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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 21:59:45 +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/25/t1461618049ngq99jbbua710ko.htm/, Retrieved Mon, 06 May 2024 01:53:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294800, Retrieved Mon, 06 May 2024 01:53:10 +0000

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-       [Classical Decomposition] [Consumptieprijsin...] [2016-04-25 20:59:45] [268d33ec1c95cc32f8abd6e0112b4a36] [Current]
-   PD    [Classical Decomposition] [Consumptieprijsin...] [2016-04-25 21:02:57] [e6773be784e85f51fb44487d8478f111] 
- R PD    [Classical Decomposition] [Levendgeborenen -...] [2016-04-25 21:04:28] [e6773be784e85f51fb44487d8478f111] 
- RMPD    [Exponential Smoothing] [Levendgeborenen -...] [2016-04-25 21:32:24] [e6773be784e85f51fb44487d8478f111] 
- RMP     [Exponential Smoothing] [Consumptieprijsin...] [2016-04-25 21:40:37] [e6773be784e85f51fb44487d8478f111] 

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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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294800&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294800&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294800&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 Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.72	NA	NA	-0.503125	NA
2	98.67	NA	NA	-0.4225	NA
3	98.82	NA	NA	-0.294375	NA
4	99.39	NA	NA	-0.643021	NA
5	99.33	NA	NA	0.175104	NA
6	99.22	NA	NA	0.361979	NA
7	99.05	99.6207	99.0037	0.616979	-0.570729
8	98.83	99.3903	99.0183	0.371979	-0.560312
9	98.84	99.526	99.0204	0.505625	-0.686042
10	98.89	98.4874	98.9771	-0.489687	0.402604
11	98.8	98.8125	98.9	-0.0875	-0.0125
12	99.4	99.2331	98.8246	0.408542	0.166875
13	98.89	98.2523	98.7554	-0.503125	0.637708
14	98.85	98.2679	98.6904	-0.4225	0.582083
15	98.69	98.3348	98.6292	-0.294375	0.355208
16	98.48	97.927	98.57	-0.643021	0.553021
17	98.39	98.6989	98.5237	0.175104	-0.308854
18	98.35	98.8378	98.4758	0.361979	-0.487812
19	98.26	99.0761	98.4592	0.616979	-0.816146
20	98.06	98.8778	98.5058	0.371979	-0.817812
21	98.14	99.1094	98.6038	0.505625	-0.969375
22	98.17	98.2566	98.7462	-0.489687	-0.0865625
23	98.41	98.825	98.9125	-0.0875	-0.415
24	98.64	99.4985	99.09	0.408542	-0.858542
25	99.25	98.7794	99.2825	-0.503125	0.470625
26	99.61	99.0742	99.4967	-0.4225	0.535833
27	100.28	99.4594	99.7538	-0.294375	0.820625
28	100.31	99.2553	99.8983	-0.643021	1.05469
29	100.55	100.1	99.925	0.175104	0.449896
30	100.45	100.339	99.9775	0.361979	0.110521
31	100.78	100.491	99.8737	0.616979	0.289271
32	100.68	99.9736	99.6017	0.371979	0.706354
