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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 14 Dec 2011 10:30:32 -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/14/t1323876674btjfexwaotiscx7.htm/, Retrieved Sun, 17 May 2026 12:14:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155064, Retrieved Sun, 17 May 2026 12:14:13 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

410

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

-       [Classical Decomposition] [Gemiddelde consum...] [2011-12-14 15:30:32] [c0f35385ddfb9717cc41b82f2b64d087] [Current]

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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	'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155064&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155064&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155064&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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	49.98	NA	NA	1.00050675083072	NA
2	50.12	NA	NA	0.999167148698138	NA
3	50.37	NA	NA	0.99828377070355	NA
4	50.39	NA	NA	0.999328838370632	NA
5	50.34	NA	NA	1.00177908483889	NA
6	50.32	NA	NA	1.00061097657055	NA
7	50.32	50.4218589503163	50.515	0.998156170450683	0.997979865232326
8	50.32	50.4404035806955	50.5975	0.99689517428125	0.997612953661187
9	50.67	50.6177706244033	50.65875	0.999191070138986	1.00103183871894
10	50.86	50.7712780193041	50.7158333333333	1.00109324213617	1.0017474836986
11	50.95	50.9424734241913	50.7904166666667	1.00299380803514	1.00014774657183
12	51.02	50.9722679917383	50.8708333333333	1.0019939649453	1.00093643092886
13	51.02	50.9783202217021	50.9525	1.00050675083072	1.00081759811066
14	51.06	50.9916627945189	51.0341666666666	0.999167148698138	1.00134016428836
15	50.9	51.0202037628028	51.1079166666667	0.99828377070355	0.99764399681033
16	51.23	51.1319091762814	51.16625	0.999328838370632	1.0019183876624
17	51.29	51.316968436776	51.2258333333333	1.00177908483889	0.999474473305858
18	51.3	51.3246723582255	51.2933333333333	1.00061097657055	0.999519288539178
19	51.3	51.2653009143471	51.36	0.998156170450683	1.00067685325228
20	51.3	51.2661650833918	51.4258333333333	0.99689517428125	1.00065998532469
21	51.46	51.4583401121578	51.5	0.999191070138986	1.00003225692548
22	51.47	51.6276298635148	51.57125	1.00109324213617	0.996946792561822
23	51.77	51.7941823328478	51.6395833333333	1.00299380803514	0.999533107160716
24	51.82	51.8218753745148	51.71875	1.0019939649453	0.999963811141507
25	51.82	51.8258328152183	51.7995833333333	1.00050675083072	0.999887453516877
26	51.84	51.83762431375	51.8808333333333	0.999167148698138	1.00004582938129
27	51.9	51.8770639993234	51.96625	0.99828377070355	1.00044212218095
28	51.94	52.028390421703	52.0633333333333	0.999328838370632	0.998301111739445
29	52.22	52.2482055777241	52.1554166666667	1.00177908483889	0.99946016179097
30	52.27	52.2623282275202	52.2304166666667	1.00061097657055	1.00014679354594
31	52.27	52.2048154097838	52.30125	0.998156170450683	1.00124863175369
32	52.28	52.2078156500983	52.3704166666667	0.99689517428125	1.00138263493699
