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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 09 Dec 2012 13:26:49 -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/2012/Dec/09/t1355077628iq56ykthej3czlj.htm/, Retrieved Sat, 20 Apr 2024 05:49:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198024, Retrieved Sat, 20 Apr 2024 05:49:25 +0000

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Estimated Impact

131

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

-       [Classical Decomposition] [] [2012-12-09 18:26:49] [50b2e07c322f56d9c76b19a7ea7f6b48] [Current]

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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	4 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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198024&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]4 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=198024&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198024&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	4 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	10	NA	NA	0.998326441325252	NA
2	9.99	NA	NA	1.00298933670607	NA
3	9.95	NA	NA	1.00432191705148	NA
4	9.96	NA	NA	1.00412163595221	NA
5	9.97	NA	NA	1.00045999509418	NA
6	9.95	NA	NA	1.00044210938845	NA
7	9.94	9.92849324264121	9.94	0.998842378535333	1.00115896310523
8	9.9	9.93320427650637	9.93625	0.999693473544483	0.99665724416995
9	9.9	9.91236358427428	9.93541666666667	0.997679706532115	0.998752710776883
10	9.92	9.89165738700491	9.93291666666666	0.995846207005822	1.00286530475998
11	9.87	9.90456420074596	9.92375	0.998066678498144	0.996510275460342
12	9.96	9.90467031813265	9.9125	0.999210120366472	1.00558622145818
13	9.94	9.88634355457386	9.90291666666666	0.998326441325252	1.00542732964214
14	9.96	9.92457948670651	9.895	1.00298933670607	1.00356896867428
15	9.96	9.92897755245016	9.88625	1.00432191705148	1.00312443525891
16	9.89	9.9106805468483	9.87	1.00412163595221	0.997913307088192
17	9.82	9.8561983850028	9.85166666666667	1.00045999509418	0.99632734817332
18	9.83	9.83643018968302	9.83208333333333	1.00044210938845	0.999346288281519
19	9.83	9.79864373343162	9.81	0.998842378535333	1.00320006190871
20	9.82	9.78908180073704	9.79208333333333	0.999693473544483	1.00315843711314
21	9.77	9.75439763074003	9.77708333333333	0.997679706532115	1.00159952155434
22	9.66	9.72609795509019	9.76666666666667	0.995846207005822	0.993204062369575
23	9.69	9.74237836549001	9.76125	0.998066678498144	0.994623657229784
24	9.67	9.7493764119257	9.75708333333333	0.999210120366472	0.991858308821823
25	9.7	9.73617861902452	9.7525	0.998326441325252	0.996284104838234
26	9.77	9.77789229621325	9.74875	1.00298933670607	0.999192842795343
27	9.79	9.78962788645927	9.7475	1.00432191705148	1.0000380109995
28	9.81	9.79227787060894	9.75208333333333	1.00412163595221	1.00180980662776
29	9.77	9.76574012711304	9.76125	1.00045999509418	1.00043620584119
30	9.78	9.77556996136189	9.77125	1.00044210938845	1.00045317445997
31	9.77	9.76951083072434	9.78083333333333	0.998842378535333	1.00005007101012
32	9.79	9.7832502554747	9.78625	0.999693473544483	1.00068992863814
33	9.77	9.76354302804991	9.78625	0.997679706532115	1.00066133492028
34	9.77	9.74311032779321	9.78375	0.995846207005822	1.00275986531016