33	101.69	99.7831	99.2775	0.505625	1.90688
34	98.09	98.4282	98.9179	-0.489687	-0.338229
35	99.13	98.5408	98.6283	-0.0875	0.589167
36	99.18	98.8444	98.4358	0.408542	0.335625
37	96.22	97.746	98.2492	-0.503125	-1.52604
38	96.11	97.5896	98.0121	-0.4225	-1.47958
39	96	97.3635	97.6579	-0.294375	-1.36354
40	95.96	96.6816	97.3246	-0.643021	-0.721563
41	97.95	97.218	97.0429	0.175104	0.731979
42	98.43	97.0853	96.7233	0.361979	1.34469
43	98.32	97.0991	96.4821	0.616979	1.22094
44	97.45	96.6549	96.2829	0.371979	0.795104
45	96.42	96.5481	96.0425	0.505625	-0.128125
46	95.36	95.2145	95.7042	-0.489687	0.145521
47	95.1	95.1383	95.2258	-0.0875	-0.0383333
48	95.54	95.0606	94.6521	0.408542	0.479375
49	94.07	93.529	94.0321	-0.503125	0.541042
50	93.48	92.995	93.4175	-0.4225	0.485
51	92.86	92.549	92.8433	-0.294375	0.311042
52	90.98	91.7428	92.3858	-0.643021	-0.762812
53	91.45	92.1997	92.0246	0.175104	-0.749688
54	91.16	92.0041	91.6421	0.361979	-0.844063
55	90.71	NA	NA	0.616979	NA
56	90.31	NA	NA	0.371979	NA
57	89.78	NA	NA	0.505625	NA
58	91.02	NA	NA	-0.489687	NA
59	90.77	NA	NA	-0.0875	NA
60	90.69	NA	NA	0.408542	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.72 & NA & NA & -0.503125 & NA \tabularnewline
2 & 98.67 & NA & NA & -0.4225 & NA \tabularnewline
3 & 98.82 & NA & NA & -0.294375 & NA \tabularnewline
4 & 99.39 & NA & NA & -0.643021 & NA \tabularnewline
5 & 99.33 & NA & NA & 0.175104 & NA \tabularnewline
6 & 99.22 & NA & NA & 0.361979 & NA \tabularnewline
7 & 99.05 & 99.6207 & 99.0037 & 0.616979 & -0.570729 \tabularnewline
8 & 98.83 & 99.3903 & 99.0183 & 0.371979 & -0.560312 \tabularnewline
9 & 98.84 & 99.526 & 99.0204 & 0.505625 & -0.686042 \tabularnewline
10 & 98.89 & 98.4874 & 98.9771 & -0.489687 & 0.402604 \tabularnewline
11 & 98.8 & 98.8125 & 98.9 & -0.0875 & -0.0125 \tabularnewline
12 & 99.4 & 99.2331 & 98.8246 & 0.408542 & 0.166875 \tabularnewline
13 & 98.89 & 98.2523 & 98.7554 & -0.503125 & 0.637708 \tabularnewline
14 & 98.85 & 98.2679 & 98.6904 & -0.4225 & 0.582083 \tabularnewline
15 & 98.69 & 98.3348 & 98.6292 & -0.294375 & 0.355208 \tabularnewline
16 & 98.48 & 97.927 & 98.57 & -0.643021 & 0.553021 \tabularnewline
17 & 98.39 & 98.6989 & 98.5237 & 0.175104 & -0.308854 \tabularnewline
18 & 98.35 & 98.8378 & 98.4758 & 0.361979 & -0.487812 \tabularnewline
19 & 98.26 & 99.0761 & 98.4592 & 0.616979 & -0.816146 \tabularnewline
20 & 98.06 & 98.8778 & 98.5058 & 0.371979 & -0.817812 \tabularnewline
21 & 98.14 & 99.1094 & 98.6038 & 0.505625 & -0.969375 \tabularnewline
22 & 98.17 & 98.2566 & 98.7462 & -0.489687 & -0.0865625 \tabularnewline
23 & 98.41 & 98.825 & 98.9125 & -0.0875 & -0.415 \tabularnewline
