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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 26 Apr 2016 22:45:52 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/26/t14617071790fb5s8cl0ogorix.htm/, Retrieved Fri, 03 May 2024 20:36:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294989, Retrieved Fri, 03 May 2024 20:36:29 +0000

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

-       [Classical Decomposition] [Opgave 9 eigen reeks] [2016-04-26 21:45:52] [0996086de175370e0a22efa864593ca4] [Current]
- RMPD    [Exponential Smoothing] [Opgave 10 eigen r...] [2016-05-29 00:13:19] [29ab9c45344d5c037bf74b62f65f8e78] 

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Dataseries X:

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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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294989&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294989&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294989&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	91.27	NA	NA	-0.18013	NA
2	91.51	NA	NA	0.0439323	NA
3	91.78	NA	NA	0.15112	NA
4	91.83	NA	NA	0.0985156	NA
5	92.01	NA	NA	0.016849	NA
6	92.1	NA	NA	-0.0374219	NA
7	92.35	92.4551	92.5037	-0.0486719	-0.105078
8	92.46	92.669	92.7179	-0.0488802	-0.209036
9	93.08	92.9804	92.9396	0.0408073	0.0996094
10	93.38	93.2529	93.1625	0.0903906	0.127109
11	93.46	93.3741	93.3854	-0.011276	0.0858594
12	93.58	93.4931	93.6083	-0.115234	0.086901
13	93.74	93.6528	93.8329	-0.18013	0.0872135
14	94.18	94.1068	94.0629	0.0439323	0.073151
15	94.43	94.4295	94.2783	0.15112	0.000546875
16	94.53	94.5685	94.47	0.0985156	-0.0385156
17	94.66	94.6793	94.6625	0.016849	-0.019349
18	94.8	94.8247	94.8621	-0.0374219	-0.0246615
19	95.04	95.0155	95.0642	-0.0486719	0.0245052
20	95.29	95.2086	95.2575	-0.0488802	0.0813802
21	95.42	95.4925	95.4517	0.0408073	-0.072474
22	95.64	95.7466	95.6562	0.0903906	-0.106641
23	95.82	95.8562	95.8675	-0.011276	-0.036224
24	96.01	95.9698	96.085	-0.115234	0.0402344
25	96.16	96.1224	96.3025	-0.18013	0.0376302
26	96.4	96.5648	96.5208	0.0439323	-0.164766
27	96.87	96.8936	96.7425	0.15112	-0.0236198
28	97	97.0631	96.9646	0.0985156	-0.063099
29	97.26	97.2002	97.1833	0.016849	0.0598177
30	97.42	97.3576	97.395	-0.0374219	0.0624219
31	97.64	97.5542	97.6029	-0.0486719	0.0857552
32	97.93	97.7711	97.82	-0.0488802	0.15888
33	98.1	98.0775	98.0367	0.0408073	0.022526
34	98.29	98.3371	98.2467	0.0903906	-0.0470573
35	98.42	98.4379	98.4492	-0.011276	-0.0178906
36	98.49	98.5285	98.6438	-0.115234	-0.0385156
37	98.67	98.6624	98.8425	-0.18013	0.00763021
38	99.1	99.0843	99.0404	0.0439323	0.015651
39	99.37	99.3915	99.2404	0.15112	-0.0215365