35	9.8	9.76358728240809	9.7825	0.998066678498144	1.00372944047497
36	9.8	9.77518934003517	9.78291666666667	0.999210120366472	1.00253812576941
37	9.8	9.76862422836759	9.785	0.998326441325252	1.00321189257555
38	9.8	9.81717604523424	9.78791666666667	1.00298933670607	0.998250408757559
39	9.76	9.83440390526114	9.79208333333333	1.00432191705148	0.992434324847961
40	9.78	9.83955526430169	9.79916666666666	1.00412163595221	0.993947362182338
41	9.77	9.81576312686774	9.81125	1.00045999509418	0.995337792255553
42	9.79	9.83142797913608	9.82708333333333	1.00044210938845	0.995786168680277
43	9.81	9.8315222950584	9.84291666666666	0.998842378535333	0.997810888851951
44	9.82	9.85947688283246	9.8625	0.999693473544483	0.995996046919974
45	9.84	9.86372669858084	9.88666666666666	0.997679706532115	0.997594550284503
46	9.87	9.87049565510604	9.91166666666667	0.995846207005822	0.999949784172613
47	9.99	9.91745589534322	9.93666666666667	0.998066678498144	1.00731478974268
48	9.99	9.95171646129991	9.95958333333333	0.999210120366472	1.00384692820067
49	9.99	9.96288191507546	9.97958333333333	0.998326441325252	1.00272191170745
50	10.08	10.0315650159552	10.0016666666667	1.00298933670607	1.0048282580004
51	10.06	10.0683272184411	10.025	1.00432191705148	0.999172929299934
52	10.08	10.0872386011699	10.0458333333333	1.00412163595221	0.999282400123949
53	10.07	10.0662949839726	10.0616666666667	1.00045999509418	1.00036806153936
54	10.04	10.0790374012097	10.0745833333333	1.00044210938845	0.996126872075597
55	10.04	10.076654862124	10.0883333333333	0.998842378535333	0.996362397777289
56	10.12	10.0989867775358	10.1020833333333	0.999693473544483	1.00208072581211
57	10.1	10.1002599290045	10.12375	0.997679706532115	0.999974265117301
58	10.11	10.111988360305	10.1541666666667	0.995846207005822	0.99980336604097
59	10.13	10.1665567038517	10.18625	0.998066678498144	0.996404219745524
60	10.16	10.213592780346	10.2216666666667	0.999210120366472	0.994752798403214
61	10.15	10.2428292879971	10.26	0.998326441325252	0.990937143889934
62	10.25	10.3249393969417	10.2941666666667	1.00298933670607	0.992741904425717
63	10.41	10.3704607284874	10.3258333333333	1.00432191705148	1.00381268224699
64	10.46	10.4014449964199	10.35875	1.00412163595221	1.00562950663107
65	10.46	10.3964467823537	10.3916666666667	1.00045999509418	1.00611297484389
66	10.5	10.4283584377379	10.42375	1.00044210938845	1.00686987915595
67	10.5	NA	NA	0.998842378535333	NA
68	10.48	NA	NA	0.999693473544483	NA
69	10.5	NA	NA	0.997679706532115	NA
70	10.5	NA	NA	0.995846207005822	NA
71	10.53	NA	NA	0.998066678498144	NA
72	10.53	NA	NA	0.999210120366472	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 10 & NA & NA & 0.998326441325252 & NA \tabularnewline
2 & 9.99 & NA & NA & 1.00298933670607 & NA \tabularnewline
3 & 9.95 & NA & NA & 1.00432191705148 & NA \tabularnewline
4 & 9.96 & NA & NA & 1.00412163595221 & NA \tabularnewline
5 & 9.97 & NA & NA & 1.00045999509418 & NA \tabularnewline
6 & 9.95 & NA & NA & 1.00044210938845 & NA \tabularnewline
7 & 9.94 & 9.92849324264121 & 9.94 & 0.998842378535333 & 1.00115896310523 \tabularnewline
8 & 9.9 & 9.93320427650637 & 9.93625 & 0.999693473544483 & 0.99665724416995 \tabularnewline