24 & 98.64 & 99.4985 & 99.09 & 0.408542 & -0.858542 \tabularnewline
25 & 99.25 & 98.7794 & 99.2825 & -0.503125 & 0.470625 \tabularnewline
26 & 99.61 & 99.0742 & 99.4967 & -0.4225 & 0.535833 \tabularnewline
27 & 100.28 & 99.4594 & 99.7538 & -0.294375 & 0.820625 \tabularnewline
28 & 100.31 & 99.2553 & 99.8983 & -0.643021 & 1.05469 \tabularnewline
29 & 100.55 & 100.1 & 99.925 & 0.175104 & 0.449896 \tabularnewline
30 & 100.45 & 100.339 & 99.9775 & 0.361979 & 0.110521 \tabularnewline
31 & 100.78 & 100.491 & 99.8737 & 0.616979 & 0.289271 \tabularnewline
32 & 100.68 & 99.9736 & 99.6017 & 0.371979 & 0.706354 \tabularnewline
33 & 101.69 & 99.7831 & 99.2775 & 0.505625 & 1.90688 \tabularnewline
34 & 98.09 & 98.4282 & 98.9179 & -0.489687 & -0.338229 \tabularnewline
35 & 99.13 & 98.5408 & 98.6283 & -0.0875 & 0.589167 \tabularnewline
36 & 99.18 & 98.8444 & 98.4358 & 0.408542 & 0.335625 \tabularnewline
37 & 96.22 & 97.746 & 98.2492 & -0.503125 & -1.52604 \tabularnewline
38 & 96.11 & 97.5896 & 98.0121 & -0.4225 & -1.47958 \tabularnewline
39 & 96 & 97.3635 & 97.6579 & -0.294375 & -1.36354 \tabularnewline
40 & 95.96 & 96.6816 & 97.3246 & -0.643021 & -0.721563 \tabularnewline
41 & 97.95 & 97.218 & 97.0429 & 0.175104 & 0.731979 \tabularnewline
42 & 98.43 & 97.0853 & 96.7233 & 0.361979 & 1.34469 \tabularnewline
43 & 98.32 & 97.0991 & 96.4821 & 0.616979 & 1.22094 \tabularnewline
44 & 97.45 & 96.6549 & 96.2829 & 0.371979 & 0.795104 \tabularnewline
45 & 96.42 & 96.5481 & 96.0425 & 0.505625 & -0.128125 \tabularnewline
46 & 95.36 & 95.2145 & 95.7042 & -0.489687 & 0.145521 \tabularnewline
47 & 95.1 & 95.1383 & 95.2258 & -0.0875 & -0.0383333 \tabularnewline
48 & 95.54 & 95.0606 & 94.6521 & 0.408542 & 0.479375 \tabularnewline
49 & 94.07 & 93.529 & 94.0321 & -0.503125 & 0.541042 \tabularnewline
50 & 93.48 & 92.995 & 93.4175 & -0.4225 & 0.485 \tabularnewline
51 & 92.86 & 92.549 & 92.8433 & -0.294375 & 0.311042 \tabularnewline
52 & 90.98 & 91.7428 & 92.3858 & -0.643021 & -0.762812 \tabularnewline
53 & 91.45 & 92.1997 & 92.0246 & 0.175104 & -0.749688 \tabularnewline
54 & 91.16 & 92.0041 & 91.6421 & 0.361979 & -0.844063 \tabularnewline
55 & 90.71 & NA & NA & 0.616979 & NA \tabularnewline
56 & 90.31 & NA & NA & 0.371979 & NA \tabularnewline
57 & 89.78 & NA & NA & 0.505625 & NA \tabularnewline
58 & 91.02 & NA & NA & -0.489687 & NA \tabularnewline
59 & 90.77 & NA & NA & -0.0875 & NA \tabularnewline
