1.82089
74	-2.8	-2.60978	-3.6	0.99022	-0.19022
75	5.5	-1.96325	-3.09167	1.12841	7.46325
76	-17.3	-3.71047	-1.99583	-1.71464	-13.5895
77	1.4	-2.17506	-1.80833	-0.366725	3.57506
78	-2.2	-2.35353	-2.325	-0.0285301	0.15353
79	-8.6	NA	NA	1.66869	NA
80	-5	NA	NA	0.884664	NA
81	4.1	NA	NA	-0.225058	NA
82	0.7	NA	NA	-1.457	NA
83	-4.2	NA	NA	-0.142419	NA
84	-2.3	NA	NA	-0.662558	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 6 & NA & NA & -0.0750579 & NA \tabularnewline
2 & 6.7 & NA & NA & 0.99022 & NA \tabularnewline
3 & -0.6 & NA & NA & 1.12841 & NA \tabularnewline
4 & 5.8 & NA & NA & -1.71464 & NA \tabularnewline
5 & 16.4 & NA & NA & -0.366725 & NA \tabularnewline
6 & 1.5 & NA & NA & -0.0285301 & NA \tabularnewline
7 & 5.1 & 7.88953 & 6.22083 & 1.66869 & -2.78953 \tabularnewline
8 & 14.7 & 7.3555 & 6.47083 & 0.884664 & 7.3445 \tabularnewline
9 & 4.3 & 7.13744 & 7.3625 & -0.225058 & -2.83744 \tabularnewline
10 & 1.5 & 6.69716 & 8.15417 & -1.457 & -5.19716 \tabularnewline
11 & 9.1 & 7.29508 & 7.4375 & -0.142419 & 1.80492 \tabularnewline
12 & 4.3 & 6.13744 & 6.8 & -0.662558 & -1.83744 \tabularnewline
13 & 5.7 & 6.97078 & 7.04583 & -0.0750579 & -1.27078 \tabularnewline
14 & 13 & 7.32355 & 6.33333 & 0.99022 & 5.67645 \tabularnewline
15 & 14.5 & 7.04508 & 5.91667 & 1.12841 & 7.45492 \tabularnewline
16 & 9.7 & 4.64369 & 6.35833 & -1.71464 & 5.05631 \tabularnewline
17 & -4.7 & 5.65411 & 6.02083 & -0.366725 & -10.3541 \tabularnewline
18 & 7.3 & 5.32147 & 5.35 & -0.0285301 & 1.97853 \tabularnewline
19 & 5.2 & 6.77286 & 5.10417 & 1.66869 & -1.57286 \tabularnewline
20 & -2.5 & 5.72216 & 4.8375 & 0.884664 & -8.22216 \tabularnewline
21 & 11.5 & 3.39161 & 3.61667 & -0.225058 & 8.10839 \tabularnewline
22 & 4.9 & 0.576331 & 2.03333 & -1.457 & 4.32367 \tabularnewline
23 & -2.4 & 2.19508 & 2.3375 & -0.142419 & -4.59508 \tabularnewline
24 & -0.3 & 2.04578 & 2.70833 & -0.662558 & -2.34578 \tabularnewline
25 & 4.4 & 2.05411 & 2.12917 & -0.0750579 & 2.34589 \tabularnewline
26 & 7.9 & 3.31105 & 2.32083 & 0.99022 & 4.58895 \tabularnewline
27 & -9.7 & 3.22425 & 2.09583 & 1.12841 & -12.9242 \tabularnewline
28 & -4.1 & -0.181308 & 1.53333 & -1.71464 & -3.91869 \tabularnewline
29 & 16.4 & 1.22078 & 1.5875 & -0.366725 & 15.1792 \tabularnewline
30 & -4.9 & 1.58397 & 1.6125 & -0.0285301 & -6.48397 \tabularnewline
31 & 3.5 & 3.23953 & 1.57083 & 1.66869 & 0.260475 \tabularnewline
32 & 3.8 & 1.968 & 1.08333 & 0.884664 & 1.832 \tabularnewline
