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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 11:39:30 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t1259952035ec17wq4mgvvgp4y.htm/, Retrieved Sat, 27 Apr 2024 17:50:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64019, Retrieved Sat, 27 Apr 2024 17:50:04 +0000

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Estimated Impact

132

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-    D    [Classical Decomposition] [Klassiek decompos...] [2009-12-01 19:46:49] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-    D        [Classical Decomposition] [klassieke decompo...] [2009-12-04 18:39:30] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
-    D          [Classical Decomposition] [Klassieke decompo...] [2009-12-11 15:40:47] [4f1a20f787b3465111b61213cdeef1a9] 
-    D            [Classical Decomposition] [Klassieke decompo...] [2009-12-11 16:38:20] [4f1a20f787b3465111b61213cdeef1a9] 

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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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64019&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64019&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64019&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	107.11	NA	NA	0.997537193196223	NA
2	107.57	NA	NA	1.00053837314138	NA
3	107.81	NA	NA	1.00216513945625	NA
4	108.75	NA	NA	1.00181946953812	NA
5	109.43	NA	NA	1.00113455682792	NA
6	109.62	NA	NA	1.00014340559154	NA
7	109.54	109.328699611791	109.147916666667	1.00165631145922	1.00193270741314
8	109.53	109.490673734648	109.395416666667	1.00087075922268	1.00035917456721
9	109.84	109.79176865484	109.633333333333	1.00144513823205	1.00043929837137
10	109.67	109.774294813808	109.835416666667	0.999443514171352	0.999049915884361
11	109.79	109.767261159592	109.978333333333	0.998080784029506	1.00020715503118
12	109.56	109.546972988661	110.079166666667	0.995165355133756	1.00011891712736
13	110.22	109.906154103377	110.1775	0.997537193196223	1.00285558073780
14	110.4	110.352712301674	110.293333333333	1.00053837314138	1.00042851414650
15	110.69	110.647382772132	110.408333333333	1.00216513945625	1.00038516254791
16	110.72	110.726096870701	110.525	1.00181946953812	0.9999449373646
17	110.89	110.760104555259	110.634583333333	1.00113455682792	1.00117276383282
18	110.58	110.763381810749	110.7475	1.00014340559154	0.99834438234233
19	110.94	111.049044326723	110.865416666667	1.00165631145922	0.999018052542607
20	110.91	111.097488332683	111.000833333333	1.00087075922268	0.99831239809741
21	111.22	111.322727909912	111.162083333333	1.00144513823205	0.999077206318592
22	111.09	111.249723301604	111.311666666667	0.999443514171352	0.99856428135852
23	111	111.214062429441	111.427916666667	0.998080784029506	0.99807522156133
24	111.06	111.011110017402	111.550416666667	0.995165355133756	1.00044040621331
25	111.55	111.418669872561	111.69375	0.997537193196223	1.00117870844796
26	112.32	111.905214343998	111.845	1.00053837314138	1.00370658023787
27	112.64	112.253352408111	112.010833333333	1.00216513945625	1.00344441910727