40	99.54	99.5523	99.4537	0.0985156	-0.0122656
41	99.58	99.6898	99.6729	0.016849	-0.109766
42	99.77	99.8538	99.8912	-0.0374219	-0.0838281
43	100.06	100.06	100.109	-0.0486719	-7.8125e-05
44	100.26	100.286	100.335	-0.0488802	-0.0261198
45	100.57	100.615	100.574	0.0408073	-0.0445573
46	100.94	100.908	100.818	0.0903906	0.0316927
47	101.03	101.057	101.068	-0.011276	-0.0266406
48	101.12	101.204	101.319	-0.115234	-0.0835156
49	101.26	101.387	101.568	-0.18013	-0.12737
50	101.94	101.859	101.815	0.0439323	0.0810677
51	102.26	102.21	102.059	0.15112	0.0497135
52	102.51	102.391	102.292	0.0985156	0.118984
53	102.61	102.536	102.519	0.016849	0.074401
54	102.76	102.709	102.746	-0.0374219	0.0511719
55	103.04	NA	NA	-0.0486719	NA
56	103.22	NA	NA	-0.0488802	NA
57	103.47	NA	NA	0.0408073	NA
58	103.64	NA	NA	0.0903906	NA
59	103.76	NA	NA	-0.011276	NA
60	103.85	NA	NA	-0.115234	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 91.27 & NA & NA & -0.18013 & NA \tabularnewline
2 & 91.51 & NA & NA & 0.0439323 & NA \tabularnewline
3 & 91.78 & NA & NA & 0.15112 & NA \tabularnewline
4 & 91.83 & NA & NA & 0.0985156 & NA \tabularnewline
5 & 92.01 & NA & NA & 0.016849 & NA \tabularnewline
6 & 92.1 & NA & NA & -0.0374219 & NA \tabularnewline
7 & 92.35 & 92.4551 & 92.5037 & -0.0486719 & -0.105078 \tabularnewline
8 & 92.46 & 92.669 & 92.7179 & -0.0488802 & -0.209036 \tabularnewline
9 & 93.08 & 92.9804 & 92.9396 & 0.0408073 & 0.0996094 \tabularnewline
10 & 93.38 & 93.2529 & 93.1625 & 0.0903906 & 0.127109 \tabularnewline
11 & 93.46 & 93.3741 & 93.3854 & -0.011276 & 0.0858594 \tabularnewline
12 & 93.58 & 93.4931 & 93.6083 & -0.115234 & 0.086901 \tabularnewline
13 & 93.74 & 93.6528 & 93.8329 & -0.18013 & 0.0872135 \tabularnewline
14 & 94.18 & 94.1068 & 94.0629 & 0.0439323 & 0.073151 \tabularnewline
15 & 94.43 & 94.4295 & 94.2783 & 0.15112 & 0.000546875 \tabularnewline
16 & 94.53 & 94.5685 & 94.47 & 0.0985156 & -0.0385156 \tabularnewline
17 & 94.66 & 94.6793 & 94.6625 & 0.016849 & -0.019349 \tabularnewline
18 & 94.8 & 94.8247 & 94.8621 & -0.0374219 & -0.0246615 \tabularnewline
19 & 95.04 & 95.0155 & 95.0642 & -0.0486719 & 0.0245052 \tabularnewline
20 & 95.29 & 95.2086 & 95.2575 & -0.0488802 & 0.0813802 \tabularnewline
21 & 95.42 & 95.4925 & 95.4517 & 0.0408073 & -0.072474 \tabularnewline
22 & 95.64 & 95.7466 & 95.6562 & 0.0903906 & -0.106641 \tabularnewline
23 & 95.82 & 95.8562 & 95.8675 & -0.011276 & -0.036224 \tabularnewline
24 & 96.01 & 95.9698 & 96.085 & -0.115234 & 0.0402344 \tabularnewline
25 & 96.16 & 96.1224 & 96.3025 & -0.18013 & 0.0376302 \tabularnewline
26 & 96.4 & 96.5648 & 96.5208 & 0.0439323 & -0.164766 \tabularnewline
