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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 06 Dec 2011 18:28:03 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/06/t1323214143gdwx0yos3exipmn.htm/, Retrieved Mon, 29 Apr 2024 01:51:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=152040, Retrieved Mon, 29 Apr 2024 01:51:59 +0000

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No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

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

-       [Classical Decomposition] [] [2011-12-06 23:28:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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5,51
5,54
5,56
5,57
5,57
5,58
5,56
5,57
5,57
5,6
5,61
5,63
5,65
5,71
5,78
5,8
5,8
5,8
5,81
5,84
5,83
5,86
5,88
5,88
5,89
5,91
5,91
5,95
5,92
5,92
5,91
5,95
6,01
6,07
6,08
6,1
6,11
6,13
6,21
6,19
6,17
6,17
6,19
6,21
6,32
6,36
6,36
6,38
6,36
6,42
6,42
6,44
6,41
6,42
6,43
6,44
6,43
6,43
6,45
6,45

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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152040&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152040&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152040&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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	5.51	NA	NA	0.998683763250932	NA
2	5.54	NA	NA	1.00232607785844	NA
3	5.56	NA	NA	1.00563457666444	NA
4	5.57	NA	NA	1.00521024531888	NA
5	5.57	NA	NA	0.999063418495026	NA
6	5.58	NA	NA	0.996588699507151	NA
7	5.56	5.54566043466324	5.57833333333333	0.994142892380623	1.0025857272557
8	5.57	5.56516735446081	5.59125	0.995335095812352	1.00086837380287
9	5.57	5.60048832015423	5.6075	0.998749588970884	0.994556131820771
10	5.6	5.63983420181237	5.62625	1.00241443267049	0.99293699063005
11	5.61	5.65183745853917	5.64541666666667	1.00113734596605	0.992597547462028
12	5.63	5.66821010626905	5.66416666666666	1.00071386310473	0.993258876161491
13	5.65	5.67626883937748	5.68375	0.998683763250932	0.995372164335267
14	5.71	5.71868791004815	5.70541666666667	1.00232607785844	0.998480786120032
15	5.78	5.7597720378456	5.7275	1.00563457666444	1.00351193797628
16	5.8	5.77912123537911	5.74916666666667	1.00521024531888	1.00361279228632
17	5.8	5.76584475398942	5.77125	0.999063418495026	1.00592371932785
18	5.8	5.77315528718663	5.79291666666667	0.996588699507151	1.00464992044696
19	5.81	5.77928401437269	5.81333333333333	0.994142892380623	1.00531484272981
20	5.84	5.80446250041237	5.83166666666667	0.995335095812352	1.00612244451318
21	5.83	5.83810749319689	5.84541666666667	0.998749588970884	0.998611280589415
22	5.86	5.87122486668714	5.85708333333333	1.00241443267049	0.99808815588876
23	5.88	5.87500765857744	5.86833333333333	1.00113734596605	1.0008497591344
24	5.88	5.88252965861731	5.87833333333333	1.00071386310473	0.999569970953975
25	5.89	5.87975065613986	5.8875	0.998683763250932	1.00174315960991
26	5.91	5.9099651365728	5.89625	1.00232607785844	1.00000589909185
27	5.91	5.94162429045909	5.90833333333333	1.00563457666444	0.994677500812384
28	5.95	5.95545186591213	5.92458333333333	1.00521024531888	0.999084558815203