28	112.36	112.371585349418	112.1675	1.00181946953812	0.999896901433031
29	112.04	112.454107653291	112.326666666667	1.00113455682792	0.996317540889054
30	112.37	112.509048779925	112.492916666667	1.00014340559154	0.998764110252169
31	112.59	112.833661988306	112.647083333333	1.00165631145922	0.997840520426157
32	112.89	112.878204225134	112.78	1.00087075922268	1.00010450002237
33	113.22	113.055227999054	112.892083333333	1.00144513823205	1.00145744698288
34	112.85	112.972097624359	113.035	0.999443514171352	0.998919223180534
35	113.06	113.029321855395	113.246666666667	0.998080784029506	1.00027141757644
36	112.99	112.925559369340	113.474166666667	0.995165355133756	1.00057064699099
37	113.32	113.412912977959	113.692916666667	0.997537193196223	0.99918075485834
38	113.74	113.973410539479	113.912083333333	1.00053837314138	0.997952061464386
39	113.91	114.361239751434	114.114166666667	1.00216513945625	0.996054259708846
40	114.52	114.552629819558	114.344583333333	1.00181946953812	0.999715154339021
41	114.96	114.729185933683	114.599166666667	1.00113455682792	1.00201181647406
42	114.91	114.842716726306	114.82625	1.00014340559154	1.00058587323265
43	115.3	115.230542070268	115.04	1.00165631145922	1.00060277360918
44	115.44	115.368704297666	115.268333333333	1.00087075922268	1.00061798130410
45	115.52	115.702798583255	115.535833333333	1.00144513823205	0.99842010231824
46	116.08	115.748884854565	115.813333333333	0.999443514171352	1.00286063356767
47	115.94	115.842662065378	116.065416666667	0.998080784029506	1.00084025982213
48	115.56	115.760951327009	116.323333333333	0.995165355133756	0.998264083659426
49	115.88	116.324474660600	116.611666666667	0.997537193196223	0.996179009946986
50	116.66	116.975025658903	116.912083333333	1.00053837314138	0.997306898142328
51	117.41	117.467534114940	117.21375	1.00216513945625	0.99951021262706
52	117.68	117.699177803465	117.485416666667	1.00181946953812	0.99983706085443
53	117.85	117.862737096554	117.729166666667	1.00113455682792	0.99989193279515
54	118.21	118.009420784260	117.9925	1.00014340559154	1.00169968816394
55	118.92	NA	NA	1.00165631145922	NA
56	119.03	NA	NA	1.00087075922268	NA
57	119.17	NA	NA	1.00144513823205	NA
58	118.95	NA	NA	0.999443514171352	NA
59	118.92	NA	NA	0.998080784029506	NA
60	118.9	NA	NA	0.995165355133756	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 107.11 & NA & NA & 0.997537193196223 & NA \tabularnewline
2 & 107.57 & NA & NA & 1.00053837314138 & NA \tabularnewline
3 & 107.81 & NA & NA & 1.00216513945625 & NA \tabularnewline
4 & 108.75 & NA & NA & 1.00181946953812 & NA \tabularnewline
5 & 109.43 & NA & NA & 1.00113455682792 & NA \tabularnewline
6 & 109.62 & NA & NA & 1.00014340559154 & NA \tabularnewline
7 & 109.54 & 109.328699611791 & 109.147916666667 & 1.00165631145922 & 1.00193270741314 \tabularnewline
8 & 109.53 & 109.490673734648 & 109.395416666667 & 1.00087075922268 & 1.00035917456721 \tabularnewline
9 & 109.84 & 109.79176865484 & 109.633333333333 & 1.00144513823205 & 1.00043929837137 \tabularnewline
10 & 109.67 & 109.774294813808 & 109.835416666667 & 0.999443514171352 & 0.999049915884361 \tabularnewline
11 & 109.79 & 109.767261159592 & 109.978333333333 & 0.998080784029506 & 1.00020715503118 \tabularnewline