33	52.53	52.3946654108005	52.4370833333333	0.999191070138986	1.00258298412898
34	52.73	52.5603150674383	52.5029166666667	1.00109324213617	1.00322838499625
35	52.72	52.7190262066735	52.5616666666667	1.00299380803514	1.00001847138304
36	52.67	52.7157374907431	52.6108333333333	1.0019939649453	0.999132375018919
37	52.67	52.6841842318685	52.6575	1.00050675083072	0.999730768691301
38	52.65	52.6602719328448	52.7041666666667	0.999167148698138	0.999804939616379
39	52.69	52.6490701153341	52.7395833333333	0.99828377070355	1.00077740945047
40	52.73	52.7312517046904	52.7666666666667	0.999328838370632	0.99997626256442
41	52.84	52.9039534703416	52.81	1.00177908483889	0.998791140053882
42	52.83	52.9023023312851	52.87	1.00061097657055	0.99863328573429
43	52.83	52.8357332891895	52.9333333333333	0.998156170450683	0.999891488414514
44	52.84	52.8325366259813	52.9970833333333	0.99689517428125	1.00014126472994
45	52.82	53.024155784988	53.0670833333333	0.999191070138986	0.996149758879408
46	53.09	53.2031003533266	53.145	1.00109324213617	0.99787417739614
47	53.4	53.3947932848372	53.2354166666667	1.00299380803514	1.00009751353723
48	53.43	53.4426006128138	53.33625	1.0019939649453	0.999764221563522
49	53.43	53.4641626197036	53.4370833333333	1.00050675083072	0.99936101833397
50	53.42	53.4945765020078	53.5391666666667	0.999167148698138	0.998605905366781
51	53.6	53.5500212183941	53.6420833333333	0.99828377070355	1.00093331021107
52	53.69	53.7114267403256	53.7475	0.999328838370632	0.999601076686546
53	54.05	53.9382903754377	53.8425	1.00177908483889	1.0020710635021
54	54.04	53.9591976752877	53.92625	1.00061097657055	1.0014974708334
55	54.04	NA	NA	0.998156170450683	NA
56	54.08	NA	NA	0.99689517428125	NA
57	54.05	NA	NA	0.999191070138986	NA
58	54.39	NA	NA	1.00109324213617	NA
59	54.38	NA	NA	1.00299380803514	NA
60	54.46	NA	NA	1.0019939649453	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 49.98 & NA & NA & 1.00050675083072 & NA \tabularnewline
2 & 50.12 & NA & NA & 0.999167148698138 & NA \tabularnewline
3 & 50.37 & NA & NA & 0.99828377070355 & NA \tabularnewline
4 & 50.39 & NA & NA & 0.999328838370632 & NA \tabularnewline
5 & 50.34 & NA & NA & 1.00177908483889 & NA \tabularnewline
6 & 50.32 & NA & NA & 1.00061097657055 & NA \tabularnewline
7 & 50.32 & 50.4218589503163 & 50.515 & 0.998156170450683 & 0.997979865232326 \tabularnewline
8 & 50.32 & 50.4404035806955 & 50.5975 & 0.99689517428125 & 0.997612953661187 \tabularnewline
9 & 50.67 & 50.6177706244033 & 50.65875 & 0.999191070138986 & 1.00103183871894 \tabularnewline
10 & 50.86 & 50.7712780193041 & 50.7158333333333 & 1.00109324213617 & 1.0017474836986 \tabularnewline
11 & 50.95 & 50.9424734241913 & 50.7904166666667 & 1.00299380803514 & 1.00014774657183 \tabularnewline
12 & 51.02 & 50.9722679917383 & 50.8708333333333 & 1.0019939649453 & 1.00093643092886 \tabularnewline
13 & 51.02 & 50.9783202217021 & 50.9525 & 1.00050675083072 & 1.00081759811066 \tabularnewline
14 & 51.06 & 50.9916627945189 & 51.0341666666666 & 0.999167148698138 & 1.00134016428836 \tabularnewline
15 & 50.9 & 51.0202037628028 & 51.1079166666667 & 0.99828377070355 & 0.99764399681033 \tabularnewline
