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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 27 May 2012 12:11:16 -0400

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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/May/27/t1338135088x7sa3iydzbd6y0z.htm/, Retrieved Thu, 09 May 2024 00:20:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=167722, Retrieved Thu, 09 May 2024 00:20:02 +0000

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Estimated Impact

113

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

-       [Classical Decomposition] [] [2012-05-27 16:11:16] [d41d8cd98f00b204e9800998ecf8427e] [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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167722&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167722&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167722&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	100.17	NA	NA	0.998575110192315	NA
2	102.01	NA	NA	1.01706720849642	NA
3	100.3	NA	NA	1.00417205770226	NA
4	99.94	NA	NA	0.99198650168014	NA
5	100.16	NA	NA	0.999676871368877	NA
6	100.18	NA	NA	0.999804863620916	NA
7	99.98	100.16989800986	100.367916666667	0.998027072162269	0.998104240758624
8	100.04	100.038042055457	100.42375	0.996159195961683	1.00001957199984
9	100.05	100.33769266076	100.492083333333	0.998463653379925	0.99713275586541
10	100.11	100.334525060051	100.546666666667	0.997890117955684	0.997762235283254
11	100.11	100.249906428898	100.588333333333	0.996635525281909	0.998604423346793
12	101.03	100.799759385984	100.644583333333	1.00154182219759	1.00228413852789
13	100.84	100.581894047084	100.725416666667	0.998575110192315	1.00256612738666
14	102.68	102.54198729462	100.82125	1.01706720849642	1.00134591408867
15	101.27	101.334767987952	100.91375	1.00417205770226	0.999360851273084
16	100.28	100.203863156383	101.013333333333	0.99198650168014	1.00075981944427
17	100.82	101.081077252375	101.11375	0.999676871368877	0.997417150079209
18	100.87	101.200248295709	101.22	0.999804863620916	0.996736684926463
19	101.23	101.112201903826	101.312083333333	0.998027072162269	1.00116502354766
20	101.09	101.002656210213	101.392083333333	0.996159195961683	1.00086476725528
21	101.22	101.352381348507	101.508333333333	0.998463653379925	0.998693850635319
22	101.33	101.387299134494	101.601666666667	0.997890117955684	0.999434848990128
23	101.3	101.339146005071	101.68125	0.996635525281909	0.999613712897589
24	102.39	101.961965208826	101.805	1.00154182219759	1.00419798490837
25	101.69	101.778103814501	101.923333333333	0.998575110192315	0.999134353940589
26	103.75	103.771791060894	102.030416666667	1.01706720849642	0.999790009783285
27	102.99	102.584962199791	102.15875	1.00417205770226	1.00394831553791
28	100.8	101.490138986895	102.31	0.99198650168014	0.993199940469248
29	102.21	102.439804733377	102.472916666667	0.999676871368877	0.997756685167693
30	102.45	102.623720470289	102.64375	0.999804863620916	0.998307209390838
31	102.49	102.598430552121	102.80125	0.998027072162269	0.998943155840319
32	102.4	102.563720683552	102.959166666667	0.996159195961683	0.998403717391877
33	102.99	102.939106504337	103.0975	0.998463653379925	1.00049440389946
34	103.19	103.056270356775	103.274166666667	0.997890117955684	1.00129763713321
35	103.35	103.146793689051	103.495	0.996635525281909	1.0019700690994