12 & 109.56 & 109.546972988661 & 110.079166666667 & 0.995165355133756 & 1.00011891712736 \tabularnewline
13 & 110.22 & 109.906154103377 & 110.1775 & 0.997537193196223 & 1.00285558073780 \tabularnewline
14 & 110.4 & 110.352712301674 & 110.293333333333 & 1.00053837314138 & 1.00042851414650 \tabularnewline
15 & 110.69 & 110.647382772132 & 110.408333333333 & 1.00216513945625 & 1.00038516254791 \tabularnewline
16 & 110.72 & 110.726096870701 & 110.525 & 1.00181946953812 & 0.9999449373646 \tabularnewline
17 & 110.89 & 110.760104555259 & 110.634583333333 & 1.00113455682792 & 1.00117276383282 \tabularnewline
18 & 110.58 & 110.763381810749 & 110.7475 & 1.00014340559154 & 0.99834438234233 \tabularnewline
19 & 110.94 & 111.049044326723 & 110.865416666667 & 1.00165631145922 & 0.999018052542607 \tabularnewline
20 & 110.91 & 111.097488332683 & 111.000833333333 & 1.00087075922268 & 0.99831239809741 \tabularnewline
21 & 111.22 & 111.322727909912 & 111.162083333333 & 1.00144513823205 & 0.999077206318592 \tabularnewline
22 & 111.09 & 111.249723301604 & 111.311666666667 & 0.999443514171352 & 0.99856428135852 \tabularnewline
23 & 111 & 111.214062429441 & 111.427916666667 & 0.998080784029506 & 0.99807522156133 \tabularnewline
24 & 111.06 & 111.011110017402 & 111.550416666667 & 0.995165355133756 & 1.00044040621331 \tabularnewline
25 & 111.55 & 111.418669872561 & 111.69375 & 0.997537193196223 & 1.00117870844796 \tabularnewline
26 & 112.32 & 111.905214343998 & 111.845 & 1.00053837314138 & 1.00370658023787 \tabularnewline
27 & 112.64 & 112.253352408111 & 112.010833333333 & 1.00216513945625 & 1.00344441910727 \tabularnewline
28 & 112.36 & 112.371585349418 & 112.1675 & 1.00181946953812 & 0.999896901433031 \tabularnewline
29 & 112.04 & 112.454107653291 & 112.326666666667 & 1.00113455682792 & 0.996317540889054 \tabularnewline
30 & 112.37 & 112.509048779925 & 112.492916666667 & 1.00014340559154 & 0.998764110252169 \tabularnewline
31 & 112.59 & 112.833661988306 & 112.647083333333 & 1.00165631145922 & 0.997840520426157 \tabularnewline
32 & 112.89 & 112.878204225134 & 112.78 & 1.00087075922268 & 1.00010450002237 \tabularnewline
33 & 113.22 & 113.055227999054 & 112.892083333333 & 1.00144513823205 & 1.00145744698288 \tabularnewline
34 & 112.85 & 112.972097624359 & 113.035 & 0.999443514171352 & 0.998919223180534 \tabularnewline
35 & 113.06 & 113.029321855395 & 113.246666666667 & 0.998080784029506 & 1.00027141757644 \tabularnewline
36 & 112.99 & 112.925559369340 & 113.474166666667 & 0.995165355133756 & 1.00057064699099 \tabularnewline
37 & 113.32 & 113.412912977959 & 113.692916666667 & 0.997537193196223 & 0.99918075485834 \tabularnewline
38 & 113.74 & 113.973410539479 & 113.912083333333 & 1.00053837314138 & 0.997952061464386 \tabularnewline
39 & 113.91 & 114.361239751434 & 114.114166666667 & 1.00216513945625 & 0.996054259708846 \tabularnewline
40 & 114.52 & 114.552629819558 & 114.344583333333 & 1.00181946953812 & 0.999715154339021 \tabularnewline
41 & 114.96 & 114.729185933683 & 114.599166666667 & 1.00113455682792 & 1.00201181647406 \tabularnewline
42 & 114.91 & 114.842716726306 & 114.82625 & 1.00014340559154 & 1.00058587323265 \tabularnewline