27 & 96.87 & 96.8936 & 96.7425 & 0.15112 & -0.0236198 \tabularnewline
28 & 97 & 97.0631 & 96.9646 & 0.0985156 & -0.063099 \tabularnewline
29 & 97.26 & 97.2002 & 97.1833 & 0.016849 & 0.0598177 \tabularnewline
30 & 97.42 & 97.3576 & 97.395 & -0.0374219 & 0.0624219 \tabularnewline
31 & 97.64 & 97.5542 & 97.6029 & -0.0486719 & 0.0857552 \tabularnewline
32 & 97.93 & 97.7711 & 97.82 & -0.0488802 & 0.15888 \tabularnewline
33 & 98.1 & 98.0775 & 98.0367 & 0.0408073 & 0.022526 \tabularnewline
34 & 98.29 & 98.3371 & 98.2467 & 0.0903906 & -0.0470573 \tabularnewline
35 & 98.42 & 98.4379 & 98.4492 & -0.011276 & -0.0178906 \tabularnewline
36 & 98.49 & 98.5285 & 98.6438 & -0.115234 & -0.0385156 \tabularnewline
37 & 98.67 & 98.6624 & 98.8425 & -0.18013 & 0.00763021 \tabularnewline
38 & 99.1 & 99.0843 & 99.0404 & 0.0439323 & 0.015651 \tabularnewline
39 & 99.37 & 99.3915 & 99.2404 & 0.15112 & -0.0215365 \tabularnewline
40 & 99.54 & 99.5523 & 99.4537 & 0.0985156 & -0.0122656 \tabularnewline
41 & 99.58 & 99.6898 & 99.6729 & 0.016849 & -0.109766 \tabularnewline
42 & 99.77 & 99.8538 & 99.8912 & -0.0374219 & -0.0838281 \tabularnewline
43 & 100.06 & 100.06 & 100.109 & -0.0486719 & -7.8125e-05 \tabularnewline
44 & 100.26 & 100.286 & 100.335 & -0.0488802 & -0.0261198 \tabularnewline
45 & 100.57 & 100.615 & 100.574 & 0.0408073 & -0.0445573 \tabularnewline
46 & 100.94 & 100.908 & 100.818 & 0.0903906 & 0.0316927 \tabularnewline
47 & 101.03 & 101.057 & 101.068 & -0.011276 & -0.0266406 \tabularnewline
48 & 101.12 & 101.204 & 101.319 & -0.115234 & -0.0835156 \tabularnewline
49 & 101.26 & 101.387 & 101.568 & -0.18013 & -0.12737 \tabularnewline
50 & 101.94 & 101.859 & 101.815 & 0.0439323 & 0.0810677 \tabularnewline
51 & 102.26 & 102.21 & 102.059 & 0.15112 & 0.0497135 \tabularnewline
52 & 102.51 & 102.391 & 102.292 & 0.0985156 & 0.118984 \tabularnewline
53 & 102.61 & 102.536 & 102.519 & 0.016849 & 0.074401 \tabularnewline
54 & 102.76 & 102.709 & 102.746 & -0.0374219 & 0.0511719 \tabularnewline
55 & 103.04 & NA & NA & -0.0486719 & NA \tabularnewline
56 & 103.22 & NA & NA & -0.0488802 & NA \tabularnewline
57 & 103.47 & NA & NA & 0.0408073 & NA \tabularnewline
58 & 103.64 & NA & NA & 0.0903906 & NA \tabularnewline
59 & 103.76 & NA & NA & -0.011276 & NA \tabularnewline
60 & 103.85 & NA & NA & -0.115234 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294989&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]91.27[/C][C]NA[/C][C]NA[/C][C]-0.18013[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]91.51[/C][C]NA[/C][C]NA[/C][C]0.0439323[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]91.78[/C][C]NA[/C][C]NA[/C][C]0.15112[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]91.83[/C][C]NA[/C][C]NA[/C][C]0.0985156[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.01[/C][C]NA[/C][C]NA[/C][C]0.016849[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.1[/C][C]NA[/C][C]NA[/C][C]-0.0374219[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]92.35[/C][C]92.4551[/C][C]92.5037[/C][C]-0.0486719[/C][C]-0.105078[/C][/ROW]