36	104.44	103.85821772552	103.698333333333	1.00154182219759	1.00560169707531
37	103.42	103.754450386757	103.9025	0.998575110192315	0.996776520086509
38	105.81	105.866101954389	104.089583333333	1.01706720849642	0.999470066873592
39	104.25	104.704602051591	104.269583333333	1.00417205770226	0.995658241923626
40	103.78	103.601003596929	104.437916666667	0.99198650168014	1.00172774777132
41	104.53	104.559119700679	104.592916666667	0.999676871368877	0.999721500135403
42	105.01	104.709146781659	104.729583333333	0.999804863620916	1.00287322767483
43	104.83	104.665178280724	104.872083333333	0.998027072162269	1.00157475219537
44	104.55	104.638222209142	105.041666666667	0.996159195961683	0.999156883524211
45	105.16	105.042120574268	105.20375	0.998463653379925	1.00112221102437
46	105.06	105.12855550173	105.350833333333	0.997890117955684	0.999347888864235
47	105.2	105.158336390912	105.513333333333	0.996635525281909	1.00039619882282
48	105.87	105.822491624305	105.659583333333	1.00154182219759	1.00044894402849
49	105.41	105.617625113191	105.768333333333	0.998575110192315	0.99803418119875
50	107.89	107.695551595672	105.888333333333	1.01706720849642	1.00180553793956
51	106.06	106.45771910233	106.015416666667	1.00417205770226	0.996264065154851
52	105.5	105.290687271457	106.14125	0.99198650168014	1.00198795101416
53	106.71	106.216917179032	106.25125	0.999676871368877	1.00464222493048
54	106.34	106.263426759229	106.284166666667	0.999804863620916	1.00072059826326
55	106.11	106.132693921416	106.3425	0.998027072162269	0.999786174075324
56	106.15	106.030354685498	106.439166666667	0.996159195961683	1.00112840624609
57	106.61	106.383390081975	106.547083333333	0.998463653379925	1.00213012499273
58	106.63	106.445770457431	106.670833333333	0.997890117955684	1.00173073614646
59	106.27	106.377553850173	106.736666666667	0.996635525281909	0.998988942250686
60	105.59	106.976351265295	106.811666666667	1.00154182219759	0.98704058187723
61	107.09	106.763073979174	106.915416666667	0.998575110192315	1.00306216380478
62	108.53	108.838904649224	107.0125	1.01706720849642	0.997161817732186
63	108.01	107.543061734696	107.09625	1.00417205770226	1.00434187252782
64	106.52	106.318219956114	107.177083333333	0.99198650168014	1.0018978877183
65	107.27	107.26616136194	107.300833333333	0.999676871368877	1.0000357861045
66	107.58	107.479439424608	107.500416666667	0.999804863620916	1.0009356261619
67	107.36	NA	NA	0.998027072162269	NA
68	107.23	NA	NA	0.996159195961683	NA
69	107.54	NA	NA	0.998463653379925	NA
70	107.64	NA	NA	0.997890117955684	NA
71	108.23	NA	NA	0.996635525281909	NA
72	108.42	NA	NA	1.00154182219759	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 100.17 & NA & NA & 0.998575110192315 & NA \tabularnewline
2 & 102.01 & NA & NA & 1.01706720849642 & NA \tabularnewline
3 & 100.3 & NA & NA & 1.00417205770226 & NA \tabularnewline
4 & 99.94 & NA & NA & 0.99198650168014 & NA \tabularnewline
5 & 100.16 & NA & NA & 0.999676871368877 & NA \tabularnewline
6 & 100.18 & NA & NA & 0.999804863620916 & NA \tabularnewline
7 & 99.98 & 100.16989800986 & 100.367916666667 & 0.998027072162269 & 0.998104240758624 \tabularnewline
8 & 100.04 & 100.038042055457 & 100.42375 & 0.996159195961683 & 1.00001957199984 \tabularnewline
9 & 100.05 & 100.33769266076 & 100.492083333333 & 0.998463653379925 & 0.99713275586541 \tabularnewline