43 & 115.3 & 115.230542070268 & 115.04 & 1.00165631145922 & 1.00060277360918 \tabularnewline
44 & 115.44 & 115.368704297666 & 115.268333333333 & 1.00087075922268 & 1.00061798130410 \tabularnewline
45 & 115.52 & 115.702798583255 & 115.535833333333 & 1.00144513823205 & 0.99842010231824 \tabularnewline
46 & 116.08 & 115.748884854565 & 115.813333333333 & 0.999443514171352 & 1.00286063356767 \tabularnewline
47 & 115.94 & 115.842662065378 & 116.065416666667 & 0.998080784029506 & 1.00084025982213 \tabularnewline
48 & 115.56 & 115.760951327009 & 116.323333333333 & 0.995165355133756 & 0.998264083659426 \tabularnewline
49 & 115.88 & 116.324474660600 & 116.611666666667 & 0.997537193196223 & 0.996179009946986 \tabularnewline
50 & 116.66 & 116.975025658903 & 116.912083333333 & 1.00053837314138 & 0.997306898142328 \tabularnewline
51 & 117.41 & 117.467534114940 & 117.21375 & 1.00216513945625 & 0.99951021262706 \tabularnewline
52 & 117.68 & 117.699177803465 & 117.485416666667 & 1.00181946953812 & 0.99983706085443 \tabularnewline
53 & 117.85 & 117.862737096554 & 117.729166666667 & 1.00113455682792 & 0.99989193279515 \tabularnewline
54 & 118.21 & 118.009420784260 & 117.9925 & 1.00014340559154 & 1.00169968816394 \tabularnewline
55 & 118.92 & NA & NA & 1.00165631145922 & NA \tabularnewline
56 & 119.03 & NA & NA & 1.00087075922268 & NA \tabularnewline
57 & 119.17 & NA & NA & 1.00144513823205 & NA \tabularnewline
58 & 118.95 & NA & NA & 0.999443514171352 & NA \tabularnewline
59 & 118.92 & NA & NA & 0.998080784029506 & NA \tabularnewline
60 & 118.9 & NA & NA & 0.995165355133756 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64019&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]107.11[/C][C]NA[/C][C]NA[/C][C]0.997537193196223[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]107.57[/C][C]NA[/C][C]NA[/C][C]1.00053837314138[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]107.81[/C][C]NA[/C][C]NA[/C][C]1.00216513945625[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]108.75[/C][C]NA[/C][C]NA[/C][C]1.00181946953812[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]109.43[/C][C]NA[/C][C]NA[/C][C]1.00113455682792[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]109.62[/C][C]NA[/C][C]NA[/C][C]1.00014340559154[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]109.54[/C][C]109.328699611791[/C][C]109.147916666667[/C][C]1.00165631145922[/C][C]1.00193270741314[/C][/ROW]
[ROW][C]8[/C][C]109.53[/C][C]109.490673734648[/C][C]109.395416666667[/C][C]1.00087075922268[/C][C]1.00035917456721[/C][/ROW]
[ROW][C]9[/C][C]109.84[/C][C]109.79176865484[/C][C]109.633333333333[/C][C]1.00144513823205[/C][C]1.00043929837137[/C][/ROW]
[ROW][C]10[/C][C]109.67[/C][C]109.774294813808[/C][C]109.835416666667[/C][C]0.999443514171352[/C][C]0.999049915884361[/C][/ROW]
[ROW][C]11[/C][C]109.79[/C][C]109.767261159592[/C][C]109.978333333333[/C][C]0.998080784029506[/C][C]1.00020715503118[/C][/ROW]
[ROW][C]12[/C][C]109.56[/C][C]109.546972988661[/C][C]110.079166666667[/C][C]0.995165355133756[/C][C]1.00011891712736[/C][/ROW]
[ROW][C]13[/C][C]110.22[/C][C]109.906154103377[/C][C]110.1775[/C][C]0.997537193196223[/C][C]1.00285558073780[/C][/ROW]