33 & -0.2 & 0.591609 & 0.816667 & -0.225058 & -0.791609 \tabularnewline
34 & 3.1 & 0.088831 & 1.54583 & -1.457 & 3.01117 \tabularnewline
35 & 0.7 & 0.828414 & 0.970833 & -0.142419 & -0.128414 \tabularnewline
36 & -2.8 & -0.454225 & 0.208333 & -0.662558 & -2.34578 \tabularnewline
37 & 5.9 & 0.533275 & 0.608333 & -0.0750579 & 5.36672 \tabularnewline
38 & -5.3 & 1.28189 & 0.291667 & 0.99022 & -6.58189 \tabularnewline
39 & -2.9 & 0.890914 & -0.2375 & 1.12841 & -3.79091 \tabularnewline
40 & 6.6 & -1.98547 & -0.270833 & -1.71464 & 8.58547 \tabularnewline
41 & -8.1 & -0.866725 & -0.5 & -0.366725 & -7.23328 \tabularnewline
42 & 1.3 & -0.51603 & -0.4875 & -0.0285301 & 1.81603 \tabularnewline
43 & 6.9 & 0.897859 & -0.770833 & 1.66869 & 6.00214 \tabularnewline
44 & -7.2 & -0.265336 & -1.15 & 0.884664 & -6.93466 \tabularnewline
45 & -1.9 & -0.766725 & -0.541667 & -0.225058 & -1.13328 \tabularnewline
46 & 4 & -2.00284 & -0.545833 & -1.457 & 6.00284 \tabularnewline
47 & -5.7 & -0.884086 & -0.741667 & -0.142419 & -4.81591 \tabularnewline
48 & 3.9 & -0.837558 & -0.175 & -0.662558 & 4.73756 \tabularnewline
49 & -7.6 & -0.150058 & -0.075 & -0.0750579 & -7.44994 \tabularnewline
50 & -0.9 & 1.37772 & 0.3875 & 0.99022 & -2.27772 \tabularnewline
51 & 7.3 & 2.76175 & 1.63333 & 1.12841 & 4.53825 \tabularnewline
52 & -3.7 & 0.231192 & 1.94583 & -1.71464 & -3.93119 \tabularnewline
53 & -2.5 & 1.91244 & 2.27917 & -0.366725 & -4.41244 \tabularnewline
54 & 9.3 & 2.45897 & 2.4875 & -0.0285301 & 6.84103 \tabularnewline
55 & 1.3 & 4.17703 & 2.50833 & 1.66869 & -2.87703 \tabularnewline
56 & 9.5 & 3.893 & 3.00833 & 0.884664 & 5.607 \tabularnewline
57 & 11.3 & 2.55828 & 2.78333 & -0.225058 & 8.74172 \tabularnewline
58 & -1.7 & 1.368 & 2.825 & -1.457 & -3.068 \tabularnewline
59 & 8 & 3.24091 & 3.38333 & -0.142419 & 4.75909 \tabularnewline
60 & -4.8 & 2.28328 & 2.94583 & -0.662558 & -7.08328 \tabularnewline
61 & 1.6 & 2.28328 & 2.35833 & -0.0750579 & -0.683275 \tabularnewline
62 & 1.9 & 2.98605 & 1.99583 & 0.99022 & -1.08605 \tabularnewline
63 & -0.9 & 1.71175 & 0.583333 & 1.12841 & -2.61175 \tabularnewline
64 & 5.5 & -2.42714 & -0.7125 & -1.71464 & 7.92714 \tabularnewline
65 & 1.7 & -1.67506 & -1.30833 & -0.366725 & 3.37506 \tabularnewline
66 & -5.4 & -1.22436 & -1.19583 & -0.0285301 & -4.17564 \tabularnewline
67 & 1.9 & 0.793692 & -0.875 & 1.66869 & 1.10631 \tabularnewline