9 & 9.9 & 9.91236358427428 & 9.93541666666667 & 0.997679706532115 & 0.998752710776883 \tabularnewline
10 & 9.92 & 9.89165738700491 & 9.93291666666666 & 0.995846207005822 & 1.00286530475998 \tabularnewline
11 & 9.87 & 9.90456420074596 & 9.92375 & 0.998066678498144 & 0.996510275460342 \tabularnewline
12 & 9.96 & 9.90467031813265 & 9.9125 & 0.999210120366472 & 1.00558622145818 \tabularnewline
13 & 9.94 & 9.88634355457386 & 9.90291666666666 & 0.998326441325252 & 1.00542732964214 \tabularnewline
14 & 9.96 & 9.92457948670651 & 9.895 & 1.00298933670607 & 1.00356896867428 \tabularnewline
15 & 9.96 & 9.92897755245016 & 9.88625 & 1.00432191705148 & 1.00312443525891 \tabularnewline
16 & 9.89 & 9.9106805468483 & 9.87 & 1.00412163595221 & 0.997913307088192 \tabularnewline
17 & 9.82 & 9.8561983850028 & 9.85166666666667 & 1.00045999509418 & 0.99632734817332 \tabularnewline
18 & 9.83 & 9.83643018968302 & 9.83208333333333 & 1.00044210938845 & 0.999346288281519 \tabularnewline
19 & 9.83 & 9.79864373343162 & 9.81 & 0.998842378535333 & 1.00320006190871 \tabularnewline
20 & 9.82 & 9.78908180073704 & 9.79208333333333 & 0.999693473544483 & 1.00315843711314 \tabularnewline
21 & 9.77 & 9.75439763074003 & 9.77708333333333 & 0.997679706532115 & 1.00159952155434 \tabularnewline
22 & 9.66 & 9.72609795509019 & 9.76666666666667 & 0.995846207005822 & 0.993204062369575 \tabularnewline
23 & 9.69 & 9.74237836549001 & 9.76125 & 0.998066678498144 & 0.994623657229784 \tabularnewline
24 & 9.67 & 9.7493764119257 & 9.75708333333333 & 0.999210120366472 & 0.991858308821823 \tabularnewline
25 & 9.7 & 9.73617861902452 & 9.7525 & 0.998326441325252 & 0.996284104838234 \tabularnewline
26 & 9.77 & 9.77789229621325 & 9.74875 & 1.00298933670607 & 0.999192842795343 \tabularnewline
27 & 9.79 & 9.78962788645927 & 9.7475 & 1.00432191705148 & 1.0000380109995 \tabularnewline
28 & 9.81 & 9.79227787060894 & 9.75208333333333 & 1.00412163595221 & 1.00180980662776 \tabularnewline
29 & 9.77 & 9.76574012711304 & 9.76125 & 1.00045999509418 & 1.00043620584119 \tabularnewline
30 & 9.78 & 9.77556996136189 & 9.77125 & 1.00044210938845 & 1.00045317445997 \tabularnewline
31 & 9.77 & 9.76951083072434 & 9.78083333333333 & 0.998842378535333 & 1.00005007101012 \tabularnewline
32 & 9.79 & 9.7832502554747 & 9.78625 & 0.999693473544483 & 1.00068992863814 \tabularnewline
33 & 9.77 & 9.76354302804991 & 9.78625 & 0.997679706532115 & 1.00066133492028 \tabularnewline
34 & 9.77 & 9.74311032779321 & 9.78375 & 0.995846207005822 & 1.00275986531016 \tabularnewline
35 & 9.8 & 9.76358728240809 & 9.7825 & 0.998066678498144 & 1.00372944047497 \tabularnewline
36 & 9.8 & 9.77518934003517 & 9.78291666666667 & 0.999210120366472 & 1.00253812576941 \tabularnewline
37 & 9.8 & 9.76862422836759 & 9.785 & 0.998326441325252 & 1.00321189257555 \tabularnewline
38 & 9.8 & 9.81717604523424 & 9.78791666666667 & 1.00298933670607 & 0.998250408757559 \tabularnewline
39 & 9.76 & 9.83440390526114 & 9.79208333333333 & 1.00432191705148 & 0.992434324847961 \tabularnewline
40 & 9.78 & 9.83955526430169 & 9.79916666666666 & 1.00412163595221 & 0.993947362182338 \tabularnewline
41 & 9.77 & 9.81576312686774 & 9.81125 & 1.00045999509418 & 0.995337792255553 \tabularnewline
42 & 9.79 & 9.83142797913608 & 9.82708333333333 & 1.00044210938845 & 0.995786168680277 \tabularnewline