[ROW][C]14[/C][C]110.4[/C][C]110.352712301674[/C][C]110.293333333333[/C][C]1.00053837314138[/C][C]1.00042851414650[/C][/ROW]
[ROW][C]15[/C][C]110.69[/C][C]110.647382772132[/C][C]110.408333333333[/C][C]1.00216513945625[/C][C]1.00038516254791[/C][/ROW]
[ROW][C]16[/C][C]110.72[/C][C]110.726096870701[/C][C]110.525[/C][C]1.00181946953812[/C][C]0.9999449373646[/C][/ROW]
[ROW][C]17[/C][C]110.89[/C][C]110.760104555259[/C][C]110.634583333333[/C][C]1.00113455682792[/C][C]1.00117276383282[/C][/ROW]
[ROW][C]18[/C][C]110.58[/C][C]110.763381810749[/C][C]110.7475[/C][C]1.00014340559154[/C][C]0.99834438234233[/C][/ROW]
[ROW][C]19[/C][C]110.94[/C][C]111.049044326723[/C][C]110.865416666667[/C][C]1.00165631145922[/C][C]0.999018052542607[/C][/ROW]
[ROW][C]20[/C][C]110.91[/C][C]111.097488332683[/C][C]111.000833333333[/C][C]1.00087075922268[/C][C]0.99831239809741[/C][/ROW]
[ROW][C]21[/C][C]111.22[/C][C]111.322727909912[/C][C]111.162083333333[/C][C]1.00144513823205[/C][C]0.999077206318592[/C][/ROW]
[ROW][C]22[/C][C]111.09[/C][C]111.249723301604[/C][C]111.311666666667[/C][C]0.999443514171352[/C][C]0.99856428135852[/C][/ROW]
[ROW][C]23[/C][C]111[/C][C]111.214062429441[/C][C]111.427916666667[/C][C]0.998080784029506[/C][C]0.99807522156133[/C][/ROW]
[ROW][C]24[/C][C]111.06[/C][C]111.011110017402[/C][C]111.550416666667[/C][C]0.995165355133756[/C][C]1.00044040621331[/C][/ROW]
[ROW][C]25[/C][C]111.55[/C][C]111.418669872561[/C][C]111.69375[/C][C]0.997537193196223[/C][C]1.00117870844796[/C][/ROW]
[ROW][C]26[/C][C]112.32[/C][C]111.905214343998[/C][C]111.845[/C][C]1.00053837314138[/C][C]1.00370658023787[/C][/ROW]
[ROW][C]27[/C][C]112.64[/C][C]112.253352408111[/C][C]112.010833333333[/C][C]1.00216513945625[/C][C]1.00344441910727[/C][/ROW]
[ROW][C]28[/C][C]112.36[/C][C]112.371585349418[/C][C]112.1675[/C][C]1.00181946953812[/C][C]0.999896901433031[/C][/ROW]
[ROW][C]29[/C][C]112.04[/C][C]112.454107653291[/C][C]112.326666666667[/C][C]1.00113455682792[/C][C]0.996317540889054[/C][/ROW]
[ROW][C]30[/C][C]112.37[/C][C]112.509048779925[/C][C]112.492916666667[/C][C]1.00014340559154[/C][C]0.998764110252169[/C][/ROW]
[ROW][C]31[/C][C]112.59[/C][C]112.833661988306[/C][C]112.647083333333[/C][C]1.00165631145922[/C][C]0.997840520426157[/C][/ROW]
[ROW][C]32[/C][C]112.89[/C][C]112.878204225134[/C][C]112.78[/C][C]1.00087075922268[/C][C]1.00010450002237[/C][/ROW]
[ROW][C]33[/C][C]113.22[/C][C]113.055227999054[/C][C]112.892083333333[/C][C]1.00144513823205[/C][C]1.00145744698288[/C][/ROW]
[ROW][C]34[/C][C]112.85[/C][C]112.972097624359[/C][C]113.035[/C][C]0.999443514171352[/C][C]0.998919223180534[/C][/ROW]
[ROW][C]35[/C][C]113.06[/C][C]113.029321855395[/C][C]113.246666666667[/C][C]0.998080784029506[/C][C]1.00027141757644[/C][/ROW]
[ROW][C]36[/C][C]112.99[/C][C]112.925559369340[/C][C]113.474166666667[/C][C]0.995165355133756[/C][C]1.00057064699099[/C][/ROW]
[ROW][C]37[/C][C]113.32[/C][C]113.412912977959[/C][C]113.692916666667[/C][C]0.997537193196223[/C][C]0.99918075485834[/C][/ROW]
[ROW][C]38[/C][C]113.74[/C][C]113.973410539479[/C][C]113.912083333333[/C][C]1.00053837314138[/C][C]0.997952061464386[/C][/ROW]