10 & 100.11 & 100.334525060051 & 100.546666666667 & 0.997890117955684 & 0.997762235283254 \tabularnewline
11 & 100.11 & 100.249906428898 & 100.588333333333 & 0.996635525281909 & 0.998604423346793 \tabularnewline
12 & 101.03 & 100.799759385984 & 100.644583333333 & 1.00154182219759 & 1.00228413852789 \tabularnewline
13 & 100.84 & 100.581894047084 & 100.725416666667 & 0.998575110192315 & 1.00256612738666 \tabularnewline
14 & 102.68 & 102.54198729462 & 100.82125 & 1.01706720849642 & 1.00134591408867 \tabularnewline
15 & 101.27 & 101.334767987952 & 100.91375 & 1.00417205770226 & 0.999360851273084 \tabularnewline
16 & 100.28 & 100.203863156383 & 101.013333333333 & 0.99198650168014 & 1.00075981944427 \tabularnewline
17 & 100.82 & 101.081077252375 & 101.11375 & 0.999676871368877 & 0.997417150079209 \tabularnewline
18 & 100.87 & 101.200248295709 & 101.22 & 0.999804863620916 & 0.996736684926463 \tabularnewline
19 & 101.23 & 101.112201903826 & 101.312083333333 & 0.998027072162269 & 1.00116502354766 \tabularnewline
20 & 101.09 & 101.002656210213 & 101.392083333333 & 0.996159195961683 & 1.00086476725528 \tabularnewline
21 & 101.22 & 101.352381348507 & 101.508333333333 & 0.998463653379925 & 0.998693850635319 \tabularnewline
22 & 101.33 & 101.387299134494 & 101.601666666667 & 0.997890117955684 & 0.999434848990128 \tabularnewline
23 & 101.3 & 101.339146005071 & 101.68125 & 0.996635525281909 & 0.999613712897589 \tabularnewline
24 & 102.39 & 101.961965208826 & 101.805 & 1.00154182219759 & 1.00419798490837 \tabularnewline
25 & 101.69 & 101.778103814501 & 101.923333333333 & 0.998575110192315 & 0.999134353940589 \tabularnewline
26 & 103.75 & 103.771791060894 & 102.030416666667 & 1.01706720849642 & 0.999790009783285 \tabularnewline
27 & 102.99 & 102.584962199791 & 102.15875 & 1.00417205770226 & 1.00394831553791 \tabularnewline
28 & 100.8 & 101.490138986895 & 102.31 & 0.99198650168014 & 0.993199940469248 \tabularnewline
29 & 102.21 & 102.439804733377 & 102.472916666667 & 0.999676871368877 & 0.997756685167693 \tabularnewline
30 & 102.45 & 102.623720470289 & 102.64375 & 0.999804863620916 & 0.998307209390838 \tabularnewline
31 & 102.49 & 102.598430552121 & 102.80125 & 0.998027072162269 & 0.998943155840319 \tabularnewline
32 & 102.4 & 102.563720683552 & 102.959166666667 & 0.996159195961683 & 0.998403717391877 \tabularnewline
33 & 102.99 & 102.939106504337 & 103.0975 & 0.998463653379925 & 1.00049440389946 \tabularnewline
34 & 103.19 & 103.056270356775 & 103.274166666667 & 0.997890117955684 & 1.00129763713321 \tabularnewline
35 & 103.35 & 103.146793689051 & 103.495 & 0.996635525281909 & 1.0019700690994 \tabularnewline
36 & 104.44 & 103.85821772552 & 103.698333333333 & 1.00154182219759 & 1.00560169707531 \tabularnewline
37 & 103.42 & 103.754450386757 & 103.9025 & 0.998575110192315 & 0.996776520086509 \tabularnewline
38 & 105.81 & 105.866101954389 & 104.089583333333 & 1.01706720849642 & 0.999470066873592 \tabularnewline
39 & 104.25 & 104.704602051591 & 104.269583333333 & 1.00417205770226 & 0.995658241923626 \tabularnewline
40 & 103.78 & 103.601003596929 & 104.437916666667 & 0.99198650168014 & 1.00172774777132 \tabularnewline
41 & 104.53 & 104.559119700679 & 104.592916666667 & 0.999676871368877 & 0.999721500135403 \tabularnewline
42 & 105.01 & 104.709146781659 & 104.729583333333 & 0.999804863620916 & 1.00287322767483 \tabularnewline