16 & 51.23 & 51.1319091762814 & 51.16625 & 0.999328838370632 & 1.0019183876624 \tabularnewline
17 & 51.29 & 51.316968436776 & 51.2258333333333 & 1.00177908483889 & 0.999474473305858 \tabularnewline
18 & 51.3 & 51.3246723582255 & 51.2933333333333 & 1.00061097657055 & 0.999519288539178 \tabularnewline
19 & 51.3 & 51.2653009143471 & 51.36 & 0.998156170450683 & 1.00067685325228 \tabularnewline
20 & 51.3 & 51.2661650833918 & 51.4258333333333 & 0.99689517428125 & 1.00065998532469 \tabularnewline
21 & 51.46 & 51.4583401121578 & 51.5 & 0.999191070138986 & 1.00003225692548 \tabularnewline
22 & 51.47 & 51.6276298635148 & 51.57125 & 1.00109324213617 & 0.996946792561822 \tabularnewline
23 & 51.77 & 51.7941823328478 & 51.6395833333333 & 1.00299380803514 & 0.999533107160716 \tabularnewline
24 & 51.82 & 51.8218753745148 & 51.71875 & 1.0019939649453 & 0.999963811141507 \tabularnewline
25 & 51.82 & 51.8258328152183 & 51.7995833333333 & 1.00050675083072 & 0.999887453516877 \tabularnewline
26 & 51.84 & 51.83762431375 & 51.8808333333333 & 0.999167148698138 & 1.00004582938129 \tabularnewline
27 & 51.9 & 51.8770639993234 & 51.96625 & 0.99828377070355 & 1.00044212218095 \tabularnewline
28 & 51.94 & 52.028390421703 & 52.0633333333333 & 0.999328838370632 & 0.998301111739445 \tabularnewline
29 & 52.22 & 52.2482055777241 & 52.1554166666667 & 1.00177908483889 & 0.99946016179097 \tabularnewline
30 & 52.27 & 52.2623282275202 & 52.2304166666667 & 1.00061097657055 & 1.00014679354594 \tabularnewline
31 & 52.27 & 52.2048154097838 & 52.30125 & 0.998156170450683 & 1.00124863175369 \tabularnewline
32 & 52.28 & 52.2078156500983 & 52.3704166666667 & 0.99689517428125 & 1.00138263493699 \tabularnewline
33 & 52.53 & 52.3946654108005 & 52.4370833333333 & 0.999191070138986 & 1.00258298412898 \tabularnewline
34 & 52.73 & 52.5603150674383 & 52.5029166666667 & 1.00109324213617 & 1.00322838499625 \tabularnewline
35 & 52.72 & 52.7190262066735 & 52.5616666666667 & 1.00299380803514 & 1.00001847138304 \tabularnewline
36 & 52.67 & 52.7157374907431 & 52.6108333333333 & 1.0019939649453 & 0.999132375018919 \tabularnewline
37 & 52.67 & 52.6841842318685 & 52.6575 & 1.00050675083072 & 0.999730768691301 \tabularnewline
38 & 52.65 & 52.6602719328448 & 52.7041666666667 & 0.999167148698138 & 0.999804939616379 \tabularnewline
39 & 52.69 & 52.6490701153341 & 52.7395833333333 & 0.99828377070355 & 1.00077740945047 \tabularnewline
40 & 52.73 & 52.7312517046904 & 52.7666666666667 & 0.999328838370632 & 0.99997626256442 \tabularnewline
41 & 52.84 & 52.9039534703416 & 52.81 & 1.00177908483889 & 0.998791140053882 \tabularnewline
42 & 52.83 & 52.9023023312851 & 52.87 & 1.00061097657055 & 0.99863328573429 \tabularnewline
43 & 52.83 & 52.8357332891895 & 52.9333333333333 & 0.998156170450683 & 0.999891488414514 \tabularnewline
44 & 52.84 & 52.8325366259813 & 52.9970833333333 & 0.99689517428125 & 1.00014126472994 \tabularnewline
45 & 52.82 & 53.024155784988 & 53.0670833333333 & 0.999191070138986 & 0.996149758879408 \tabularnewline
46 & 53.09 & 53.2031003533266 & 53.145 & 1.00109324213617 & 0.99787417739614 \tabularnewline