29	5.92	5.93610181155794	5.94166666666667	0.999063418495026	0.997287477191413
30	5.92	5.9388381584797	5.95916666666667	0.996588699507151	0.996827972411944
31	5.91	5.94248913920517	5.9775	0.994142892380623	0.994532738984607
32	5.95	5.96786334530823	5.99583333333333	0.995335095812352	0.997006743573934
33	6.01	6.0099756516323	6.0175	0.998749588970884	1.00000405132552
34	6.07	6.05458317332979	6.04	1.00241443267049	1.00254630686025
35	6.08	6.06730945711508	6.06041666666667	1.00113734596605	1.00209162611115
36	6.1	6.08559118000565	6.08125	1.00071386310473	1.00236769437318
37	6.11	6.09529990170819	6.10333333333333	0.998683763250932	1.00241171042096
38	6.13	6.14008249861447	6.12583333333333	1.00232607785844	0.998357921311848
39	6.21	6.18423363207938	6.14958333333333	1.00563457666444	1.00416646094788
40	6.19	6.20675442724185	6.17458333333333	1.00521024531888	0.99730061380094
41	6.17	6.19252808897167	6.19833333333333	0.999063418495026	0.996362053001942
42	6.17	6.20044269210032	6.22166666666667	0.996588699507151	0.995090238937437
43	6.19	6.20717968430152	6.24375	0.994142892380623	0.997232288225043
44	6.21	6.23701854413415	6.26625	0.995335095812352	0.995668035305176
45	6.32	6.27922189499236	6.28708333333333	0.998749588970884	1.00649413345946
46	6.36	6.3214760160283	6.30625	1.00241443267049	1.0060941438161
47	6.36	6.33386227547854	6.32666666666667	1.00113734596605	1.00412666448758
48	6.38	6.35161428194765	6.34708333333333	1.00071386310473	1.00446905570652
49	6.36	6.35911886250031	6.3675	0.998683763250932	1.00013856282902
50	6.42	6.40194018645498	6.38708333333333	1.00232607785844	1.00282099067143
51	6.42	6.43731833387327	6.40125	1.00563457666444	0.997309697458623
52	6.44	6.44214115968736	6.40875	1.00521024531888	0.999667632292699
53	6.41	6.40940810606996	6.41541666666667	0.999063418495026	1.00009234767396
54	6.42	6.40017567729322	6.42208333333333	0.996588699507151	1.00309746539882
55	6.43	NA	NA	0.994142892380623	NA
56	6.44	NA	NA	0.995335095812352	NA
57	6.43	NA	NA	0.998749588970884	NA
58	6.43	NA	NA	1.00241443267049	NA
59	6.45	NA	NA	1.00113734596605	NA
60	6.45	NA	NA	1.00071386310473	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 5.51 & NA & NA & 0.998683763250932 & NA \tabularnewline
2 & 5.54 & NA & NA & 1.00232607785844 & NA \tabularnewline
3 & 5.56 & NA & NA & 1.00563457666444 & NA \tabularnewline
4 & 5.57 & NA & NA & 1.00521024531888 & NA \tabularnewline
5 & 5.57 & NA & NA & 0.999063418495026 & NA \tabularnewline
6 & 5.58 & NA & NA & 0.996588699507151 & NA \tabularnewline
7 & 5.56 & 5.54566043466324 & 5.57833333333333 & 0.994142892380623 & 1.0025857272557 \tabularnewline
8 & 5.57 & 5.56516735446081 & 5.59125 & 0.995335095812352 & 1.00086837380287 \tabularnewline
9 & 5.57 & 5.60048832015423 & 5.6075 & 0.998749588970884 & 0.994556131820771 \tabularnewline
10 & 5.6 & 5.63983420181237 & 5.62625 & 1.00241443267049 & 0.99293699063005 \tabularnewline
11 & 5.61 & 5.65183745853917 & 5.64541666666667 & 1.00113734596605 & 0.992597547462028 \tabularnewline
12 & 5.63 & 5.66821010626905 & 5.66416666666666 & 1.00071386310473 & 0.993258876161491 \tabularnewline
13 & 5.65 & 5.67626883937748 & 5.68375 & 0.998683763250932 & 0.995372164335267 \tabularnewline