43 & 104.83 & 104.665178280724 & 104.872083333333 & 0.998027072162269 & 1.00157475219537 \tabularnewline
44 & 104.55 & 104.638222209142 & 105.041666666667 & 0.996159195961683 & 0.999156883524211 \tabularnewline
45 & 105.16 & 105.042120574268 & 105.20375 & 0.998463653379925 & 1.00112221102437 \tabularnewline
46 & 105.06 & 105.12855550173 & 105.350833333333 & 0.997890117955684 & 0.999347888864235 \tabularnewline
47 & 105.2 & 105.158336390912 & 105.513333333333 & 0.996635525281909 & 1.00039619882282 \tabularnewline
48 & 105.87 & 105.822491624305 & 105.659583333333 & 1.00154182219759 & 1.00044894402849 \tabularnewline
49 & 105.41 & 105.617625113191 & 105.768333333333 & 0.998575110192315 & 0.99803418119875 \tabularnewline
50 & 107.89 & 107.695551595672 & 105.888333333333 & 1.01706720849642 & 1.00180553793956 \tabularnewline
51 & 106.06 & 106.45771910233 & 106.015416666667 & 1.00417205770226 & 0.996264065154851 \tabularnewline
52 & 105.5 & 105.290687271457 & 106.14125 & 0.99198650168014 & 1.00198795101416 \tabularnewline
53 & 106.71 & 106.216917179032 & 106.25125 & 0.999676871368877 & 1.00464222493048 \tabularnewline
54 & 106.34 & 106.263426759229 & 106.284166666667 & 0.999804863620916 & 1.00072059826326 \tabularnewline
55 & 106.11 & 106.132693921416 & 106.3425 & 0.998027072162269 & 0.999786174075324 \tabularnewline
56 & 106.15 & 106.030354685498 & 106.439166666667 & 0.996159195961683 & 1.00112840624609 \tabularnewline
57 & 106.61 & 106.383390081975 & 106.547083333333 & 0.998463653379925 & 1.00213012499273 \tabularnewline
58 & 106.63 & 106.445770457431 & 106.670833333333 & 0.997890117955684 & 1.00173073614646 \tabularnewline
59 & 106.27 & 106.377553850173 & 106.736666666667 & 0.996635525281909 & 0.998988942250686 \tabularnewline
60 & 105.59 & 106.976351265295 & 106.811666666667 & 1.00154182219759 & 0.98704058187723 \tabularnewline
61 & 107.09 & 106.763073979174 & 106.915416666667 & 0.998575110192315 & 1.00306216380478 \tabularnewline
62 & 108.53 & 108.838904649224 & 107.0125 & 1.01706720849642 & 0.997161817732186 \tabularnewline
63 & 108.01 & 107.543061734696 & 107.09625 & 1.00417205770226 & 1.00434187252782 \tabularnewline
64 & 106.52 & 106.318219956114 & 107.177083333333 & 0.99198650168014 & 1.0018978877183 \tabularnewline
65 & 107.27 & 107.26616136194 & 107.300833333333 & 0.999676871368877 & 1.0000357861045 \tabularnewline
66 & 107.58 & 107.479439424608 & 107.500416666667 & 0.999804863620916 & 1.0009356261619 \tabularnewline
67 & 107.36 & NA & NA & 0.998027072162269 & NA \tabularnewline
68 & 107.23 & NA & NA & 0.996159195961683 & NA \tabularnewline
69 & 107.54 & NA & NA & 0.998463653379925 & NA \tabularnewline
70 & 107.64 & NA & NA & 0.997890117955684 & NA \tabularnewline
71 & 108.23 & NA & NA & 0.996635525281909 & NA \tabularnewline
72 & 108.42 & NA & NA & 1.00154182219759 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=167722&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]100.17[/C][C]NA[/C][C]NA[/C][C]0.998575110192315[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102.01[/C][C]NA[/C][C]NA[/C][C]1.01706720849642[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.3[/C][C]NA[/C][C]NA[/C][C]1.00417205770226[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]99.94[/C][C]NA[/C][C]NA[/C][C]0.99198650168014[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.16[/C][C]NA[/C][C]NA[/C][C]0.999676871368877[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.18[/C][C]NA[/C][C]NA[/C][C]0.999804863620916[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.98[/C][C]100.16989800986[/C][C]100.367916666667[/C][C]0.998027072162269[/C][C]0.998104240758624[/C][/ROW]