47 & 53.4 & 53.3947932848372 & 53.2354166666667 & 1.00299380803514 & 1.00009751353723 \tabularnewline
48 & 53.43 & 53.4426006128138 & 53.33625 & 1.0019939649453 & 0.999764221563522 \tabularnewline
49 & 53.43 & 53.4641626197036 & 53.4370833333333 & 1.00050675083072 & 0.99936101833397 \tabularnewline
50 & 53.42 & 53.4945765020078 & 53.5391666666667 & 0.999167148698138 & 0.998605905366781 \tabularnewline
51 & 53.6 & 53.5500212183941 & 53.6420833333333 & 0.99828377070355 & 1.00093331021107 \tabularnewline
52 & 53.69 & 53.7114267403256 & 53.7475 & 0.999328838370632 & 0.999601076686546 \tabularnewline
53 & 54.05 & 53.9382903754377 & 53.8425 & 1.00177908483889 & 1.0020710635021 \tabularnewline
54 & 54.04 & 53.9591976752877 & 53.92625 & 1.00061097657055 & 1.0014974708334 \tabularnewline
55 & 54.04 & NA & NA & 0.998156170450683 & NA \tabularnewline
56 & 54.08 & NA & NA & 0.99689517428125 & NA \tabularnewline
57 & 54.05 & NA & NA & 0.999191070138986 & NA \tabularnewline
58 & 54.39 & NA & NA & 1.00109324213617 & NA \tabularnewline
59 & 54.38 & NA & NA & 1.00299380803514 & NA \tabularnewline
60 & 54.46 & NA & NA & 1.0019939649453 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155064&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]49.98[/C][C]NA[/C][C]NA[/C][C]1.00050675083072[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]50.12[/C][C]NA[/C][C]NA[/C][C]0.999167148698138[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]50.37[/C][C]NA[/C][C]NA[/C][C]0.99828377070355[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]50.39[/C][C]NA[/C][C]NA[/C][C]0.999328838370632[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]50.34[/C][C]NA[/C][C]NA[/C][C]1.00177908483889[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]50.32[/C][C]NA[/C][C]NA[/C][C]1.00061097657055[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]50.32[/C][C]50.4218589503163[/C][C]50.515[/C][C]0.998156170450683[/C][C]0.997979865232326[/C][/ROW]
[ROW][C]8[/C][C]50.32[/C][C]50.4404035806955[/C][C]50.5975[/C][C]0.99689517428125[/C][C]0.997612953661187[/C][/ROW]
[ROW][C]9[/C][C]50.67[/C][C]50.6177706244033[/C][C]50.65875[/C][C]0.999191070138986[/C][C]1.00103183871894[/C][/ROW]
[ROW][C]10[/C][C]50.86[/C][C]50.7712780193041[/C][C]50.7158333333333[/C][C]1.00109324213617[/C][C]1.0017474836986[/C][/ROW]
[ROW][C]11[/C][C]50.95[/C][C]50.9424734241913[/C][C]50.7904166666667[/C][C]1.00299380803514[/C][C]1.00014774657183[/C][/ROW]
[ROW][C]12[/C][C]51.02[/C][C]50.9722679917383[/C][C]50.8708333333333[/C][C]1.0019939649453[/C][C]1.00093643092886[/C][/ROW]
[ROW][C]13[/C][C]51.02[/C][C]50.9783202217021[/C][C]50.9525[/C][C]1.00050675083072[/C][C]1.00081759811066[/C][/ROW]
[ROW][C]14[/C][C]51.06[/C][C]50.9916627945189[/C][C]51.0341666666666[/C][C]0.999167148698138[/C][C]1.00134016428836[/C][/ROW]
[ROW][C]15[/C][C]50.9[/C][C]51.0202037628028[/C][C]51.1079166666667[/C][C]0.99828377070355[/C][C]0.99764399681033[/C][/ROW]
[ROW][C]16[/C][C]51.23[/C][C]51.1319091762814[/C][C]51.16625[/C][C]0.999328838370632[/C][C]1.0019183876624[/C][/ROW]