68 & 0.2 & -0.302836 & -1.1875 & 0.884664 & 0.502836 \tabularnewline
69 & -13.3 & -1.34172 & -1.11667 & -0.225058 & -11.9583 \tabularnewline
70 & -8.2 & -3.257 & -1.8 & -1.457 & -4.943 \tabularnewline
71 & 0.2 & -2.90492 & -2.7625 & -0.142419 & 3.10492 \tabularnewline
72 & 5.7 & -3.30422 & -2.64167 & -0.662558 & 9.00422 \tabularnewline
73 & -1.2 & -3.02089 & -2.94583 & -0.0750579 & 1.82089 \tabularnewline
74 & -2.8 & -2.60978 & -3.6 & 0.99022 & -0.19022 \tabularnewline
75 & 5.5 & -1.96325 & -3.09167 & 1.12841 & 7.46325 \tabularnewline
76 & -17.3 & -3.71047 & -1.99583 & -1.71464 & -13.5895 \tabularnewline
77 & 1.4 & -2.17506 & -1.80833 & -0.366725 & 3.57506 \tabularnewline
78 & -2.2 & -2.35353 & -2.325 & -0.0285301 & 0.15353 \tabularnewline
79 & -8.6 & NA & NA & 1.66869 & NA \tabularnewline
80 & -5 & NA & NA & 0.884664 & NA \tabularnewline
81 & 4.1 & NA & NA & -0.225058 & NA \tabularnewline
82 & 0.7 & NA & NA & -1.457 & NA \tabularnewline
83 & -4.2 & NA & NA & -0.142419 & NA \tabularnewline
84 & -2.3 & NA & NA & -0.662558 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234799&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]-0.0750579[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]6.7[/C][C]NA[/C][C]NA[/C][C]0.99022[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]-0.6[/C][C]NA[/C][C]NA[/C][C]1.12841[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]-1.71464[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]16.4[/C][C]NA[/C][C]NA[/C][C]-0.366725[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.5[/C][C]NA[/C][C]NA[/C][C]-0.0285301[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.1[/C][C]7.88953[/C][C]6.22083[/C][C]1.66869[/C][C]-2.78953[/C][/ROW]
[ROW][C]8[/C][C]14.7[/C][C]7.3555[/C][C]6.47083[/C][C]0.884664[/C][C]7.3445[/C][/ROW]
[ROW][C]9[/C][C]4.3[/C][C]7.13744[/C][C]7.3625[/C][C]-0.225058[/C][C]-2.83744[/C][/ROW]
[ROW][C]10[/C][C]1.5[/C][C]6.69716[/C][C]8.15417[/C][C]-1.457[/C][C]-5.19716[/C][/ROW]
[ROW][C]11[/C][C]9.1[/C][C]7.29508[/C][C]7.4375[/C][C]-0.142419[/C][C]1.80492[/C][/ROW]
[ROW][C]12[/C][C]4.3[/C][C]6.13744[/C][C]6.8[/C][C]-0.662558[/C][C]-1.83744[/C][/ROW]
[ROW][C]13[/C][C]5.7[/C][C]6.97078[/C][C]7.04583[/C][C]-0.0750579[/C][C]-1.27078[/C][/ROW]
[ROW][C]14[/C][C]13[/C][C]7.32355[/C][C]6.33333[/C][C]0.99022[/C][C]5.67645[/C][/ROW]
[ROW][C]15[/C][C]14.5[/C][C]7.04508[/C][C]5.91667[/C][C]1.12841[/C][C]7.45492[/C][/ROW]