60 & 90.69 & NA & NA & 0.408542 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294800&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]98.72[/C][C]NA[/C][C]NA[/C][C]-0.503125[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.67[/C][C]NA[/C][C]NA[/C][C]-0.4225[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]98.82[/C][C]NA[/C][C]NA[/C][C]-0.294375[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]99.39[/C][C]NA[/C][C]NA[/C][C]-0.643021[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]99.33[/C][C]NA[/C][C]NA[/C][C]0.175104[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]99.22[/C][C]NA[/C][C]NA[/C][C]0.361979[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.05[/C][C]99.6207[/C][C]99.0037[/C][C]0.616979[/C][C]-0.570729[/C][/ROW]
[ROW][C]8[/C][C]98.83[/C][C]99.3903[/C][C]99.0183[/C][C]0.371979[/C][C]-0.560312[/C][/ROW]
[ROW][C]9[/C][C]98.84[/C][C]99.526[/C][C]99.0204[/C][C]0.505625[/C][C]-0.686042[/C][/ROW]
[ROW][C]10[/C][C]98.89[/C][C]98.4874[/C][C]98.9771[/C][C]-0.489687[/C][C]0.402604[/C][/ROW]
[ROW][C]11[/C][C]98.8[/C][C]98.8125[/C][C]98.9[/C][C]-0.0875[/C][C]-0.0125[/C][/ROW]
[ROW][C]12[/C][C]99.4[/C][C]99.2331[/C][C]98.8246[/C][C]0.408542[/C][C]0.166875[/C][/ROW]
[ROW][C]13[/C][C]98.89[/C][C]98.2523[/C][C]98.7554[/C][C]-0.503125[/C][C]0.637708[/C][/ROW]
[ROW][C]14[/C][C]98.85[/C][C]98.2679[/C][C]98.6904[/C][C]-0.4225[/C][C]0.582083[/C][/ROW]
[ROW][C]15[/C][C]98.69[/C][C]98.3348[/C][C]98.6292[/C][C]-0.294375[/C][C]0.355208[/C][/ROW]
[ROW][C]16[/C][C]98.48[/C][C]97.927[/C][C]98.57[/C][C]-0.643021[/C][C]0.553021[/C][/ROW]
[ROW][C]17[/C][C]98.39[/C][C]98.6989[/C][C]98.5237[/C][C]0.175104[/C][C]-0.308854[/C][/ROW]
[ROW][C]18[/C][C]98.35[/C][C]98.8378[/C][C]98.4758[/C][C]0.361979[/C][C]-0.487812[/C][/ROW]
[ROW][C]19[/C][C]98.26[/C][C]99.0761[/C][C]98.4592[/C][C]0.616979[/C][C]-0.816146[/C][/ROW]
[ROW][C]20[/C][C]98.06[/C][C]98.8778[/C][C]98.5058[/C][C]0.371979[/C][C]-0.817812[/C][/ROW]
[ROW][C]21[/C][C]98.14[/C][C]99.1094[/C][C]98.6038[/C][C]0.505625[/C][C]-0.969375[/C][/ROW]
[ROW][C]22[/C][C]98.17[/C][C]98.2566[/C][C]98.7462[/C][C]-0.489687[/C][C]-0.0865625[/C][/ROW]
[ROW][C]23[/C][C]98.41[/C][C]98.825[/C][C]98.9125[/C][C]-0.0875[/C][C]-0.415[/C][/ROW]
[ROW][C]24[/C][C]98.64[/C][C]99.4985[/C][C]99.09[/C][C]0.408542[/C][C]-0.858542[/C][/ROW]
[ROW][C]25[/C][C]99.25[/C][C]98.7794[/C][C]99.2825[/C][C]-0.503125[/C][C]0.470625[/C][/ROW]
[ROW][C]26[/C][C]99.61[/C][C]99.0742[/C][C]99.4967[/C][C]-0.4225[/C][C]0.535833[/C][/ROW]
[ROW][C]27[/C][C]100.28[/C][C]99.4594[/C][C]99.7538[/C][C]-0.294375[/C][C]0.820625[/C][/ROW]
[ROW][C]28[/C][C]100.31[/C][C]99.2553[/C][C]99.8983[/C][C]-0.643021[/C][C]1.05469[/C][/ROW]
[ROW][C]29[/C][C]100.55[/C][C]100.1[/C][C]99.925[/C][C]0.175104[/C][C]0.449896[/C][/ROW]
[ROW][C]30[/C][C]100.45[/C][C]100.339[/C][C]99.9775[/C][C]0.361979[/C][C]0.110521[/C][/ROW]
[ROW][C]31[/C][C]100.78[/C][C]100.491[/C][C]99.8737[/C][C]0.616979[/C][C]0.289271[/C][/ROW]