[ROW][C]17[/C][C]51.29[/C][C]51.316968436776[/C][C]51.2258333333333[/C][C]1.00177908483889[/C][C]0.999474473305858[/C][/ROW]
[ROW][C]18[/C][C]51.3[/C][C]51.3246723582255[/C][C]51.2933333333333[/C][C]1.00061097657055[/C][C]0.999519288539178[/C][/ROW]
[ROW][C]19[/C][C]51.3[/C][C]51.2653009143471[/C][C]51.36[/C][C]0.998156170450683[/C][C]1.00067685325228[/C][/ROW]
[ROW][C]20[/C][C]51.3[/C][C]51.2661650833918[/C][C]51.4258333333333[/C][C]0.99689517428125[/C][C]1.00065998532469[/C][/ROW]
[ROW][C]21[/C][C]51.46[/C][C]51.4583401121578[/C][C]51.5[/C][C]0.999191070138986[/C][C]1.00003225692548[/C][/ROW]
[ROW][C]22[/C][C]51.47[/C][C]51.6276298635148[/C][C]51.57125[/C][C]1.00109324213617[/C][C]0.996946792561822[/C][/ROW]
[ROW][C]23[/C][C]51.77[/C][C]51.7941823328478[/C][C]51.6395833333333[/C][C]1.00299380803514[/C][C]0.999533107160716[/C][/ROW]
[ROW][C]24[/C][C]51.82[/C][C]51.8218753745148[/C][C]51.71875[/C][C]1.0019939649453[/C][C]0.999963811141507[/C][/ROW]
[ROW][C]25[/C][C]51.82[/C][C]51.8258328152183[/C][C]51.7995833333333[/C][C]1.00050675083072[/C][C]0.999887453516877[/C][/ROW]
[ROW][C]26[/C][C]51.84[/C][C]51.83762431375[/C][C]51.8808333333333[/C][C]0.999167148698138[/C][C]1.00004582938129[/C][/ROW]
[ROW][C]27[/C][C]51.9[/C][C]51.8770639993234[/C][C]51.96625[/C][C]0.99828377070355[/C][C]1.00044212218095[/C][/ROW]
[ROW][C]28[/C][C]51.94[/C][C]52.028390421703[/C][C]52.0633333333333[/C][C]0.999328838370632[/C][C]0.998301111739445[/C][/ROW]
[ROW][C]29[/C][C]52.22[/C][C]52.2482055777241[/C][C]52.1554166666667[/C][C]1.00177908483889[/C][C]0.99946016179097[/C][/ROW]
[ROW][C]30[/C][C]52.27[/C][C]52.2623282275202[/C][C]52.2304166666667[/C][C]1.00061097657055[/C][C]1.00014679354594[/C][/ROW]
[ROW][C]31[/C][C]52.27[/C][C]52.2048154097838[/C][C]52.30125[/C][C]0.998156170450683[/C][C]1.00124863175369[/C][/ROW]
[ROW][C]32[/C][C]52.28[/C][C]52.2078156500983[/C][C]52.3704166666667[/C][C]0.99689517428125[/C][C]1.00138263493699[/C][/ROW]
[ROW][C]33[/C][C]52.53[/C][C]52.3946654108005[/C][C]52.4370833333333[/C][C]0.999191070138986[/C][C]1.00258298412898[/C][/ROW]
[ROW][C]34[/C][C]52.73[/C][C]52.5603150674383[/C][C]52.5029166666667[/C][C]1.00109324213617[/C][C]1.00322838499625[/C][/ROW]
[ROW][C]35[/C][C]52.72[/C][C]52.7190262066735[/C][C]52.5616666666667[/C][C]1.00299380803514[/C][C]1.00001847138304[/C][/ROW]
[ROW][C]36[/C][C]52.67[/C][C]52.7157374907431[/C][C]52.6108333333333[/C][C]1.0019939649453[/C][C]0.999132375018919[/C][/ROW]
[ROW][C]37[/C][C]52.67[/C][C]52.6841842318685[/C][C]52.6575[/C][C]1.00050675083072[/C][C]0.999730768691301[/C][/ROW]
[ROW][C]38[/C][C]52.65[/C][C]52.6602719328448[/C][C]52.7041666666667[/C][C]0.999167148698138[/C][C]0.999804939616379[/C][/ROW]
[ROW][C]39[/C][C]52.69[/C][C]52.6490701153341[/C][C]52.7395833333333[/C][C]0.99828377070355[/C][C]1.00077740945047[/C][/ROW]
[ROW][C]40[/C][C]52.73[/C][C]52.7312517046904[/C][C]52.7666666666667[/C][C]0.999328838370632[/C][C]0.99997626256442[/C][/ROW]
[ROW][C]41[/C][C]52.84[/C][C]52.9039534703416[/C][C]52.81[/C][C]1.00177908483889[/C][C]0.998791140053882[/C][/ROW]
[ROW][C]42[/C][C]52.83[/C][C]52.9023023312851[/C][C]52.87[/C][C]1.00061097657055[/C][C]0.99863328573429[/C][/ROW]