14 & 5.71 & 5.71868791004815 & 5.70541666666667 & 1.00232607785844 & 0.998480786120032 \tabularnewline
15 & 5.78 & 5.7597720378456 & 5.7275 & 1.00563457666444 & 1.00351193797628 \tabularnewline
16 & 5.8 & 5.77912123537911 & 5.74916666666667 & 1.00521024531888 & 1.00361279228632 \tabularnewline
17 & 5.8 & 5.76584475398942 & 5.77125 & 0.999063418495026 & 1.00592371932785 \tabularnewline
18 & 5.8 & 5.77315528718663 & 5.79291666666667 & 0.996588699507151 & 1.00464992044696 \tabularnewline
19 & 5.81 & 5.77928401437269 & 5.81333333333333 & 0.994142892380623 & 1.00531484272981 \tabularnewline
20 & 5.84 & 5.80446250041237 & 5.83166666666667 & 0.995335095812352 & 1.00612244451318 \tabularnewline
21 & 5.83 & 5.83810749319689 & 5.84541666666667 & 0.998749588970884 & 0.998611280589415 \tabularnewline
22 & 5.86 & 5.87122486668714 & 5.85708333333333 & 1.00241443267049 & 0.99808815588876 \tabularnewline
23 & 5.88 & 5.87500765857744 & 5.86833333333333 & 1.00113734596605 & 1.0008497591344 \tabularnewline
24 & 5.88 & 5.88252965861731 & 5.87833333333333 & 1.00071386310473 & 0.999569970953975 \tabularnewline
25 & 5.89 & 5.87975065613986 & 5.8875 & 0.998683763250932 & 1.00174315960991 \tabularnewline
26 & 5.91 & 5.9099651365728 & 5.89625 & 1.00232607785844 & 1.00000589909185 \tabularnewline
27 & 5.91 & 5.94162429045909 & 5.90833333333333 & 1.00563457666444 & 0.994677500812384 \tabularnewline
28 & 5.95 & 5.95545186591213 & 5.92458333333333 & 1.00521024531888 & 0.999084558815203 \tabularnewline
29 & 5.92 & 5.93610181155794 & 5.94166666666667 & 0.999063418495026 & 0.997287477191413 \tabularnewline
30 & 5.92 & 5.9388381584797 & 5.95916666666667 & 0.996588699507151 & 0.996827972411944 \tabularnewline
31 & 5.91 & 5.94248913920517 & 5.9775 & 0.994142892380623 & 0.994532738984607 \tabularnewline
32 & 5.95 & 5.96786334530823 & 5.99583333333333 & 0.995335095812352 & 0.997006743573934 \tabularnewline
33 & 6.01 & 6.0099756516323 & 6.0175 & 0.998749588970884 & 1.00000405132552 \tabularnewline
34 & 6.07 & 6.05458317332979 & 6.04 & 1.00241443267049 & 1.00254630686025 \tabularnewline
35 & 6.08 & 6.06730945711508 & 6.06041666666667 & 1.00113734596605 & 1.00209162611115 \tabularnewline
36 & 6.1 & 6.08559118000565 & 6.08125 & 1.00071386310473 & 1.00236769437318 \tabularnewline
37 & 6.11 & 6.09529990170819 & 6.10333333333333 & 0.998683763250932 & 1.00241171042096 \tabularnewline
38 & 6.13 & 6.14008249861447 & 6.12583333333333 & 1.00232607785844 & 0.998357921311848 \tabularnewline
39 & 6.21 & 6.18423363207938 & 6.14958333333333 & 1.00563457666444 & 1.00416646094788 \tabularnewline
40 & 6.19 & 6.20675442724185 & 6.17458333333333 & 1.00521024531888 & 0.99730061380094 \tabularnewline
41 & 6.17 & 6.19252808897167 & 6.19833333333333 & 0.999063418495026 & 0.996362053001942 \tabularnewline
42 & 6.17 & 6.20044269210032 & 6.22166666666667 & 0.996588699507151 & 0.995090238937437 \tabularnewline
43 & 6.19 & 6.20717968430152 & 6.24375 & 0.994142892380623 & 0.997232288225043 \tabularnewline
44 & 6.21 & 6.23701854413415 & 6.26625 & 0.995335095812352 & 0.995668035305176 \tabularnewline