[ROW][C]8[/C][C]100.04[/C][C]100.038042055457[/C][C]100.42375[/C][C]0.996159195961683[/C][C]1.00001957199984[/C][/ROW]
[ROW][C]9[/C][C]100.05[/C][C]100.33769266076[/C][C]100.492083333333[/C][C]0.998463653379925[/C][C]0.99713275586541[/C][/ROW]
[ROW][C]10[/C][C]100.11[/C][C]100.334525060051[/C][C]100.546666666667[/C][C]0.997890117955684[/C][C]0.997762235283254[/C][/ROW]
[ROW][C]11[/C][C]100.11[/C][C]100.249906428898[/C][C]100.588333333333[/C][C]0.996635525281909[/C][C]0.998604423346793[/C][/ROW]
[ROW][C]12[/C][C]101.03[/C][C]100.799759385984[/C][C]100.644583333333[/C][C]1.00154182219759[/C][C]1.00228413852789[/C][/ROW]
[ROW][C]13[/C][C]100.84[/C][C]100.581894047084[/C][C]100.725416666667[/C][C]0.998575110192315[/C][C]1.00256612738666[/C][/ROW]
[ROW][C]14[/C][C]102.68[/C][C]102.54198729462[/C][C]100.82125[/C][C]1.01706720849642[/C][C]1.00134591408867[/C][/ROW]
[ROW][C]15[/C][C]101.27[/C][C]101.334767987952[/C][C]100.91375[/C][C]1.00417205770226[/C][C]0.999360851273084[/C][/ROW]
[ROW][C]16[/C][C]100.28[/C][C]100.203863156383[/C][C]101.013333333333[/C][C]0.99198650168014[/C][C]1.00075981944427[/C][/ROW]
[ROW][C]17[/C][C]100.82[/C][C]101.081077252375[/C][C]101.11375[/C][C]0.999676871368877[/C][C]0.997417150079209[/C][/ROW]
[ROW][C]18[/C][C]100.87[/C][C]101.200248295709[/C][C]101.22[/C][C]0.999804863620916[/C][C]0.996736684926463[/C][/ROW]
[ROW][C]19[/C][C]101.23[/C][C]101.112201903826[/C][C]101.312083333333[/C][C]0.998027072162269[/C][C]1.00116502354766[/C][/ROW]
[ROW][C]20[/C][C]101.09[/C][C]101.002656210213[/C][C]101.392083333333[/C][C]0.996159195961683[/C][C]1.00086476725528[/C][/ROW]
[ROW][C]21[/C][C]101.22[/C][C]101.352381348507[/C][C]101.508333333333[/C][C]0.998463653379925[/C][C]0.998693850635319[/C][/ROW]
[ROW][C]22[/C][C]101.33[/C][C]101.387299134494[/C][C]101.601666666667[/C][C]0.997890117955684[/C][C]0.999434848990128[/C][/ROW]
[ROW][C]23[/C][C]101.3[/C][C]101.339146005071[/C][C]101.68125[/C][C]0.996635525281909[/C][C]0.999613712897589[/C][/ROW]
[ROW][C]24[/C][C]102.39[/C][C]101.961965208826[/C][C]101.805[/C][C]1.00154182219759[/C][C]1.00419798490837[/C][/ROW]
[ROW][C]25[/C][C]101.69[/C][C]101.778103814501[/C][C]101.923333333333[/C][C]0.998575110192315[/C][C]0.999134353940589[/C][/ROW]
[ROW][C]26[/C][C]103.75[/C][C]103.771791060894[/C][C]102.030416666667[/C][C]1.01706720849642[/C][C]0.999790009783285[/C][/ROW]
[ROW][C]27[/C][C]102.99[/C][C]102.584962199791[/C][C]102.15875[/C][C]1.00417205770226[/C][C]1.00394831553791[/C][/ROW]
[ROW][C]28[/C][C]100.8[/C][C]101.490138986895[/C][C]102.31[/C][C]0.99198650168014[/C][C]0.993199940469248[/C][/ROW]
[ROW][C]29[/C][C]102.21[/C][C]102.439804733377[/C][C]102.472916666667[/C][C]0.999676871368877[/C][C]0.997756685167693[/C][/ROW]
[ROW][C]30[/C][C]102.45[/C][C]102.623720470289[/C][C]102.64375[/C][C]0.999804863620916[/C][C]0.998307209390838[/C][/ROW]
[ROW][C]31[/C][C]102.49[/C][C]102.598430552121[/C][C]102.80125[/C][C]0.998027072162269[/C][C]0.998943155840319[/C][/ROW]
[ROW][C]32[/C][C]102.4[/C][C]102.563720683552[/C][C]102.959166666667[/C][C]0.996159195961683[/C][C]0.998403717391877[/C][/ROW]