[ROW][C]16[/C][C]9.7[/C][C]4.64369[/C][C]6.35833[/C][C]-1.71464[/C][C]5.05631[/C][/ROW]
[ROW][C]17[/C][C]-4.7[/C][C]5.65411[/C][C]6.02083[/C][C]-0.366725[/C][C]-10.3541[/C][/ROW]
[ROW][C]18[/C][C]7.3[/C][C]5.32147[/C][C]5.35[/C][C]-0.0285301[/C][C]1.97853[/C][/ROW]
[ROW][C]19[/C][C]5.2[/C][C]6.77286[/C][C]5.10417[/C][C]1.66869[/C][C]-1.57286[/C][/ROW]
[ROW][C]20[/C][C]-2.5[/C][C]5.72216[/C][C]4.8375[/C][C]0.884664[/C][C]-8.22216[/C][/ROW]
[ROW][C]21[/C][C]11.5[/C][C]3.39161[/C][C]3.61667[/C][C]-0.225058[/C][C]8.10839[/C][/ROW]
[ROW][C]22[/C][C]4.9[/C][C]0.576331[/C][C]2.03333[/C][C]-1.457[/C][C]4.32367[/C][/ROW]
[ROW][C]23[/C][C]-2.4[/C][C]2.19508[/C][C]2.3375[/C][C]-0.142419[/C][C]-4.59508[/C][/ROW]
[ROW][C]24[/C][C]-0.3[/C][C]2.04578[/C][C]2.70833[/C][C]-0.662558[/C][C]-2.34578[/C][/ROW]
[ROW][C]25[/C][C]4.4[/C][C]2.05411[/C][C]2.12917[/C][C]-0.0750579[/C][C]2.34589[/C][/ROW]
[ROW][C]26[/C][C]7.9[/C][C]3.31105[/C][C]2.32083[/C][C]0.99022[/C][C]4.58895[/C][/ROW]
[ROW][C]27[/C][C]-9.7[/C][C]3.22425[/C][C]2.09583[/C][C]1.12841[/C][C]-12.9242[/C][/ROW]
[ROW][C]28[/C][C]-4.1[/C][C]-0.181308[/C][C]1.53333[/C][C]-1.71464[/C][C]-3.91869[/C][/ROW]
[ROW][C]29[/C][C]16.4[/C][C]1.22078[/C][C]1.5875[/C][C]-0.366725[/C][C]15.1792[/C][/ROW]
[ROW][C]30[/C][C]-4.9[/C][C]1.58397[/C][C]1.6125[/C][C]-0.0285301[/C][C]-6.48397[/C][/ROW]
[ROW][C]31[/C][C]3.5[/C][C]3.23953[/C][C]1.57083[/C][C]1.66869[/C][C]0.260475[/C][/ROW]
[ROW][C]32[/C][C]3.8[/C][C]1.968[/C][C]1.08333[/C][C]0.884664[/C][C]1.832[/C][/ROW]
[ROW][C]33[/C][C]-0.2[/C][C]0.591609[/C][C]0.816667[/C][C]-0.225058[/C][C]-0.791609[/C][/ROW]
[ROW][C]34[/C][C]3.1[/C][C]0.088831[/C][C]1.54583[/C][C]-1.457[/C][C]3.01117[/C][/ROW]
[ROW][C]35[/C][C]0.7[/C][C]0.828414[/C][C]0.970833[/C][C]-0.142419[/C][C]-0.128414[/C][/ROW]
[ROW][C]36[/C][C]-2.8[/C][C]-0.454225[/C][C]0.208333[/C][C]-0.662558[/C][C]-2.34578[/C][/ROW]
[ROW][C]37[/C][C]5.9[/C][C]0.533275[/C][C]0.608333[/C][C]-0.0750579[/C][C]5.36672[/C][/ROW]
[ROW][C]38[/C][C]-5.3[/C][C]1.28189[/C][C]0.291667[/C][C]0.99022[/C][C]-6.58189[/C][/ROW]
[ROW][C]39[/C][C]-2.9[/C][C]0.890914[/C][C]-0.2375[/C][C]1.12841[/C][C]-3.79091[/C][/ROW]
[ROW][C]40[/C][C]6.6[/C][C]-1.98547[/C][C]-0.270833[/C][C]-1.71464[/C][C]8.58547[/C][/ROW]
[ROW][C]41[/C][C]-8.1[/C][C]-0.866725[/C][C]-0.5[/C][C]-0.366725[/C][C]-7.23328[/C][/ROW]
[ROW][C]42[/C][C]1.3[/C][C]-0.51603[/C][C]-0.4875[/C][C]-0.0285301[/C][C]1.81603[/C][/ROW]