45 & 6.32 & 6.27922189499236 & 6.28708333333333 & 0.998749588970884 & 1.00649413345946 \tabularnewline
46 & 6.36 & 6.3214760160283 & 6.30625 & 1.00241443267049 & 1.0060941438161 \tabularnewline
47 & 6.36 & 6.33386227547854 & 6.32666666666667 & 1.00113734596605 & 1.00412666448758 \tabularnewline
48 & 6.38 & 6.35161428194765 & 6.34708333333333 & 1.00071386310473 & 1.00446905570652 \tabularnewline
49 & 6.36 & 6.35911886250031 & 6.3675 & 0.998683763250932 & 1.00013856282902 \tabularnewline
50 & 6.42 & 6.40194018645498 & 6.38708333333333 & 1.00232607785844 & 1.00282099067143 \tabularnewline
51 & 6.42 & 6.43731833387327 & 6.40125 & 1.00563457666444 & 0.997309697458623 \tabularnewline
52 & 6.44 & 6.44214115968736 & 6.40875 & 1.00521024531888 & 0.999667632292699 \tabularnewline
53 & 6.41 & 6.40940810606996 & 6.41541666666667 & 0.999063418495026 & 1.00009234767396 \tabularnewline
54 & 6.42 & 6.40017567729322 & 6.42208333333333 & 0.996588699507151 & 1.00309746539882 \tabularnewline
55 & 6.43 & NA & NA & 0.994142892380623 & NA \tabularnewline
56 & 6.44 & NA & NA & 0.995335095812352 & NA \tabularnewline
57 & 6.43 & NA & NA & 0.998749588970884 & NA \tabularnewline
58 & 6.43 & NA & NA & 1.00241443267049 & NA \tabularnewline
59 & 6.45 & NA & NA & 1.00113734596605 & NA \tabularnewline
60 & 6.45 & NA & NA & 1.00071386310473 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=152040&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]5.51[/C][C]NA[/C][C]NA[/C][C]0.998683763250932[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5.54[/C][C]NA[/C][C]NA[/C][C]1.00232607785844[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.56[/C][C]NA[/C][C]NA[/C][C]1.00563457666444[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.57[/C][C]NA[/C][C]NA[/C][C]1.00521024531888[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.57[/C][C]NA[/C][C]NA[/C][C]0.999063418495026[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.58[/C][C]NA[/C][C]NA[/C][C]0.996588699507151[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.56[/C][C]5.54566043466324[/C][C]5.57833333333333[/C][C]0.994142892380623[/C][C]1.0025857272557[/C][/ROW]
[ROW][C]8[/C][C]5.57[/C][C]5.56516735446081[/C][C]5.59125[/C][C]0.995335095812352[/C][C]1.00086837380287[/C][/ROW]
[ROW][C]9[/C][C]5.57[/C][C]5.60048832015423[/C][C]5.6075[/C][C]0.998749588970884[/C][C]0.994556131820771[/C][/ROW]
[ROW][C]10[/C][C]5.6[/C][C]5.63983420181237[/C][C]5.62625[/C][C]1.00241443267049[/C][C]0.99293699063005[/C][/ROW]
[ROW][C]11[/C][C]5.61[/C][C]5.65183745853917[/C][C]5.64541666666667[/C][C]1.00113734596605[/C][C]0.992597547462028[/C][/ROW]
[ROW][C]12[/C][C]5.63[/C][C]5.66821010626905[/C][C]5.66416666666666[/C][C]1.00071386310473[/C][C]0.993258876161491[/C][/ROW]
[ROW][C]13[/C][C]5.65[/C][C]5.67626883937748[/C][C]5.68375[/C][C]0.998683763250932[/C][C]0.995372164335267[/C][/ROW]
[ROW][C]14[/C][C]5.71[/C][C]5.71868791004815[/C][C]5.70541666666667[/C][C]1.00232607785844[/C][C]0.998480786120032[/C][/ROW]
[ROW][C]15[/C][C]5.78[/C][C]5.7597720378456[/C][C]5.7275[/C][C]1.00563457666444[/C][C]1.00351193797628[/C][/ROW]
[ROW][C]16[/C][C]5.8[/C][C]5.77912123537911[/C][C]5.74916666666667[/C][C]1.00521024531888[/C][C]1.00361279228632[/C][/ROW]