[ROW][C]33[/C][C]102.99[/C][C]102.939106504337[/C][C]103.0975[/C][C]0.998463653379925[/C][C]1.00049440389946[/C][/ROW]
[ROW][C]34[/C][C]103.19[/C][C]103.056270356775[/C][C]103.274166666667[/C][C]0.997890117955684[/C][C]1.00129763713321[/C][/ROW]
[ROW][C]35[/C][C]103.35[/C][C]103.146793689051[/C][C]103.495[/C][C]0.996635525281909[/C][C]1.0019700690994[/C][/ROW]
[ROW][C]36[/C][C]104.44[/C][C]103.85821772552[/C][C]103.698333333333[/C][C]1.00154182219759[/C][C]1.00560169707531[/C][/ROW]
[ROW][C]37[/C][C]103.42[/C][C]103.754450386757[/C][C]103.9025[/C][C]0.998575110192315[/C][C]0.996776520086509[/C][/ROW]
[ROW][C]38[/C][C]105.81[/C][C]105.866101954389[/C][C]104.089583333333[/C][C]1.01706720849642[/C][C]0.999470066873592[/C][/ROW]
[ROW][C]39[/C][C]104.25[/C][C]104.704602051591[/C][C]104.269583333333[/C][C]1.00417205770226[/C][C]0.995658241923626[/C][/ROW]
[ROW][C]40[/C][C]103.78[/C][C]103.601003596929[/C][C]104.437916666667[/C][C]0.99198650168014[/C][C]1.00172774777132[/C][/ROW]
[ROW][C]41[/C][C]104.53[/C][C]104.559119700679[/C][C]104.592916666667[/C][C]0.999676871368877[/C][C]0.999721500135403[/C][/ROW]
[ROW][C]42[/C][C]105.01[/C][C]104.709146781659[/C][C]104.729583333333[/C][C]0.999804863620916[/C][C]1.00287322767483[/C][/ROW]
[ROW][C]43[/C][C]104.83[/C][C]104.665178280724[/C][C]104.872083333333[/C][C]0.998027072162269[/C][C]1.00157475219537[/C][/ROW]
[ROW][C]44[/C][C]104.55[/C][C]104.638222209142[/C][C]105.041666666667[/C][C]0.996159195961683[/C][C]0.999156883524211[/C][/ROW]
[ROW][C]45[/C][C]105.16[/C][C]105.042120574268[/C][C]105.20375[/C][C]0.998463653379925[/C][C]1.00112221102437[/C][/ROW]
[ROW][C]46[/C][C]105.06[/C][C]105.12855550173[/C][C]105.350833333333[/C][C]0.997890117955684[/C][C]0.999347888864235[/C][/ROW]
[ROW][C]47[/C][C]105.2[/C][C]105.158336390912[/C][C]105.513333333333[/C][C]0.996635525281909[/C][C]1.00039619882282[/C][/ROW]
[ROW][C]48[/C][C]105.87[/C][C]105.822491624305[/C][C]105.659583333333[/C][C]1.00154182219759[/C][C]1.00044894402849[/C][/ROW]
[ROW][C]49[/C][C]105.41[/C][C]105.617625113191[/C][C]105.768333333333[/C][C]0.998575110192315[/C][C]0.99803418119875[/C][/ROW]
[ROW][C]50[/C][C]107.89[/C][C]107.695551595672[/C][C]105.888333333333[/C][C]1.01706720849642[/C][C]1.00180553793956[/C][/ROW]
[ROW][C]51[/C][C]106.06[/C][C]106.45771910233[/C][C]106.015416666667[/C][C]1.00417205770226[/C][C]0.996264065154851[/C][/ROW]
[ROW][C]52[/C][C]105.5[/C][C]105.290687271457[/C][C]106.14125[/C][C]0.99198650168014[/C][C]1.00198795101416[/C][/ROW]
[ROW][C]53[/C][C]106.71[/C][C]106.216917179032[/C][C]106.25125[/C][C]0.999676871368877[/C][C]1.00464222493048[/C][/ROW]
[ROW][C]54[/C][C]106.34[/C][C]106.263426759229[/C][C]106.284166666667[/C][C]0.999804863620916[/C][C]1.00072059826326[/C][/ROW]
[ROW][C]55[/C][C]106.11[/C][C]106.132693921416[/C][C]106.3425[/C][C]0.998027072162269[/C][C]0.999786174075324[/C][/ROW]
[ROW][C]56[/C][C]106.15[/C][C]106.030354685498[/C][C]106.439166666667[/C][C]0.996159195961683[/C][C]1.00112840624609[/C][/ROW]
[ROW][C]57[/C][C]106.61[/C][C]106.383390081975[/C][C]106.547083333333[/C][C]0.998463653379925[/C][C]1.00213012499273[/C][/ROW]
[ROW][C]58[/C][C]106.63[/C][C]106.445770457431[/C][C]106.670833333333[/C][C]0.997890117955684[/C][C]1.00173073614646[/C][/ROW]
[ROW][C]59[/C][C]106.27[/C][C]106.377553850173[/C][C]106.736666666667[/C][C]0.996635525281909[/C][C]0.998988942250686[/C][/ROW]