[ROW][C]32[/C][C]100.68[/C][C]99.9736[/C][C]99.6017[/C][C]0.371979[/C][C]0.706354[/C][/ROW]
[ROW][C]33[/C][C]101.69[/C][C]99.7831[/C][C]99.2775[/C][C]0.505625[/C][C]1.90688[/C][/ROW]
[ROW][C]34[/C][C]98.09[/C][C]98.4282[/C][C]98.9179[/C][C]-0.489687[/C][C]-0.338229[/C][/ROW]
[ROW][C]35[/C][C]99.13[/C][C]98.5408[/C][C]98.6283[/C][C]-0.0875[/C][C]0.589167[/C][/ROW]
[ROW][C]36[/C][C]99.18[/C][C]98.8444[/C][C]98.4358[/C][C]0.408542[/C][C]0.335625[/C][/ROW]
[ROW][C]37[/C][C]96.22[/C][C]97.746[/C][C]98.2492[/C][C]-0.503125[/C][C]-1.52604[/C][/ROW]
[ROW][C]38[/C][C]96.11[/C][C]97.5896[/C][C]98.0121[/C][C]-0.4225[/C][C]-1.47958[/C][/ROW]
[ROW][C]39[/C][C]96[/C][C]97.3635[/C][C]97.6579[/C][C]-0.294375[/C][C]-1.36354[/C][/ROW]
[ROW][C]40[/C][C]95.96[/C][C]96.6816[/C][C]97.3246[/C][C]-0.643021[/C][C]-0.721563[/C][/ROW]
[ROW][C]41[/C][C]97.95[/C][C]97.218[/C][C]97.0429[/C][C]0.175104[/C][C]0.731979[/C][/ROW]
[ROW][C]42[/C][C]98.43[/C][C]97.0853[/C][C]96.7233[/C][C]0.361979[/C][C]1.34469[/C][/ROW]
[ROW][C]43[/C][C]98.32[/C][C]97.0991[/C][C]96.4821[/C][C]0.616979[/C][C]1.22094[/C][/ROW]
[ROW][C]44[/C][C]97.45[/C][C]96.6549[/C][C]96.2829[/C][C]0.371979[/C][C]0.795104[/C][/ROW]
[ROW][C]45[/C][C]96.42[/C][C]96.5481[/C][C]96.0425[/C][C]0.505625[/C][C]-0.128125[/C][/ROW]
[ROW][C]46[/C][C]95.36[/C][C]95.2145[/C][C]95.7042[/C][C]-0.489687[/C][C]0.145521[/C][/ROW]
[ROW][C]47[/C][C]95.1[/C][C]95.1383[/C][C]95.2258[/C][C]-0.0875[/C][C]-0.0383333[/C][/ROW]
[ROW][C]48[/C][C]95.54[/C][C]95.0606[/C][C]94.6521[/C][C]0.408542[/C][C]0.479375[/C][/ROW]
[ROW][C]49[/C][C]94.07[/C][C]93.529[/C][C]94.0321[/C][C]-0.503125[/C][C]0.541042[/C][/ROW]
[ROW][C]50[/C][C]93.48[/C][C]92.995[/C][C]93.4175[/C][C]-0.4225[/C][C]0.485[/C][/ROW]
[ROW][C]51[/C][C]92.86[/C][C]92.549[/C][C]92.8433[/C][C]-0.294375[/C][C]0.311042[/C][/ROW]
[ROW][C]52[/C][C]90.98[/C][C]91.7428[/C][C]92.3858[/C][C]-0.643021[/C][C]-0.762812[/C][/ROW]
[ROW][C]53[/C][C]91.45[/C][C]92.1997[/C][C]92.0246[/C][C]0.175104[/C][C]-0.749688[/C][/ROW]
[ROW][C]54[/C][C]91.16[/C][C]92.0041[/C][C]91.6421[/C][C]0.361979[/C][C]-0.844063[/C][/ROW]
[ROW][C]55[/C][C]90.71[/C][C]NA[/C][C]NA[/C][C]0.616979[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]90.31[/C][C]NA[/C][C]NA[/C][C]0.371979[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]89.78[/C][C]NA[/C][C]NA[/C][C]0.505625[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]91.02[/C][C]NA[/C][C]NA[/C][C]-0.489687[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]90.77[/C][C]NA[/C][C]NA[/C][C]-0.0875[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]90.69[/C][C]NA[/C][C]NA[/C][C]0.408542[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294800&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294800&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	98.72	NA	NA	-0.503125	NA