[ROW][C]39[/C][C]113.91[/C][C]114.361239751434[/C][C]114.114166666667[/C][C]1.00216513945625[/C][C]0.996054259708846[/C][/ROW]
[ROW][C]40[/C][C]114.52[/C][C]114.552629819558[/C][C]114.344583333333[/C][C]1.00181946953812[/C][C]0.999715154339021[/C][/ROW]
[ROW][C]41[/C][C]114.96[/C][C]114.729185933683[/C][C]114.599166666667[/C][C]1.00113455682792[/C][C]1.00201181647406[/C][/ROW]
[ROW][C]42[/C][C]114.91[/C][C]114.842716726306[/C][C]114.82625[/C][C]1.00014340559154[/C][C]1.00058587323265[/C][/ROW]
[ROW][C]43[/C][C]115.3[/C][C]115.230542070268[/C][C]115.04[/C][C]1.00165631145922[/C][C]1.00060277360918[/C][/ROW]
[ROW][C]44[/C][C]115.44[/C][C]115.368704297666[/C][C]115.268333333333[/C][C]1.00087075922268[/C][C]1.00061798130410[/C][/ROW]
[ROW][C]45[/C][C]115.52[/C][C]115.702798583255[/C][C]115.535833333333[/C][C]1.00144513823205[/C][C]0.99842010231824[/C][/ROW]
[ROW][C]46[/C][C]116.08[/C][C]115.748884854565[/C][C]115.813333333333[/C][C]0.999443514171352[/C][C]1.00286063356767[/C][/ROW]
[ROW][C]47[/C][C]115.94[/C][C]115.842662065378[/C][C]116.065416666667[/C][C]0.998080784029506[/C][C]1.00084025982213[/C][/ROW]
[ROW][C]48[/C][C]115.56[/C][C]115.760951327009[/C][C]116.323333333333[/C][C]0.995165355133756[/C][C]0.998264083659426[/C][/ROW]
[ROW][C]49[/C][C]115.88[/C][C]116.324474660600[/C][C]116.611666666667[/C][C]0.997537193196223[/C][C]0.996179009946986[/C][/ROW]
[ROW][C]50[/C][C]116.66[/C][C]116.975025658903[/C][C]116.912083333333[/C][C]1.00053837314138[/C][C]0.997306898142328[/C][/ROW]
[ROW][C]51[/C][C]117.41[/C][C]117.467534114940[/C][C]117.21375[/C][C]1.00216513945625[/C][C]0.99951021262706[/C][/ROW]
[ROW][C]52[/C][C]117.68[/C][C]117.699177803465[/C][C]117.485416666667[/C][C]1.00181946953812[/C][C]0.99983706085443[/C][/ROW]
[ROW][C]53[/C][C]117.85[/C][C]117.862737096554[/C][C]117.729166666667[/C][C]1.00113455682792[/C][C]0.99989193279515[/C][/ROW]
[ROW][C]54[/C][C]118.21[/C][C]118.009420784260[/C][C]117.9925[/C][C]1.00014340559154[/C][C]1.00169968816394[/C][/ROW]
[ROW][C]55[/C][C]118.92[/C][C]NA[/C][C]NA[/C][C]1.00165631145922[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]119.03[/C][C]NA[/C][C]NA[/C][C]1.00087075922268[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]119.17[/C][C]NA[/C][C]NA[/C][C]1.00144513823205[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]118.95[/C][C]NA[/C][C]NA[/C][C]0.999443514171352[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]118.92[/C][C]NA[/C][C]NA[/C][C]0.998080784029506[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]118.9[/C][C]NA[/C][C]NA[/C][C]0.995165355133756[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64019&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64019&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	107.11	NA	NA	0.997537193196223	NA
2	107.57	NA	NA	1.00053837314138	NA
3	107.81	NA	NA	1.00216513945625	NA
4	108.75	NA	NA	1.00181946953812	NA
5	109.43	NA	NA	1.00113455682792	NA
6	109.62	NA	NA	1.00014340559154	NA
7	109.54	109.328699611791	109.147916666667	1.00165631145922	1.00193270741314
8	109.53	109.490673734648	109.395416666667	1.00087075922268	1.00035917456721
9	109.84	109.79176865484	109.633333333333	1.00144513823205	1.00043929837137