[ROW][C]43[/C][C]6.9[/C][C]0.897859[/C][C]-0.770833[/C][C]1.66869[/C][C]6.00214[/C][/ROW]
[ROW][C]44[/C][C]-7.2[/C][C]-0.265336[/C][C]-1.15[/C][C]0.884664[/C][C]-6.93466[/C][/ROW]
[ROW][C]45[/C][C]-1.9[/C][C]-0.766725[/C][C]-0.541667[/C][C]-0.225058[/C][C]-1.13328[/C][/ROW]
[ROW][C]46[/C][C]4[/C][C]-2.00284[/C][C]-0.545833[/C][C]-1.457[/C][C]6.00284[/C][/ROW]
[ROW][C]47[/C][C]-5.7[/C][C]-0.884086[/C][C]-0.741667[/C][C]-0.142419[/C][C]-4.81591[/C][/ROW]
[ROW][C]48[/C][C]3.9[/C][C]-0.837558[/C][C]-0.175[/C][C]-0.662558[/C][C]4.73756[/C][/ROW]
[ROW][C]49[/C][C]-7.6[/C][C]-0.150058[/C][C]-0.075[/C][C]-0.0750579[/C][C]-7.44994[/C][/ROW]
[ROW][C]50[/C][C]-0.9[/C][C]1.37772[/C][C]0.3875[/C][C]0.99022[/C][C]-2.27772[/C][/ROW]
[ROW][C]51[/C][C]7.3[/C][C]2.76175[/C][C]1.63333[/C][C]1.12841[/C][C]4.53825[/C][/ROW]
[ROW][C]52[/C][C]-3.7[/C][C]0.231192[/C][C]1.94583[/C][C]-1.71464[/C][C]-3.93119[/C][/ROW]
[ROW][C]53[/C][C]-2.5[/C][C]1.91244[/C][C]2.27917[/C][C]-0.366725[/C][C]-4.41244[/C][/ROW]
[ROW][C]54[/C][C]9.3[/C][C]2.45897[/C][C]2.4875[/C][C]-0.0285301[/C][C]6.84103[/C][/ROW]
[ROW][C]55[/C][C]1.3[/C][C]4.17703[/C][C]2.50833[/C][C]1.66869[/C][C]-2.87703[/C][/ROW]
[ROW][C]56[/C][C]9.5[/C][C]3.893[/C][C]3.00833[/C][C]0.884664[/C][C]5.607[/C][/ROW]
[ROW][C]57[/C][C]11.3[/C][C]2.55828[/C][C]2.78333[/C][C]-0.225058[/C][C]8.74172[/C][/ROW]
[ROW][C]58[/C][C]-1.7[/C][C]1.368[/C][C]2.825[/C][C]-1.457[/C][C]-3.068[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]3.24091[/C][C]3.38333[/C][C]-0.142419[/C][C]4.75909[/C][/ROW]
[ROW][C]60[/C][C]-4.8[/C][C]2.28328[/C][C]2.94583[/C][C]-0.662558[/C][C]-7.08328[/C][/ROW]
[ROW][C]61[/C][C]1.6[/C][C]2.28328[/C][C]2.35833[/C][C]-0.0750579[/C][C]-0.683275[/C][/ROW]
[ROW][C]62[/C][C]1.9[/C][C]2.98605[/C][C]1.99583[/C][C]0.99022[/C][C]-1.08605[/C][/ROW]
[ROW][C]63[/C][C]-0.9[/C][C]1.71175[/C][C]0.583333[/C][C]1.12841[/C][C]-2.61175[/C][/ROW]
[ROW][C]64[/C][C]5.5[/C][C]-2.42714[/C][C]-0.7125[/C][C]-1.71464[/C][C]7.92714[/C][/ROW]
[ROW][C]65[/C][C]1.7[/C][C]-1.67506[/C][C]-1.30833[/C][C]-0.366725[/C][C]3.37506[/C][/ROW]
[ROW][C]66[/C][C]-5.4[/C][C]-1.22436[/C][C]-1.19583[/C][C]-0.0285301[/C][C]-4.17564[/C][/ROW]
[ROW][C]67[/C][C]1.9[/C][C]0.793692[/C][C]-0.875[/C][C]1.66869[/C][C]1.10631[/C][/ROW]
[ROW][C]68[/C][C]0.2[/C][C]-0.302836[/C][C]-1.1875[/C][C]0.884664[/C][C]0.502836[/C][/ROW]
[ROW][C]69[/C][C]-13.3[/C][C]-1.34172[/C][C]-1.11667[/C][C]-0.225058[/C][C]-11.9583[/C][/ROW]