[ROW][C]60[/C][C]105.59[/C][C]106.976351265295[/C][C]106.811666666667[/C][C]1.00154182219759[/C][C]0.98704058187723[/C][/ROW]
[ROW][C]61[/C][C]107.09[/C][C]106.763073979174[/C][C]106.915416666667[/C][C]0.998575110192315[/C][C]1.00306216380478[/C][/ROW]
[ROW][C]62[/C][C]108.53[/C][C]108.838904649224[/C][C]107.0125[/C][C]1.01706720849642[/C][C]0.997161817732186[/C][/ROW]
[ROW][C]63[/C][C]108.01[/C][C]107.543061734696[/C][C]107.09625[/C][C]1.00417205770226[/C][C]1.00434187252782[/C][/ROW]
[ROW][C]64[/C][C]106.52[/C][C]106.318219956114[/C][C]107.177083333333[/C][C]0.99198650168014[/C][C]1.0018978877183[/C][/ROW]
[ROW][C]65[/C][C]107.27[/C][C]107.26616136194[/C][C]107.300833333333[/C][C]0.999676871368877[/C][C]1.0000357861045[/C][/ROW]
[ROW][C]66[/C][C]107.58[/C][C]107.479439424608[/C][C]107.500416666667[/C][C]0.999804863620916[/C][C]1.0009356261619[/C][/ROW]
[ROW][C]67[/C][C]107.36[/C][C]NA[/C][C]NA[/C][C]0.998027072162269[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]107.23[/C][C]NA[/C][C]NA[/C][C]0.996159195961683[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]107.54[/C][C]NA[/C][C]NA[/C][C]0.998463653379925[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]107.64[/C][C]NA[/C][C]NA[/C][C]0.997890117955684[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]108.23[/C][C]NA[/C][C]NA[/C][C]0.996635525281909[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]108.42[/C][C]NA[/C][C]NA[/C][C]1.00154182219759[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=167722&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=167722&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	100.17	NA	NA	0.998575110192315	NA
2	102.01	NA	NA	1.01706720849642	NA
3	100.3	NA	NA	1.00417205770226	NA
4	99.94	NA	NA	0.99198650168014	NA
5	100.16	NA	NA	0.999676871368877	NA
6	100.18	NA	NA	0.999804863620916	NA
7	99.98	100.16989800986	100.367916666667	0.998027072162269	0.998104240758624
8	100.04	100.038042055457	100.42375	0.996159195961683	1.00001957199984
9	100.05	100.33769266076	100.492083333333	0.998463653379925	0.99713275586541
10	100.11	100.334525060051	100.546666666667	0.997890117955684	0.997762235283254
11	100.11	100.249906428898	100.588333333333	0.996635525281909	0.998604423346793
12	101.03	100.799759385984	100.644583333333	1.00154182219759	1.00228413852789
13	100.84	100.581894047084	100.725416666667	0.998575110192315	1.00256612738666
14	102.68	102.54198729462	100.82125	1.01706720849642	1.00134591408867
15	101.27	101.334767987952	100.91375	1.00417205770226	0.999360851273084
16	100.28	100.203863156383	101.013333333333	0.99198650168014	1.00075981944427
17	100.82	101.081077252375	101.11375	0.999676871368877	0.997417150079209
18	100.87	101.200248295709	101.22	0.999804863620916	0.996736684926463
19	101.23	101.112201903826	101.312083333333	0.998027072162269	1.00116502354766
20	101.09	101.002656210213	101.392083333333	0.996159195961683	1.00086476725528
21	101.22	101.352381348507	101.508333333333	0.998463653379925	0.998693850635319
22	101.33	101.387299134494	101.601666666667	0.997890117955684	0.999434848990128
23	101.3	101.339146005071	101.68125	0.996635525281909	0.999613712897589
24	102.39	101.961965208826	101.805	1.00154182219759	1.00419798490837
25	101.69	101.778103814501	101.923333333333	0.998575110192315	0.999134353940589
26	103.75	103.771791060894	102.030416666667	1.01706720849642	0.999790009783285