[ROW][C]8[/C][C]92.46[/C][C]92.669[/C][C]92.7179[/C][C]-0.0488802[/C][C]-0.209036[/C][/ROW]
[ROW][C]9[/C][C]93.08[/C][C]92.9804[/C][C]92.9396[/C][C]0.0408073[/C][C]0.0996094[/C][/ROW]
[ROW][C]10[/C][C]93.38[/C][C]93.2529[/C][C]93.1625[/C][C]0.0903906[/C][C]0.127109[/C][/ROW]
[ROW][C]11[/C][C]93.46[/C][C]93.3741[/C][C]93.3854[/C][C]-0.011276[/C][C]0.0858594[/C][/ROW]
[ROW][C]12[/C][C]93.58[/C][C]93.4931[/C][C]93.6083[/C][C]-0.115234[/C][C]0.086901[/C][/ROW]
[ROW][C]13[/C][C]93.74[/C][C]93.6528[/C][C]93.8329[/C][C]-0.18013[/C][C]0.0872135[/C][/ROW]
[ROW][C]14[/C][C]94.18[/C][C]94.1068[/C][C]94.0629[/C][C]0.0439323[/C][C]0.073151[/C][/ROW]
[ROW][C]15[/C][C]94.43[/C][C]94.4295[/C][C]94.2783[/C][C]0.15112[/C][C]0.000546875[/C][/ROW]
[ROW][C]16[/C][C]94.53[/C][C]94.5685[/C][C]94.47[/C][C]0.0985156[/C][C]-0.0385156[/C][/ROW]
[ROW][C]17[/C][C]94.66[/C][C]94.6793[/C][C]94.6625[/C][C]0.016849[/C][C]-0.019349[/C][/ROW]
[ROW][C]18[/C][C]94.8[/C][C]94.8247[/C][C]94.8621[/C][C]-0.0374219[/C][C]-0.0246615[/C][/ROW]
[ROW][C]19[/C][C]95.04[/C][C]95.0155[/C][C]95.0642[/C][C]-0.0486719[/C][C]0.0245052[/C][/ROW]
[ROW][C]20[/C][C]95.29[/C][C]95.2086[/C][C]95.2575[/C][C]-0.0488802[/C][C]0.0813802[/C][/ROW]
[ROW][C]21[/C][C]95.42[/C][C]95.4925[/C][C]95.4517[/C][C]0.0408073[/C][C]-0.072474[/C][/ROW]
[ROW][C]22[/C][C]95.64[/C][C]95.7466[/C][C]95.6562[/C][C]0.0903906[/C][C]-0.106641[/C][/ROW]
[ROW][C]23[/C][C]95.82[/C][C]95.8562[/C][C]95.8675[/C][C]-0.011276[/C][C]-0.036224[/C][/ROW]
[ROW][C]24[/C][C]96.01[/C][C]95.9698[/C][C]96.085[/C][C]-0.115234[/C][C]0.0402344[/C][/ROW]
[ROW][C]25[/C][C]96.16[/C][C]96.1224[/C][C]96.3025[/C][C]-0.18013[/C][C]0.0376302[/C][/ROW]
[ROW][C]26[/C][C]96.4[/C][C]96.5648[/C][C]96.5208[/C][C]0.0439323[/C][C]-0.164766[/C][/ROW]
[ROW][C]27[/C][C]96.87[/C][C]96.8936[/C][C]96.7425[/C][C]0.15112[/C][C]-0.0236198[/C][/ROW]
[ROW][C]28[/C][C]97[/C][C]97.0631[/C][C]96.9646[/C][C]0.0985156[/C][C]-0.063099[/C][/ROW]
[ROW][C]29[/C][C]97.26[/C][C]97.2002[/C][C]97.1833[/C][C]0.016849[/C][C]0.0598177[/C][/ROW]
[ROW][C]30[/C][C]97.42[/C][C]97.3576[/C][C]97.395[/C][C]-0.0374219[/C][C]0.0624219[/C][/ROW]
[ROW][C]31[/C][C]97.64[/C][C]97.5542[/C][C]97.6029[/C][C]-0.0486719[/C][C]0.0857552[/C][/ROW]
[ROW][C]32[/C][C]97.93[/C][C]97.7711[/C][C]97.82[/C][C]-0.0488802[/C][C]0.15888[/C][/ROW]