[ROW][C]43[/C][C]52.83[/C][C]52.8357332891895[/C][C]52.9333333333333[/C][C]0.998156170450683[/C][C]0.999891488414514[/C][/ROW]
[ROW][C]44[/C][C]52.84[/C][C]52.8325366259813[/C][C]52.9970833333333[/C][C]0.99689517428125[/C][C]1.00014126472994[/C][/ROW]
[ROW][C]45[/C][C]52.82[/C][C]53.024155784988[/C][C]53.0670833333333[/C][C]0.999191070138986[/C][C]0.996149758879408[/C][/ROW]
[ROW][C]46[/C][C]53.09[/C][C]53.2031003533266[/C][C]53.145[/C][C]1.00109324213617[/C][C]0.99787417739614[/C][/ROW]
[ROW][C]47[/C][C]53.4[/C][C]53.3947932848372[/C][C]53.2354166666667[/C][C]1.00299380803514[/C][C]1.00009751353723[/C][/ROW]
[ROW][C]48[/C][C]53.43[/C][C]53.4426006128138[/C][C]53.33625[/C][C]1.0019939649453[/C][C]0.999764221563522[/C][/ROW]
[ROW][C]49[/C][C]53.43[/C][C]53.4641626197036[/C][C]53.4370833333333[/C][C]1.00050675083072[/C][C]0.99936101833397[/C][/ROW]
[ROW][C]50[/C][C]53.42[/C][C]53.4945765020078[/C][C]53.5391666666667[/C][C]0.999167148698138[/C][C]0.998605905366781[/C][/ROW]
[ROW][C]51[/C][C]53.6[/C][C]53.5500212183941[/C][C]53.6420833333333[/C][C]0.99828377070355[/C][C]1.00093331021107[/C][/ROW]
[ROW][C]52[/C][C]53.69[/C][C]53.7114267403256[/C][C]53.7475[/C][C]0.999328838370632[/C][C]0.999601076686546[/C][/ROW]
[ROW][C]53[/C][C]54.05[/C][C]53.9382903754377[/C][C]53.8425[/C][C]1.00177908483889[/C][C]1.0020710635021[/C][/ROW]
[ROW][C]54[/C][C]54.04[/C][C]53.9591976752877[/C][C]53.92625[/C][C]1.00061097657055[/C][C]1.0014974708334[/C][/ROW]
[ROW][C]55[/C][C]54.04[/C][C]NA[/C][C]NA[/C][C]0.998156170450683[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]54.08[/C][C]NA[/C][C]NA[/C][C]0.99689517428125[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]54.05[/C][C]NA[/C][C]NA[/C][C]0.999191070138986[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]54.39[/C][C]NA[/C][C]NA[/C][C]1.00109324213617[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]54.38[/C][C]NA[/C][C]NA[/C][C]1.00299380803514[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]54.46[/C][C]NA[/C][C]NA[/C][C]1.0019939649453[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155064&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155064&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	49.98	NA	NA	1.00050675083072	NA
2	50.12	NA	NA	0.999167148698138	NA
3	50.37	NA	NA	0.99828377070355	NA
4	50.39	NA	NA	0.999328838370632	NA
5	50.34	NA	NA	1.00177908483889	NA
6	50.32	NA	NA	1.00061097657055	NA
7	50.32	50.4218589503163	50.515	0.998156170450683	0.997979865232326
8	50.32	50.4404035806955	50.5975	0.99689517428125	0.997612953661187
9	50.67	50.6177706244033	50.65875	0.999191070138986	1.00103183871894
10	50.86	50.7712780193041	50.7158333333333	1.00109324213617	1.0017474836986
11	50.95	50.9424734241913	50.7904166666667	1.00299380803514	1.00014774657183
12	51.02	50.9722679917383	50.8708333333333	1.0019939649453	1.00093643092886
13	51.02	50.9783202217021	50.9525	1.00050675083072	1.00081759811066
14	51.06	50.9916627945189	51.0341666666666	0.999167148698138	1.00134016428836
15	50.9	51.0202037628028	51.1079166666667	0.99828377070355	0.99764399681033