43 & 9.81 & 9.8315222950584 & 9.84291666666666 & 0.998842378535333 & 0.997810888851951 \tabularnewline
44 & 9.82 & 9.85947688283246 & 9.8625 & 0.999693473544483 & 0.995996046919974 \tabularnewline
45 & 9.84 & 9.86372669858084 & 9.88666666666666 & 0.997679706532115 & 0.997594550284503 \tabularnewline
46 & 9.87 & 9.87049565510604 & 9.91166666666667 & 0.995846207005822 & 0.999949784172613 \tabularnewline
47 & 9.99 & 9.91745589534322 & 9.93666666666667 & 0.998066678498144 & 1.00731478974268 \tabularnewline
48 & 9.99 & 9.95171646129991 & 9.95958333333333 & 0.999210120366472 & 1.00384692820067 \tabularnewline
49 & 9.99 & 9.96288191507546 & 9.97958333333333 & 0.998326441325252 & 1.00272191170745 \tabularnewline
50 & 10.08 & 10.0315650159552 & 10.0016666666667 & 1.00298933670607 & 1.0048282580004 \tabularnewline
51 & 10.06 & 10.0683272184411 & 10.025 & 1.00432191705148 & 0.999172929299934 \tabularnewline
52 & 10.08 & 10.0872386011699 & 10.0458333333333 & 1.00412163595221 & 0.999282400123949 \tabularnewline
53 & 10.07 & 10.0662949839726 & 10.0616666666667 & 1.00045999509418 & 1.00036806153936 \tabularnewline
54 & 10.04 & 10.0790374012097 & 10.0745833333333 & 1.00044210938845 & 0.996126872075597 \tabularnewline
55 & 10.04 & 10.076654862124 & 10.0883333333333 & 0.998842378535333 & 0.996362397777289 \tabularnewline
56 & 10.12 & 10.0989867775358 & 10.1020833333333 & 0.999693473544483 & 1.00208072581211 \tabularnewline
57 & 10.1 & 10.1002599290045 & 10.12375 & 0.997679706532115 & 0.999974265117301 \tabularnewline
58 & 10.11 & 10.111988360305 & 10.1541666666667 & 0.995846207005822 & 0.99980336604097 \tabularnewline
59 & 10.13 & 10.1665567038517 & 10.18625 & 0.998066678498144 & 0.996404219745524 \tabularnewline
60 & 10.16 & 10.213592780346 & 10.2216666666667 & 0.999210120366472 & 0.994752798403214 \tabularnewline
61 & 10.15 & 10.2428292879971 & 10.26 & 0.998326441325252 & 0.990937143889934 \tabularnewline
62 & 10.25 & 10.3249393969417 & 10.2941666666667 & 1.00298933670607 & 0.992741904425717 \tabularnewline
63 & 10.41 & 10.3704607284874 & 10.3258333333333 & 1.00432191705148 & 1.00381268224699 \tabularnewline
64 & 10.46 & 10.4014449964199 & 10.35875 & 1.00412163595221 & 1.00562950663107 \tabularnewline
65 & 10.46 & 10.3964467823537 & 10.3916666666667 & 1.00045999509418 & 1.00611297484389 \tabularnewline
66 & 10.5 & 10.4283584377379 & 10.42375 & 1.00044210938845 & 1.00686987915595 \tabularnewline
67 & 10.5 & NA & NA & 0.998842378535333 & NA \tabularnewline
68 & 10.48 & NA & NA & 0.999693473544483 & NA \tabularnewline
69 & 10.5 & NA & NA & 0.997679706532115 & NA \tabularnewline
70 & 10.5 & NA & NA & 0.995846207005822 & NA \tabularnewline
71 & 10.53 & NA & NA & 0.998066678498144 & NA \tabularnewline
72 & 10.53 & NA & NA & 0.999210120366472 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198024&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]10[/C][C]NA[/C][C]NA[/C][C]0.998326441325252[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.99[/C][C]NA[/C][C]NA[/C][C]1.00298933670607[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9.95[/C][C]NA[/C][C]NA[/C][C]1.00432191705148[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9.96[/C][C]NA[/C][C]NA[/C][C]1.00412163595221[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]9.97[/C][C]NA[/C][C]NA[/C][C]1.00045999509418[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9.95[/C][C]NA[/C][C]NA[/C][C]1.00044210938845[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9.94[/C][C]9.92849324264121[/C][C]9.94[/C][C]0.998842378535333[/C][C]1.00115896310523[/C][/ROW]