[ROW][C]33[/C][C]98.1[/C][C]98.0775[/C][C]98.0367[/C][C]0.0408073[/C][C]0.022526[/C][/ROW]
[ROW][C]34[/C][C]98.29[/C][C]98.3371[/C][C]98.2467[/C][C]0.0903906[/C][C]-0.0470573[/C][/ROW]
[ROW][C]35[/C][C]98.42[/C][C]98.4379[/C][C]98.4492[/C][C]-0.011276[/C][C]-0.0178906[/C][/ROW]
[ROW][C]36[/C][C]98.49[/C][C]98.5285[/C][C]98.6438[/C][C]-0.115234[/C][C]-0.0385156[/C][/ROW]
[ROW][C]37[/C][C]98.67[/C][C]98.6624[/C][C]98.8425[/C][C]-0.18013[/C][C]0.00763021[/C][/ROW]
[ROW][C]38[/C][C]99.1[/C][C]99.0843[/C][C]99.0404[/C][C]0.0439323[/C][C]0.015651[/C][/ROW]
[ROW][C]39[/C][C]99.37[/C][C]99.3915[/C][C]99.2404[/C][C]0.15112[/C][C]-0.0215365[/C][/ROW]
[ROW][C]40[/C][C]99.54[/C][C]99.5523[/C][C]99.4537[/C][C]0.0985156[/C][C]-0.0122656[/C][/ROW]
[ROW][C]41[/C][C]99.58[/C][C]99.6898[/C][C]99.6729[/C][C]0.016849[/C][C]-0.109766[/C][/ROW]
[ROW][C]42[/C][C]99.77[/C][C]99.8538[/C][C]99.8912[/C][C]-0.0374219[/C][C]-0.0838281[/C][/ROW]
[ROW][C]43[/C][C]100.06[/C][C]100.06[/C][C]100.109[/C][C]-0.0486719[/C][C]-7.8125e-05[/C][/ROW]
[ROW][C]44[/C][C]100.26[/C][C]100.286[/C][C]100.335[/C][C]-0.0488802[/C][C]-0.0261198[/C][/ROW]
[ROW][C]45[/C][C]100.57[/C][C]100.615[/C][C]100.574[/C][C]0.0408073[/C][C]-0.0445573[/C][/ROW]
[ROW][C]46[/C][C]100.94[/C][C]100.908[/C][C]100.818[/C][C]0.0903906[/C][C]0.0316927[/C][/ROW]
[ROW][C]47[/C][C]101.03[/C][C]101.057[/C][C]101.068[/C][C]-0.011276[/C][C]-0.0266406[/C][/ROW]
[ROW][C]48[/C][C]101.12[/C][C]101.204[/C][C]101.319[/C][C]-0.115234[/C][C]-0.0835156[/C][/ROW]
[ROW][C]49[/C][C]101.26[/C][C]101.387[/C][C]101.568[/C][C]-0.18013[/C][C]-0.12737[/C][/ROW]
[ROW][C]50[/C][C]101.94[/C][C]101.859[/C][C]101.815[/C][C]0.0439323[/C][C]0.0810677[/C][/ROW]
[ROW][C]51[/C][C]102.26[/C][C]102.21[/C][C]102.059[/C][C]0.15112[/C][C]0.0497135[/C][/ROW]
[ROW][C]52[/C][C]102.51[/C][C]102.391[/C][C]102.292[/C][C]0.0985156[/C][C]0.118984[/C][/ROW]
[ROW][C]53[/C][C]102.61[/C][C]102.536[/C][C]102.519[/C][C]0.016849[/C][C]0.074401[/C][/ROW]
[ROW][C]54[/C][C]102.76[/C][C]102.709[/C][C]102.746[/C][C]-0.0374219[/C][C]0.0511719[/C][/ROW]
[ROW][C]55[/C][C]103.04[/C][C]NA[/C][C]NA[/C][C]-0.0486719[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]103.22[/C][C]NA[/C][C]NA[/C][C]-0.0488802[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]103.47[/C][C]NA[/C][C]NA[/C][C]0.0408073[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]103.64[/C][C]NA[/C][C]NA[/C][C]0.0903906[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]103.76[/C][C]NA[/C][C]NA[/C][C]-0.011276[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]103.85[/C][C]NA[/C][C]NA[/C][C]-0.115234[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294989&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294989&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	91.27	NA	NA	-0.18013	NA