[ROW][C]70[/C][C]-8.2[/C][C]-3.257[/C][C]-1.8[/C][C]-1.457[/C][C]-4.943[/C][/ROW]
[ROW][C]71[/C][C]0.2[/C][C]-2.90492[/C][C]-2.7625[/C][C]-0.142419[/C][C]3.10492[/C][/ROW]
[ROW][C]72[/C][C]5.7[/C][C]-3.30422[/C][C]-2.64167[/C][C]-0.662558[/C][C]9.00422[/C][/ROW]
[ROW][C]73[/C][C]-1.2[/C][C]-3.02089[/C][C]-2.94583[/C][C]-0.0750579[/C][C]1.82089[/C][/ROW]
[ROW][C]74[/C][C]-2.8[/C][C]-2.60978[/C][C]-3.6[/C][C]0.99022[/C][C]-0.19022[/C][/ROW]
[ROW][C]75[/C][C]5.5[/C][C]-1.96325[/C][C]-3.09167[/C][C]1.12841[/C][C]7.46325[/C][/ROW]
[ROW][C]76[/C][C]-17.3[/C][C]-3.71047[/C][C]-1.99583[/C][C]-1.71464[/C][C]-13.5895[/C][/ROW]
[ROW][C]77[/C][C]1.4[/C][C]-2.17506[/C][C]-1.80833[/C][C]-0.366725[/C][C]3.57506[/C][/ROW]
[ROW][C]78[/C][C]-2.2[/C][C]-2.35353[/C][C]-2.325[/C][C]-0.0285301[/C][C]0.15353[/C][/ROW]
[ROW][C]79[/C][C]-8.6[/C][C]NA[/C][C]NA[/C][C]1.66869[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]-5[/C][C]NA[/C][C]NA[/C][C]0.884664[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]4.1[/C][C]NA[/C][C]NA[/C][C]-0.225058[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]0.7[/C][C]NA[/C][C]NA[/C][C]-1.457[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]-4.2[/C][C]NA[/C][C]NA[/C][C]-0.142419[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]-2.3[/C][C]NA[/C][C]NA[/C][C]-0.662558[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234799&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234799&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	-0.0750579	NA
2	6.7	NA	NA	0.99022	NA
3	-0.6	NA	NA	1.12841	NA
4	5.8	NA	NA	-1.71464	NA
5	16.4	NA	NA	-0.366725	NA
6	1.5	NA	NA	-0.0285301	NA
7	5.1	7.88953	6.22083	1.66869	-2.78953
8	14.7	7.3555	6.47083	0.884664	7.3445
9	4.3	7.13744	7.3625	-0.225058	-2.83744
10	1.5	6.69716	8.15417	-1.457	-5.19716
11	9.1	7.29508	7.4375	-0.142419	1.80492
12	4.3	6.13744	6.8	-0.662558	-1.83744
13	5.7	6.97078	7.04583	-0.0750579	-1.27078
14	13	7.32355	6.33333	0.99022	5.67645
15	14.5	7.04508	5.91667	1.12841	7.45492
16	9.7	4.64369	6.35833	-1.71464	5.05631
17	-4.7	5.65411	6.02083	-0.366725	-10.3541
18	7.3	5.32147	5.35	-0.0285301	1.97853
19	5.2	6.77286	5.10417	1.66869	-1.57286
20	-2.5	5.72216	4.8375	0.884664	-8.22216
21	11.5	3.39161	3.61667	-0.225058	8.10839
22	4.9	0.576331	2.03333	-1.457	4.32367
23	-2.4	2.19508	2.3375	-0.142419	-4.59508
24	-0.3	2.04578	2.70833	-0.662558	-2.34578
25	4.4	2.05411	2.12917	-0.0750579	2.34589