16	51.23	51.1319091762814	51.16625	0.999328838370632	1.0019183876624
17	51.29	51.316968436776	51.2258333333333	1.00177908483889	0.999474473305858
18	51.3	51.3246723582255	51.2933333333333	1.00061097657055	0.999519288539178
19	51.3	51.2653009143471	51.36	0.998156170450683	1.00067685325228
20	51.3	51.2661650833918	51.4258333333333	0.99689517428125	1.00065998532469
21	51.46	51.4583401121578	51.5	0.999191070138986	1.00003225692548
22	51.47	51.6276298635148	51.57125	1.00109324213617	0.996946792561822
23	51.77	51.7941823328478	51.6395833333333	1.00299380803514	0.999533107160716
24	51.82	51.8218753745148	51.71875	1.0019939649453	0.999963811141507
25	51.82	51.8258328152183	51.7995833333333	1.00050675083072	0.999887453516877
26	51.84	51.83762431375	51.8808333333333	0.999167148698138	1.00004582938129
27	51.9	51.8770639993234	51.96625	0.99828377070355	1.00044212218095
28	51.94	52.028390421703	52.0633333333333	0.999328838370632	0.998301111739445
29	52.22	52.2482055777241	52.1554166666667	1.00177908483889	0.99946016179097
30	52.27	52.2623282275202	52.2304166666667	1.00061097657055	1.00014679354594
31	52.27	52.2048154097838	52.30125	0.998156170450683	1.00124863175369
32	52.28	52.2078156500983	52.3704166666667	0.99689517428125	1.00138263493699
33	52.53	52.3946654108005	52.4370833333333	0.999191070138986	1.00258298412898
34	52.73	52.5603150674383	52.5029166666667	1.00109324213617	1.00322838499625
35	52.72	52.7190262066735	52.5616666666667	1.00299380803514	1.00001847138304
36	52.67	52.7157374907431	52.6108333333333	1.0019939649453	0.999132375018919
37	52.67	52.6841842318685	52.6575	1.00050675083072	0.999730768691301
38	52.65	52.6602719328448	52.7041666666667	0.999167148698138	0.999804939616379
39	52.69	52.6490701153341	52.7395833333333	0.99828377070355	1.00077740945047
40	52.73	52.7312517046904	52.7666666666667	0.999328838370632	0.99997626256442
41	52.84	52.9039534703416	52.81	1.00177908483889	0.998791140053882
42	52.83	52.9023023312851	52.87	1.00061097657055	0.99863328573429
43	52.83	52.8357332891895	52.9333333333333	0.998156170450683	0.999891488414514
44	52.84	52.8325366259813	52.9970833333333	0.99689517428125	1.00014126472994
45	52.82	53.024155784988	53.0670833333333	0.999191070138986	0.996149758879408
46	53.09	53.2031003533266	53.145	1.00109324213617	0.99787417739614
47	53.4	53.3947932848372	53.2354166666667	1.00299380803514	1.00009751353723
48	53.43	53.4426006128138	53.33625	1.0019939649453	0.999764221563522
49	53.43	53.4641626197036	53.4370833333333	1.00050675083072	0.99936101833397
50	53.42	53.4945765020078	53.5391666666667	0.999167148698138	0.998605905366781
51	53.6	53.5500212183941	53.6420833333333	0.99828377070355	1.00093331021107
52	53.69	53.7114267403256	53.7475	0.999328838370632	0.999601076686546
53	54.05	53.9382903754377	53.8425	1.00177908483889	1.0020710635021
54	54.04	53.9591976752877	53.92625	1.00061097657055	1.0014974708334
55	54.04	NA	NA	0.998156170450683	NA
56	54.08	NA	NA	0.99689517428125	NA
57	54.05	NA	NA	0.999191070138986	NA
58	54.39	NA	NA	1.00109324213617	NA
59	54.38	NA	NA	1.00299380803514	NA
60	54.46	NA	NA	1.0019939649453	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