[ROW][C]8[/C][C]9.9[/C][C]9.93320427650637[/C][C]9.93625[/C][C]0.999693473544483[/C][C]0.99665724416995[/C][/ROW]
[ROW][C]9[/C][C]9.9[/C][C]9.91236358427428[/C][C]9.93541666666667[/C][C]0.997679706532115[/C][C]0.998752710776883[/C][/ROW]
[ROW][C]10[/C][C]9.92[/C][C]9.89165738700491[/C][C]9.93291666666666[/C][C]0.995846207005822[/C][C]1.00286530475998[/C][/ROW]
[ROW][C]11[/C][C]9.87[/C][C]9.90456420074596[/C][C]9.92375[/C][C]0.998066678498144[/C][C]0.996510275460342[/C][/ROW]
[ROW][C]12[/C][C]9.96[/C][C]9.90467031813265[/C][C]9.9125[/C][C]0.999210120366472[/C][C]1.00558622145818[/C][/ROW]
[ROW][C]13[/C][C]9.94[/C][C]9.88634355457386[/C][C]9.90291666666666[/C][C]0.998326441325252[/C][C]1.00542732964214[/C][/ROW]
[ROW][C]14[/C][C]9.96[/C][C]9.92457948670651[/C][C]9.895[/C][C]1.00298933670607[/C][C]1.00356896867428[/C][/ROW]
[ROW][C]15[/C][C]9.96[/C][C]9.92897755245016[/C][C]9.88625[/C][C]1.00432191705148[/C][C]1.00312443525891[/C][/ROW]
[ROW][C]16[/C][C]9.89[/C][C]9.9106805468483[/C][C]9.87[/C][C]1.00412163595221[/C][C]0.997913307088192[/C][/ROW]
[ROW][C]17[/C][C]9.82[/C][C]9.8561983850028[/C][C]9.85166666666667[/C][C]1.00045999509418[/C][C]0.99632734817332[/C][/ROW]
[ROW][C]18[/C][C]9.83[/C][C]9.83643018968302[/C][C]9.83208333333333[/C][C]1.00044210938845[/C][C]0.999346288281519[/C][/ROW]
[ROW][C]19[/C][C]9.83[/C][C]9.79864373343162[/C][C]9.81[/C][C]0.998842378535333[/C][C]1.00320006190871[/C][/ROW]
[ROW][C]20[/C][C]9.82[/C][C]9.78908180073704[/C][C]9.79208333333333[/C][C]0.999693473544483[/C][C]1.00315843711314[/C][/ROW]
[ROW][C]21[/C][C]9.77[/C][C]9.75439763074003[/C][C]9.77708333333333[/C][C]0.997679706532115[/C][C]1.00159952155434[/C][/ROW]
[ROW][C]22[/C][C]9.66[/C][C]9.72609795509019[/C][C]9.76666666666667[/C][C]0.995846207005822[/C][C]0.993204062369575[/C][/ROW]
[ROW][C]23[/C][C]9.69[/C][C]9.74237836549001[/C][C]9.76125[/C][C]0.998066678498144[/C][C]0.994623657229784[/C][/ROW]
[ROW][C]24[/C][C]9.67[/C][C]9.7493764119257[/C][C]9.75708333333333[/C][C]0.999210120366472[/C][C]0.991858308821823[/C][/ROW]
[ROW][C]25[/C][C]9.7[/C][C]9.73617861902452[/C][C]9.7525[/C][C]0.998326441325252[/C][C]0.996284104838234[/C][/ROW]
[ROW][C]26[/C][C]9.77[/C][C]9.77789229621325[/C][C]9.74875[/C][C]1.00298933670607[/C][C]0.999192842795343[/C][/ROW]
[ROW][C]27[/C][C]9.79[/C][C]9.78962788645927[/C][C]9.7475[/C][C]1.00432191705148[/C][C]1.0000380109995[/C][/ROW]
[ROW][C]28[/C][C]9.81[/C][C]9.79227787060894[/C][C]9.75208333333333[/C][C]1.00412163595221[/C][C]1.00180980662776[/C][/ROW]
[ROW][C]29[/C][C]9.77[/C][C]9.76574012711304[/C][C]9.76125[/C][C]1.00045999509418[/C][C]1.00043620584119[/C][/ROW]
[ROW][C]30[/C][C]9.78[/C][C]9.77556996136189[/C][C]9.77125[/C][C]1.00044210938845[/C][C]1.00045317445997[/C][/ROW]
[ROW][C]31[/C][C]9.77[/C][C]9.76951083072434[/C][C]9.78083333333333[/C][C]0.998842378535333[/C][C]1.00005007101012[/C][/ROW]