26	7.9	3.31105	2.32083	0.99022	4.58895
27	-9.7	3.22425	2.09583	1.12841	-12.9242
28	-4.1	-0.181308	1.53333	-1.71464	-3.91869
29	16.4	1.22078	1.5875	-0.366725	15.1792
30	-4.9	1.58397	1.6125	-0.0285301	-6.48397
31	3.5	3.23953	1.57083	1.66869	0.260475
32	3.8	1.968	1.08333	0.884664	1.832
33	-0.2	0.591609	0.816667	-0.225058	-0.791609
34	3.1	0.088831	1.54583	-1.457	3.01117
35	0.7	0.828414	0.970833	-0.142419	-0.128414
36	-2.8	-0.454225	0.208333	-0.662558	-2.34578
37	5.9	0.533275	0.608333	-0.0750579	5.36672
38	-5.3	1.28189	0.291667	0.99022	-6.58189
39	-2.9	0.890914	-0.2375	1.12841	-3.79091
40	6.6	-1.98547	-0.270833	-1.71464	8.58547
41	-8.1	-0.866725	-0.5	-0.366725	-7.23328
42	1.3	-0.51603	-0.4875	-0.0285301	1.81603
43	6.9	0.897859	-0.770833	1.66869	6.00214
44	-7.2	-0.265336	-1.15	0.884664	-6.93466
45	-1.9	-0.766725	-0.541667	-0.225058	-1.13328
46	4	-2.00284	-0.545833	-1.457	6.00284
47	-5.7	-0.884086	-0.741667	-0.142419	-4.81591
48	3.9	-0.837558	-0.175	-0.662558	4.73756
49	-7.6	-0.150058	-0.075	-0.0750579	-7.44994
50	-0.9	1.37772	0.3875	0.99022	-2.27772
51	7.3	2.76175	1.63333	1.12841	4.53825
52	-3.7	0.231192	1.94583	-1.71464	-3.93119
53	-2.5	1.91244	2.27917	-0.366725	-4.41244
54	9.3	2.45897	2.4875	-0.0285301	6.84103
55	1.3	4.17703	2.50833	1.66869	-2.87703
56	9.5	3.893	3.00833	0.884664	5.607
57	11.3	2.55828	2.78333	-0.225058	8.74172
58	-1.7	1.368	2.825	-1.457	-3.068
59	8	3.24091	3.38333	-0.142419	4.75909
60	-4.8	2.28328	2.94583	-0.662558	-7.08328
61	1.6	2.28328	2.35833	-0.0750579	-0.683275
62	1.9	2.98605	1.99583	0.99022	-1.08605
63	-0.9	1.71175	0.583333	1.12841	-2.61175
64	5.5	-2.42714	-0.7125	-1.71464	7.92714
65	1.7	-1.67506	-1.30833	-0.366725	3.37506
66	-5.4	-1.22436	-1.19583	-0.0285301	-4.17564
67	1.9	0.793692	-0.875	1.66869	1.10631
68	0.2	-0.302836	-1.1875	0.884664	0.502836
69	-13.3	-1.34172	-1.11667	-0.225058	-11.9583
70	-8.2	-3.257	-1.8	-1.457	-4.943
71	0.2	-2.90492	-2.7625	-0.142419	3.10492
72	5.7	-3.30422	-2.64167	-0.662558	9.00422
73	-1.2	-3.02089	-2.94583	-0.0750579	1.82089
74	-2.8	-2.60978	-3.6	0.99022	-0.19022
75	5.5	-1.96325	-3.09167	1.12841	7.46325
76	-17.3	-3.71047	-1.99583	-1.71464	-13.5895
77	1.4	-2.17506	-1.80833	-0.366725	3.57506
78	-2.2	-2.35353	-2.325	-0.0285301	0.15353
79	-8.6	NA	NA	1.66869	NA
80	-5	NA	NA	0.884664	NA
81	4.1	NA	NA	-0.225058	NA
82	0.7	NA	NA	-1.457	NA
83	-4.2	NA	NA	-0.142419	NA
84	-2.3	NA	NA	-0.662558	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