[ROW][C]17[/C][C]5.8[/C][C]5.76584475398942[/C][C]5.77125[/C][C]0.999063418495026[/C][C]1.00592371932785[/C][/ROW]
[ROW][C]18[/C][C]5.8[/C][C]5.77315528718663[/C][C]5.79291666666667[/C][C]0.996588699507151[/C][C]1.00464992044696[/C][/ROW]
[ROW][C]19[/C][C]5.81[/C][C]5.77928401437269[/C][C]5.81333333333333[/C][C]0.994142892380623[/C][C]1.00531484272981[/C][/ROW]
[ROW][C]20[/C][C]5.84[/C][C]5.80446250041237[/C][C]5.83166666666667[/C][C]0.995335095812352[/C][C]1.00612244451318[/C][/ROW]
[ROW][C]21[/C][C]5.83[/C][C]5.83810749319689[/C][C]5.84541666666667[/C][C]0.998749588970884[/C][C]0.998611280589415[/C][/ROW]
[ROW][C]22[/C][C]5.86[/C][C]5.87122486668714[/C][C]5.85708333333333[/C][C]1.00241443267049[/C][C]0.99808815588876[/C][/ROW]
[ROW][C]23[/C][C]5.88[/C][C]5.87500765857744[/C][C]5.86833333333333[/C][C]1.00113734596605[/C][C]1.0008497591344[/C][/ROW]
[ROW][C]24[/C][C]5.88[/C][C]5.88252965861731[/C][C]5.87833333333333[/C][C]1.00071386310473[/C][C]0.999569970953975[/C][/ROW]
[ROW][C]25[/C][C]5.89[/C][C]5.87975065613986[/C][C]5.8875[/C][C]0.998683763250932[/C][C]1.00174315960991[/C][/ROW]
[ROW][C]26[/C][C]5.91[/C][C]5.9099651365728[/C][C]5.89625[/C][C]1.00232607785844[/C][C]1.00000589909185[/C][/ROW]
[ROW][C]27[/C][C]5.91[/C][C]5.94162429045909[/C][C]5.90833333333333[/C][C]1.00563457666444[/C][C]0.994677500812384[/C][/ROW]
[ROW][C]28[/C][C]5.95[/C][C]5.95545186591213[/C][C]5.92458333333333[/C][C]1.00521024531888[/C][C]0.999084558815203[/C][/ROW]
[ROW][C]29[/C][C]5.92[/C][C]5.93610181155794[/C][C]5.94166666666667[/C][C]0.999063418495026[/C][C]0.997287477191413[/C][/ROW]
[ROW][C]30[/C][C]5.92[/C][C]5.9388381584797[/C][C]5.95916666666667[/C][C]0.996588699507151[/C][C]0.996827972411944[/C][/ROW]
[ROW][C]31[/C][C]5.91[/C][C]5.94248913920517[/C][C]5.9775[/C][C]0.994142892380623[/C][C]0.994532738984607[/C][/ROW]
[ROW][C]32[/C][C]5.95[/C][C]5.96786334530823[/C][C]5.99583333333333[/C][C]0.995335095812352[/C][C]0.997006743573934[/C][/ROW]
[ROW][C]33[/C][C]6.01[/C][C]6.0099756516323[/C][C]6.0175[/C][C]0.998749588970884[/C][C]1.00000405132552[/C][/ROW]
[ROW][C]34[/C][C]6.07[/C][C]6.05458317332979[/C][C]6.04[/C][C]1.00241443267049[/C][C]1.00254630686025[/C][/ROW]
[ROW][C]35[/C][C]6.08[/C][C]6.06730945711508[/C][C]6.06041666666667[/C][C]1.00113734596605[/C][C]1.00209162611115[/C][/ROW]
[ROW][C]36[/C][C]6.1[/C][C]6.08559118000565[/C][C]6.08125[/C][C]1.00071386310473[/C][C]1.00236769437318[/C][/ROW]
[ROW][C]37[/C][C]6.11[/C][C]6.09529990170819[/C][C]6.10333333333333[/C][C]0.998683763250932[/C][C]1.00241171042096[/C][/ROW]
[ROW][C]38[/C][C]6.13[/C][C]6.14008249861447[/C][C]6.12583333333333[/C][C]1.00232607785844[/C][C]0.998357921311848[/C][/ROW]
[ROW][C]39[/C][C]6.21[/C][C]6.18423363207938[/C][C]6.14958333333333[/C][C]1.00563457666444[/C][C]1.00416646094788[/C][/ROW]
[ROW][C]40[/C][C]6.19[/C][C]6.20675442724185[/C][C]6.17458333333333[/C][C]1.00521024531888[/C][C]0.99730061380094[/C][/ROW]
[ROW][C]41[/C][C]6.17[/C][C]6.19252808897167[/C][C]6.19833333333333[/C][C]0.999063418495026[/C][C]0.996362053001942[/C][/ROW]