[ROW][C]32[/C][C]9.79[/C][C]9.7832502554747[/C][C]9.78625[/C][C]0.999693473544483[/C][C]1.00068992863814[/C][/ROW]
[ROW][C]33[/C][C]9.77[/C][C]9.76354302804991[/C][C]9.78625[/C][C]0.997679706532115[/C][C]1.00066133492028[/C][/ROW]
[ROW][C]34[/C][C]9.77[/C][C]9.74311032779321[/C][C]9.78375[/C][C]0.995846207005822[/C][C]1.00275986531016[/C][/ROW]
[ROW][C]35[/C][C]9.8[/C][C]9.76358728240809[/C][C]9.7825[/C][C]0.998066678498144[/C][C]1.00372944047497[/C][/ROW]
[ROW][C]36[/C][C]9.8[/C][C]9.77518934003517[/C][C]9.78291666666667[/C][C]0.999210120366472[/C][C]1.00253812576941[/C][/ROW]
[ROW][C]37[/C][C]9.8[/C][C]9.76862422836759[/C][C]9.785[/C][C]0.998326441325252[/C][C]1.00321189257555[/C][/ROW]
[ROW][C]38[/C][C]9.8[/C][C]9.81717604523424[/C][C]9.78791666666667[/C][C]1.00298933670607[/C][C]0.998250408757559[/C][/ROW]
[ROW][C]39[/C][C]9.76[/C][C]9.83440390526114[/C][C]9.79208333333333[/C][C]1.00432191705148[/C][C]0.992434324847961[/C][/ROW]
[ROW][C]40[/C][C]9.78[/C][C]9.83955526430169[/C][C]9.79916666666666[/C][C]1.00412163595221[/C][C]0.993947362182338[/C][/ROW]
[ROW][C]41[/C][C]9.77[/C][C]9.81576312686774[/C][C]9.81125[/C][C]1.00045999509418[/C][C]0.995337792255553[/C][/ROW]
[ROW][C]42[/C][C]9.79[/C][C]9.83142797913608[/C][C]9.82708333333333[/C][C]1.00044210938845[/C][C]0.995786168680277[/C][/ROW]
[ROW][C]43[/C][C]9.81[/C][C]9.8315222950584[/C][C]9.84291666666666[/C][C]0.998842378535333[/C][C]0.997810888851951[/C][/ROW]
[ROW][C]44[/C][C]9.82[/C][C]9.85947688283246[/C][C]9.8625[/C][C]0.999693473544483[/C][C]0.995996046919974[/C][/ROW]
[ROW][C]45[/C][C]9.84[/C][C]9.86372669858084[/C][C]9.88666666666666[/C][C]0.997679706532115[/C][C]0.997594550284503[/C][/ROW]
[ROW][C]46[/C][C]9.87[/C][C]9.87049565510604[/C][C]9.91166666666667[/C][C]0.995846207005822[/C][C]0.999949784172613[/C][/ROW]
[ROW][C]47[/C][C]9.99[/C][C]9.91745589534322[/C][C]9.93666666666667[/C][C]0.998066678498144[/C][C]1.00731478974268[/C][/ROW]
[ROW][C]48[/C][C]9.99[/C][C]9.95171646129991[/C][C]9.95958333333333[/C][C]0.999210120366472[/C][C]1.00384692820067[/C][/ROW]
[ROW][C]49[/C][C]9.99[/C][C]9.96288191507546[/C][C]9.97958333333333[/C][C]0.998326441325252[/C][C]1.00272191170745[/C][/ROW]
[ROW][C]50[/C][C]10.08[/C][C]10.0315650159552[/C][C]10.0016666666667[/C][C]1.00298933670607[/C][C]1.0048282580004[/C][/ROW]
[ROW][C]51[/C][C]10.06[/C][C]10.0683272184411[/C][C]10.025[/C][C]1.00432191705148[/C][C]0.999172929299934[/C][/ROW]
[ROW][C]52[/C][C]10.08[/C][C]10.0872386011699[/C][C]10.0458333333333[/C][C]1.00412163595221[/C][C]0.999282400123949[/C][/ROW]
[ROW][C]53[/C][C]10.07[/C][C]10.0662949839726[/C][C]10.0616666666667[/C][C]1.00045999509418[/C][C]1.00036806153936[/C][/ROW]
[ROW][C]54[/C][C]10.04[/C][C]10.0790374012097[/C][C]10.0745833333333[/C][C]1.00044210938845[/C][C]0.996126872075597[/C][/ROW]
[ROW][C]55[/C][C]10.04[/C][C]10.076654862124[/C][C]10.0883333333333[/C][C]0.998842378535333[/C][C]0.996362397777289[/C][/ROW]
[ROW][C]56[/C][C]10.12[/C][C]10.0989867775358[/C][C]10.1020833333333[/C][C]0.999693473544483[/C][C]1.00208072581211[/C][/ROW]
[ROW][C]57[/C][C]10.1[/C][C]10.1002599290045[/C][C]10.12375[/C][C]0.997679706532115[/C][C]0.999974265117301[/C][/ROW]
[ROW][C]58[/C][C]10.11[/C][C]10.111988360305[/C][C]10.1541666666667[/C][C]0.995846207005822[/C][C]0.99980336604097[/C][/ROW]