2	98.67	NA	NA	-0.4225	NA
3	98.82	NA	NA	-0.294375	NA
4	99.39	NA	NA	-0.643021	NA
5	99.33	NA	NA	0.175104	NA
6	99.22	NA	NA	0.361979	NA
7	99.05	99.6207	99.0037	0.616979	-0.570729
8	98.83	99.3903	99.0183	0.371979	-0.560312
9	98.84	99.526	99.0204	0.505625	-0.686042
10	98.89	98.4874	98.9771	-0.489687	0.402604
11	98.8	98.8125	98.9	-0.0875	-0.0125
12	99.4	99.2331	98.8246	0.408542	0.166875
13	98.89	98.2523	98.7554	-0.503125	0.637708
14	98.85	98.2679	98.6904	-0.4225	0.582083
15	98.69	98.3348	98.6292	-0.294375	0.355208
16	98.48	97.927	98.57	-0.643021	0.553021
17	98.39	98.6989	98.5237	0.175104	-0.308854
18	98.35	98.8378	98.4758	0.361979	-0.487812
19	98.26	99.0761	98.4592	0.616979	-0.816146
20	98.06	98.8778	98.5058	0.371979	-0.817812
21	98.14	99.1094	98.6038	0.505625	-0.969375
22	98.17	98.2566	98.7462	-0.489687	-0.0865625
23	98.41	98.825	98.9125	-0.0875	-0.415
24	98.64	99.4985	99.09	0.408542	-0.858542
25	99.25	98.7794	99.2825	-0.503125	0.470625
26	99.61	99.0742	99.4967	-0.4225	0.535833
27	100.28	99.4594	99.7538	-0.294375	0.820625
28	100.31	99.2553	99.8983	-0.643021	1.05469
29	100.55	100.1	99.925	0.175104	0.449896
30	100.45	100.339	99.9775	0.361979	0.110521
31	100.78	100.491	99.8737	0.616979	0.289271
32	100.68	99.9736	99.6017	0.371979	0.706354
33	101.69	99.7831	99.2775	0.505625	1.90688
34	98.09	98.4282	98.9179	-0.489687	-0.338229
35	99.13	98.5408	98.6283	-0.0875	0.589167
36	99.18	98.8444	98.4358	0.408542	0.335625
37	96.22	97.746	98.2492	-0.503125	-1.52604
38	96.11	97.5896	98.0121	-0.4225	-1.47958
39	96	97.3635	97.6579	-0.294375	-1.36354
40	95.96	96.6816	97.3246	-0.643021	-0.721563
41	97.95	97.218	97.0429	0.175104	0.731979
42	98.43	97.0853	96.7233	0.361979	1.34469
43	98.32	97.0991	96.4821	0.616979	1.22094
44	97.45	96.6549	96.2829	0.371979	0.795104
45	96.42	96.5481	96.0425	0.505625	-0.128125
46	95.36	95.2145	95.7042	-0.489687	0.145521
47	95.1	95.1383	95.2258	-0.0875	-0.0383333
48	95.54	95.0606	94.6521	0.408542	0.479375
49	94.07	93.529	94.0321	-0.503125	0.541042
50	93.48	92.995	93.4175	-0.4225	0.485
51	92.86	92.549	92.8433	-0.294375	0.311042
52	90.98	91.7428	92.3858	-0.643021	-0.762812
53	91.45	92.1997	92.0246	0.175104	-0.749688
54	91.16	92.0041	91.6421	0.361979	-0.844063
55	90.71	NA	NA	0.616979	NA
56	90.31	NA	NA	0.371979	NA
57	89.78	NA	NA	0.505625	NA
58	91.02	NA	NA	-0.489687	NA
59	90.77	NA	NA	-0.0875	NA
60	90.69	NA	NA	0.408542	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 <- '12'
par1 <- 'additive'
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