[ROW][C]42[/C][C]6.17[/C][C]6.20044269210032[/C][C]6.22166666666667[/C][C]0.996588699507151[/C][C]0.995090238937437[/C][/ROW]
[ROW][C]43[/C][C]6.19[/C][C]6.20717968430152[/C][C]6.24375[/C][C]0.994142892380623[/C][C]0.997232288225043[/C][/ROW]
[ROW][C]44[/C][C]6.21[/C][C]6.23701854413415[/C][C]6.26625[/C][C]0.995335095812352[/C][C]0.995668035305176[/C][/ROW]
[ROW][C]45[/C][C]6.32[/C][C]6.27922189499236[/C][C]6.28708333333333[/C][C]0.998749588970884[/C][C]1.00649413345946[/C][/ROW]
[ROW][C]46[/C][C]6.36[/C][C]6.3214760160283[/C][C]6.30625[/C][C]1.00241443267049[/C][C]1.0060941438161[/C][/ROW]
[ROW][C]47[/C][C]6.36[/C][C]6.33386227547854[/C][C]6.32666666666667[/C][C]1.00113734596605[/C][C]1.00412666448758[/C][/ROW]
[ROW][C]48[/C][C]6.38[/C][C]6.35161428194765[/C][C]6.34708333333333[/C][C]1.00071386310473[/C][C]1.00446905570652[/C][/ROW]
[ROW][C]49[/C][C]6.36[/C][C]6.35911886250031[/C][C]6.3675[/C][C]0.998683763250932[/C][C]1.00013856282902[/C][/ROW]
[ROW][C]50[/C][C]6.42[/C][C]6.40194018645498[/C][C]6.38708333333333[/C][C]1.00232607785844[/C][C]1.00282099067143[/C][/ROW]
[ROW][C]51[/C][C]6.42[/C][C]6.43731833387327[/C][C]6.40125[/C][C]1.00563457666444[/C][C]0.997309697458623[/C][/ROW]
[ROW][C]52[/C][C]6.44[/C][C]6.44214115968736[/C][C]6.40875[/C][C]1.00521024531888[/C][C]0.999667632292699[/C][/ROW]
[ROW][C]53[/C][C]6.41[/C][C]6.40940810606996[/C][C]6.41541666666667[/C][C]0.999063418495026[/C][C]1.00009234767396[/C][/ROW]
[ROW][C]54[/C][C]6.42[/C][C]6.40017567729322[/C][C]6.42208333333333[/C][C]0.996588699507151[/C][C]1.00309746539882[/C][/ROW]
[ROW][C]55[/C][C]6.43[/C][C]NA[/C][C]NA[/C][C]0.994142892380623[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]6.44[/C][C]NA[/C][C]NA[/C][C]0.995335095812352[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]6.43[/C][C]NA[/C][C]NA[/C][C]0.998749588970884[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]6.43[/C][C]NA[/C][C]NA[/C][C]1.00241443267049[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]6.45[/C][C]NA[/C][C]NA[/C][C]1.00113734596605[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]6.45[/C][C]NA[/C][C]NA[/C][C]1.00071386310473[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=152040&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=152040&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	5.51	NA	NA	0.998683763250932	NA
2	5.54	NA	NA	1.00232607785844	NA
3	5.56	NA	NA	1.00563457666444	NA
4	5.57	NA	NA	1.00521024531888	NA
5	5.57	NA	NA	0.999063418495026	NA
6	5.58	NA	NA	0.996588699507151	NA
7	5.56	5.54566043466324	5.57833333333333	0.994142892380623	1.0025857272557
8	5.57	5.56516735446081	5.59125	0.995335095812352	1.00086837380287
9	5.57	5.60048832015423	5.6075	0.998749588970884	0.994556131820771
10	5.6	5.63983420181237	5.62625	1.00241443267049	0.99293699063005
11	5.61	5.65183745853917	5.64541666666667	1.00113734596605	0.992597547462028
12	5.63	5.66821010626905	5.66416666666666	1.00071386310473	0.993258876161491
13	5.65	5.67626883937748	5.68375	0.998683763250932	0.995372164335267
14	5.71	5.71868791004815	5.70541666666667	1.00232607785844	0.998480786120032
15	5.78	5.7597720378456	5.7275	1.00563457666444	1.00351193797628