[ROW][C]59[/C][C]10.13[/C][C]10.1665567038517[/C][C]10.18625[/C][C]0.998066678498144[/C][C]0.996404219745524[/C][/ROW]
[ROW][C]60[/C][C]10.16[/C][C]10.213592780346[/C][C]10.2216666666667[/C][C]0.999210120366472[/C][C]0.994752798403214[/C][/ROW]
[ROW][C]61[/C][C]10.15[/C][C]10.2428292879971[/C][C]10.26[/C][C]0.998326441325252[/C][C]0.990937143889934[/C][/ROW]
[ROW][C]62[/C][C]10.25[/C][C]10.3249393969417[/C][C]10.2941666666667[/C][C]1.00298933670607[/C][C]0.992741904425717[/C][/ROW]
[ROW][C]63[/C][C]10.41[/C][C]10.3704607284874[/C][C]10.3258333333333[/C][C]1.00432191705148[/C][C]1.00381268224699[/C][/ROW]
[ROW][C]64[/C][C]10.46[/C][C]10.4014449964199[/C][C]10.35875[/C][C]1.00412163595221[/C][C]1.00562950663107[/C][/ROW]
[ROW][C]65[/C][C]10.46[/C][C]10.3964467823537[/C][C]10.3916666666667[/C][C]1.00045999509418[/C][C]1.00611297484389[/C][/ROW]
[ROW][C]66[/C][C]10.5[/C][C]10.4283584377379[/C][C]10.42375[/C][C]1.00044210938845[/C][C]1.00686987915595[/C][/ROW]
[ROW][C]67[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.998842378535333[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]10.48[/C][C]NA[/C][C]NA[/C][C]0.999693473544483[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.997679706532115[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]10.5[/C][C]NA[/C][C]NA[/C][C]0.995846207005822[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]10.53[/C][C]NA[/C][C]NA[/C][C]0.998066678498144[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10.53[/C][C]NA[/C][C]NA[/C][C]0.999210120366472[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198024&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198024&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	10	NA	NA	0.998326441325252	NA
2	9.99	NA	NA	1.00298933670607	NA
3	9.95	NA	NA	1.00432191705148	NA
4	9.96	NA	NA	1.00412163595221	NA
5	9.97	NA	NA	1.00045999509418	NA
6	9.95	NA	NA	1.00044210938845	NA
7	9.94	9.92849324264121	9.94	0.998842378535333	1.00115896310523
8	9.9	9.93320427650637	9.93625	0.999693473544483	0.99665724416995
9	9.9	9.91236358427428	9.93541666666667	0.997679706532115	0.998752710776883
10	9.92	9.89165738700491	9.93291666666666	0.995846207005822	1.00286530475998
11	9.87	9.90456420074596	9.92375	0.998066678498144	0.996510275460342
12	9.96	9.90467031813265	9.9125	0.999210120366472	1.00558622145818
13	9.94	9.88634355457386	9.90291666666666	0.998326441325252	1.00542732964214
14	9.96	9.92457948670651	9.895	1.00298933670607	1.00356896867428
15	9.96	9.92897755245016	9.88625	1.00432191705148	1.00312443525891
16	9.89	9.9106805468483	9.87	1.00412163595221	0.997913307088192
17	9.82	9.8561983850028	9.85166666666667	1.00045999509418	0.99632734817332
18	9.83	9.83643018968302	9.83208333333333	1.00044210938845	0.999346288281519
19	9.83	9.79864373343162	9.81	0.998842378535333	1.00320006190871
20	9.82	9.78908180073704	9.79208333333333	0.999693473544483	1.00315843711314
21	9.77	9.75439763074003	9.77708333333333	0.997679706532115	1.00159952155434
22	9.66	9.72609795509019	9.76666666666667	0.995846207005822	0.993204062369575
23	9.69	9.74237836549001	9.76125	0.998066678498144	0.994623657229784
24	9.67	9.7493764119257	9.75708333333333	0.999210120366472	0.991858308821823
25	9.7	9.73617861902452	9.7525	0.998326441325252	0.996284104838234