2	91.51	NA	NA	0.0439323	NA
3	91.78	NA	NA	0.15112	NA
4	91.83	NA	NA	0.0985156	NA
5	92.01	NA	NA	0.016849	NA
6	92.1	NA	NA	-0.0374219	NA
7	92.35	92.4551	92.5037	-0.0486719	-0.105078
8	92.46	92.669	92.7179	-0.0488802	-0.209036
9	93.08	92.9804	92.9396	0.0408073	0.0996094
10	93.38	93.2529	93.1625	0.0903906	0.127109
11	93.46	93.3741	93.3854	-0.011276	0.0858594
12	93.58	93.4931	93.6083	-0.115234	0.086901
13	93.74	93.6528	93.8329	-0.18013	0.0872135
14	94.18	94.1068	94.0629	0.0439323	0.073151
15	94.43	94.4295	94.2783	0.15112	0.000546875
16	94.53	94.5685	94.47	0.0985156	-0.0385156
17	94.66	94.6793	94.6625	0.016849	-0.019349
18	94.8	94.8247	94.8621	-0.0374219	-0.0246615
19	95.04	95.0155	95.0642	-0.0486719	0.0245052
20	95.29	95.2086	95.2575	-0.0488802	0.0813802
21	95.42	95.4925	95.4517	0.0408073	-0.072474
22	95.64	95.7466	95.6562	0.0903906	-0.106641
23	95.82	95.8562	95.8675	-0.011276	-0.036224
24	96.01	95.9698	96.085	-0.115234	0.0402344
25	96.16	96.1224	96.3025	-0.18013	0.0376302
26	96.4	96.5648	96.5208	0.0439323	-0.164766
27	96.87	96.8936	96.7425	0.15112	-0.0236198
28	97	97.0631	96.9646	0.0985156	-0.063099
29	97.26	97.2002	97.1833	0.016849	0.0598177
30	97.42	97.3576	97.395	-0.0374219	0.0624219
31	97.64	97.5542	97.6029	-0.0486719	0.0857552
32	97.93	97.7711	97.82	-0.0488802	0.15888
33	98.1	98.0775	98.0367	0.0408073	0.022526
34	98.29	98.3371	98.2467	0.0903906	-0.0470573
35	98.42	98.4379	98.4492	-0.011276	-0.0178906
36	98.49	98.5285	98.6438	-0.115234	-0.0385156
37	98.67	98.6624	98.8425	-0.18013	0.00763021
38	99.1	99.0843	99.0404	0.0439323	0.015651
39	99.37	99.3915	99.2404	0.15112	-0.0215365
40	99.54	99.5523	99.4537	0.0985156	-0.0122656
41	99.58	99.6898	99.6729	0.016849	-0.109766
42	99.77	99.8538	99.8912	-0.0374219	-0.0838281
43	100.06	100.06	100.109	-0.0486719	-7.8125e-05
44	100.26	100.286	100.335	-0.0488802	-0.0261198
45	100.57	100.615	100.574	0.0408073	-0.0445573
46	100.94	100.908	100.818	0.0903906	0.0316927
47	101.03	101.057	101.068	-0.011276	-0.0266406
48	101.12	101.204	101.319	-0.115234	-0.0835156
49	101.26	101.387	101.568	-0.18013	-0.12737
50	101.94	101.859	101.815	0.0439323	0.0810677
51	102.26	102.21	102.059	0.15112	0.0497135
52	102.51	102.391	102.292	0.0985156	0.118984
53	102.61	102.536	102.519	0.016849	0.074401
54	102.76	102.709	102.746	-0.0374219	0.0511719
55	103.04	NA	NA	-0.0486719	NA
56	103.22	NA	NA	-0.0488802	NA
57	103.47	NA	NA	0.0408073	NA
58	103.64	NA	NA	0.0903906	NA
59	103.76	NA	NA	-0.011276	NA
60	103.85	NA	NA	-0.115234	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