16	5.8	5.77912123537911	5.74916666666667	1.00521024531888	1.00361279228632
17	5.8	5.76584475398942	5.77125	0.999063418495026	1.00592371932785
18	5.8	5.77315528718663	5.79291666666667	0.996588699507151	1.00464992044696
19	5.81	5.77928401437269	5.81333333333333	0.994142892380623	1.00531484272981
20	5.84	5.80446250041237	5.83166666666667	0.995335095812352	1.00612244451318
21	5.83	5.83810749319689	5.84541666666667	0.998749588970884	0.998611280589415
22	5.86	5.87122486668714	5.85708333333333	1.00241443267049	0.99808815588876
23	5.88	5.87500765857744	5.86833333333333	1.00113734596605	1.0008497591344
24	5.88	5.88252965861731	5.87833333333333	1.00071386310473	0.999569970953975
25	5.89	5.87975065613986	5.8875	0.998683763250932	1.00174315960991
26	5.91	5.9099651365728	5.89625	1.00232607785844	1.00000589909185
27	5.91	5.94162429045909	5.90833333333333	1.00563457666444	0.994677500812384
28	5.95	5.95545186591213	5.92458333333333	1.00521024531888	0.999084558815203
29	5.92	5.93610181155794	5.94166666666667	0.999063418495026	0.997287477191413
30	5.92	5.9388381584797	5.95916666666667	0.996588699507151	0.996827972411944
31	5.91	5.94248913920517	5.9775	0.994142892380623	0.994532738984607
32	5.95	5.96786334530823	5.99583333333333	0.995335095812352	0.997006743573934
33	6.01	6.0099756516323	6.0175	0.998749588970884	1.00000405132552
34	6.07	6.05458317332979	6.04	1.00241443267049	1.00254630686025
35	6.08	6.06730945711508	6.06041666666667	1.00113734596605	1.00209162611115
36	6.1	6.08559118000565	6.08125	1.00071386310473	1.00236769437318
37	6.11	6.09529990170819	6.10333333333333	0.998683763250932	1.00241171042096
38	6.13	6.14008249861447	6.12583333333333	1.00232607785844	0.998357921311848
39	6.21	6.18423363207938	6.14958333333333	1.00563457666444	1.00416646094788
40	6.19	6.20675442724185	6.17458333333333	1.00521024531888	0.99730061380094
41	6.17	6.19252808897167	6.19833333333333	0.999063418495026	0.996362053001942
42	6.17	6.20044269210032	6.22166666666667	0.996588699507151	0.995090238937437
43	6.19	6.20717968430152	6.24375	0.994142892380623	0.997232288225043
44	6.21	6.23701854413415	6.26625	0.995335095812352	0.995668035305176
45	6.32	6.27922189499236	6.28708333333333	0.998749588970884	1.00649413345946
46	6.36	6.3214760160283	6.30625	1.00241443267049	1.0060941438161
47	6.36	6.33386227547854	6.32666666666667	1.00113734596605	1.00412666448758
48	6.38	6.35161428194765	6.34708333333333	1.00071386310473	1.00446905570652
49	6.36	6.35911886250031	6.3675	0.998683763250932	1.00013856282902
50	6.42	6.40194018645498	6.38708333333333	1.00232607785844	1.00282099067143
51	6.42	6.43731833387327	6.40125	1.00563457666444	0.997309697458623
52	6.44	6.44214115968736	6.40875	1.00521024531888	0.999667632292699
53	6.41	6.40940810606996	6.41541666666667	0.999063418495026	1.00009234767396
54	6.42	6.40017567729322	6.42208333333333	0.996588699507151	1.00309746539882
55	6.43	NA	NA	0.994142892380623	NA
56	6.44	NA	NA	0.995335095812352	NA
57	6.43	NA	NA	0.998749588970884	NA
58	6.43	NA	NA	1.00241443267049	NA
59	6.45	NA	NA	1.00113734596605	NA
60	6.45	NA	NA	1.00071386310473	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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