26	9.77	9.77789229621325	9.74875	1.00298933670607	0.999192842795343
27	9.79	9.78962788645927	9.7475	1.00432191705148	1.0000380109995
28	9.81	9.79227787060894	9.75208333333333	1.00412163595221	1.00180980662776
29	9.77	9.76574012711304	9.76125	1.00045999509418	1.00043620584119
30	9.78	9.77556996136189	9.77125	1.00044210938845	1.00045317445997
31	9.77	9.76951083072434	9.78083333333333	0.998842378535333	1.00005007101012
32	9.79	9.7832502554747	9.78625	0.999693473544483	1.00068992863814
33	9.77	9.76354302804991	9.78625	0.997679706532115	1.00066133492028
34	9.77	9.74311032779321	9.78375	0.995846207005822	1.00275986531016
35	9.8	9.76358728240809	9.7825	0.998066678498144	1.00372944047497
36	9.8	9.77518934003517	9.78291666666667	0.999210120366472	1.00253812576941
37	9.8	9.76862422836759	9.785	0.998326441325252	1.00321189257555
38	9.8	9.81717604523424	9.78791666666667	1.00298933670607	0.998250408757559
39	9.76	9.83440390526114	9.79208333333333	1.00432191705148	0.992434324847961
40	9.78	9.83955526430169	9.79916666666666	1.00412163595221	0.993947362182338
41	9.77	9.81576312686774	9.81125	1.00045999509418	0.995337792255553
42	9.79	9.83142797913608	9.82708333333333	1.00044210938845	0.995786168680277
43	9.81	9.8315222950584	9.84291666666666	0.998842378535333	0.997810888851951
44	9.82	9.85947688283246	9.8625	0.999693473544483	0.995996046919974
45	9.84	9.86372669858084	9.88666666666666	0.997679706532115	0.997594550284503
46	9.87	9.87049565510604	9.91166666666667	0.995846207005822	0.999949784172613
47	9.99	9.91745589534322	9.93666666666667	0.998066678498144	1.00731478974268
48	9.99	9.95171646129991	9.95958333333333	0.999210120366472	1.00384692820067
49	9.99	9.96288191507546	9.97958333333333	0.998326441325252	1.00272191170745
50	10.08	10.0315650159552	10.0016666666667	1.00298933670607	1.0048282580004
51	10.06	10.0683272184411	10.025	1.00432191705148	0.999172929299934
52	10.08	10.0872386011699	10.0458333333333	1.00412163595221	0.999282400123949
53	10.07	10.0662949839726	10.0616666666667	1.00045999509418	1.00036806153936
54	10.04	10.0790374012097	10.0745833333333	1.00044210938845	0.996126872075597
55	10.04	10.076654862124	10.0883333333333	0.998842378535333	0.996362397777289
56	10.12	10.0989867775358	10.1020833333333	0.999693473544483	1.00208072581211
57	10.1	10.1002599290045	10.12375	0.997679706532115	0.999974265117301
58	10.11	10.111988360305	10.1541666666667	0.995846207005822	0.99980336604097
59	10.13	10.1665567038517	10.18625	0.998066678498144	0.996404219745524
60	10.16	10.213592780346	10.2216666666667	0.999210120366472	0.994752798403214
61	10.15	10.2428292879971	10.26	0.998326441325252	0.990937143889934
62	10.25	10.3249393969417	10.2941666666667	1.00298933670607	0.992741904425717
63	10.41	10.3704607284874	10.3258333333333	1.00432191705148	1.00381268224699
64	10.46	10.4014449964199	10.35875	1.00412163595221	1.00562950663107
65	10.46	10.3964467823537	10.3916666666667	1.00045999509418	1.00611297484389
66	10.5	10.4283584377379	10.42375	1.00044210938845	1.00686987915595
67	10.5	NA	NA	0.998842378535333	NA
68	10.48	NA	NA	0.999693473544483	NA
69	10.5	NA	NA	0.997679706532115	NA
70	10.5	NA	NA	0.995846207005822	NA
71	10.53	NA	NA	0.998066678498144	NA
72	10.53	NA	NA	0.999210120366472	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