27	102.99	102.584962199791	102.15875	1.00417205770226	1.00394831553791
28	100.8	101.490138986895	102.31	0.99198650168014	0.993199940469248
29	102.21	102.439804733377	102.472916666667	0.999676871368877	0.997756685167693
30	102.45	102.623720470289	102.64375	0.999804863620916	0.998307209390838
31	102.49	102.598430552121	102.80125	0.998027072162269	0.998943155840319
32	102.4	102.563720683552	102.959166666667	0.996159195961683	0.998403717391877
33	102.99	102.939106504337	103.0975	0.998463653379925	1.00049440389946
34	103.19	103.056270356775	103.274166666667	0.997890117955684	1.00129763713321
35	103.35	103.146793689051	103.495	0.996635525281909	1.0019700690994
36	104.44	103.85821772552	103.698333333333	1.00154182219759	1.00560169707531
37	103.42	103.754450386757	103.9025	0.998575110192315	0.996776520086509
38	105.81	105.866101954389	104.089583333333	1.01706720849642	0.999470066873592
39	104.25	104.704602051591	104.269583333333	1.00417205770226	0.995658241923626
40	103.78	103.601003596929	104.437916666667	0.99198650168014	1.00172774777132
41	104.53	104.559119700679	104.592916666667	0.999676871368877	0.999721500135403
42	105.01	104.709146781659	104.729583333333	0.999804863620916	1.00287322767483
43	104.83	104.665178280724	104.872083333333	0.998027072162269	1.00157475219537
44	104.55	104.638222209142	105.041666666667	0.996159195961683	0.999156883524211
45	105.16	105.042120574268	105.20375	0.998463653379925	1.00112221102437
46	105.06	105.12855550173	105.350833333333	0.997890117955684	0.999347888864235
47	105.2	105.158336390912	105.513333333333	0.996635525281909	1.00039619882282
48	105.87	105.822491624305	105.659583333333	1.00154182219759	1.00044894402849
49	105.41	105.617625113191	105.768333333333	0.998575110192315	0.99803418119875
50	107.89	107.695551595672	105.888333333333	1.01706720849642	1.00180553793956
51	106.06	106.45771910233	106.015416666667	1.00417205770226	0.996264065154851
52	105.5	105.290687271457	106.14125	0.99198650168014	1.00198795101416
53	106.71	106.216917179032	106.25125	0.999676871368877	1.00464222493048
54	106.34	106.263426759229	106.284166666667	0.999804863620916	1.00072059826326
55	106.11	106.132693921416	106.3425	0.998027072162269	0.999786174075324
56	106.15	106.030354685498	106.439166666667	0.996159195961683	1.00112840624609
57	106.61	106.383390081975	106.547083333333	0.998463653379925	1.00213012499273
58	106.63	106.445770457431	106.670833333333	0.997890117955684	1.00173073614646
59	106.27	106.377553850173	106.736666666667	0.996635525281909	0.998988942250686
60	105.59	106.976351265295	106.811666666667	1.00154182219759	0.98704058187723
61	107.09	106.763073979174	106.915416666667	0.998575110192315	1.00306216380478
62	108.53	108.838904649224	107.0125	1.01706720849642	0.997161817732186
63	108.01	107.543061734696	107.09625	1.00417205770226	1.00434187252782
64	106.52	106.318219956114	107.177083333333	0.99198650168014	1.0018978877183
65	107.27	107.26616136194	107.300833333333	0.999676871368877	1.0000357861045
66	107.58	107.479439424608	107.500416666667	0.999804863620916	1.0009356261619
67	107.36	NA	NA	0.998027072162269	NA
68	107.23	NA	NA	0.996159195961683	NA
69	107.54	NA	NA	0.998463653379925	NA
70	107.64	NA	NA	0.997890117955684	NA
71	108.23	NA	NA	0.996635525281909	NA
72	108.42	NA	NA	1.00154182219759	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