10	109.67	109.774294813808	109.835416666667	0.999443514171352	0.999049915884361
11	109.79	109.767261159592	109.978333333333	0.998080784029506	1.00020715503118
12	109.56	109.546972988661	110.079166666667	0.995165355133756	1.00011891712736
13	110.22	109.906154103377	110.1775	0.997537193196223	1.00285558073780
14	110.4	110.352712301674	110.293333333333	1.00053837314138	1.00042851414650
15	110.69	110.647382772132	110.408333333333	1.00216513945625	1.00038516254791
16	110.72	110.726096870701	110.525	1.00181946953812	0.9999449373646
17	110.89	110.760104555259	110.634583333333	1.00113455682792	1.00117276383282
18	110.58	110.763381810749	110.7475	1.00014340559154	0.99834438234233
19	110.94	111.049044326723	110.865416666667	1.00165631145922	0.999018052542607
20	110.91	111.097488332683	111.000833333333	1.00087075922268	0.99831239809741
21	111.22	111.322727909912	111.162083333333	1.00144513823205	0.999077206318592
22	111.09	111.249723301604	111.311666666667	0.999443514171352	0.99856428135852
23	111	111.214062429441	111.427916666667	0.998080784029506	0.99807522156133
24	111.06	111.011110017402	111.550416666667	0.995165355133756	1.00044040621331
25	111.55	111.418669872561	111.69375	0.997537193196223	1.00117870844796
26	112.32	111.905214343998	111.845	1.00053837314138	1.00370658023787
27	112.64	112.253352408111	112.010833333333	1.00216513945625	1.00344441910727
28	112.36	112.371585349418	112.1675	1.00181946953812	0.999896901433031
29	112.04	112.454107653291	112.326666666667	1.00113455682792	0.996317540889054
30	112.37	112.509048779925	112.492916666667	1.00014340559154	0.998764110252169
31	112.59	112.833661988306	112.647083333333	1.00165631145922	0.997840520426157
32	112.89	112.878204225134	112.78	1.00087075922268	1.00010450002237
33	113.22	113.055227999054	112.892083333333	1.00144513823205	1.00145744698288
34	112.85	112.972097624359	113.035	0.999443514171352	0.998919223180534
35	113.06	113.029321855395	113.246666666667	0.998080784029506	1.00027141757644
36	112.99	112.925559369340	113.474166666667	0.995165355133756	1.00057064699099
37	113.32	113.412912977959	113.692916666667	0.997537193196223	0.99918075485834
38	113.74	113.973410539479	113.912083333333	1.00053837314138	0.997952061464386
39	113.91	114.361239751434	114.114166666667	1.00216513945625	0.996054259708846
40	114.52	114.552629819558	114.344583333333	1.00181946953812	0.999715154339021
41	114.96	114.729185933683	114.599166666667	1.00113455682792	1.00201181647406
42	114.91	114.842716726306	114.82625	1.00014340559154	1.00058587323265
43	115.3	115.230542070268	115.04	1.00165631145922	1.00060277360918
44	115.44	115.368704297666	115.268333333333	1.00087075922268	1.00061798130410
45	115.52	115.702798583255	115.535833333333	1.00144513823205	0.99842010231824
46	116.08	115.748884854565	115.813333333333	0.999443514171352	1.00286063356767
47	115.94	115.842662065378	116.065416666667	0.998080784029506	1.00084025982213
48	115.56	115.760951327009	116.323333333333	0.995165355133756	0.998264083659426
49	115.88	116.324474660600	116.611666666667	0.997537193196223	0.996179009946986
50	116.66	116.975025658903	116.912083333333	1.00053837314138	0.997306898142328
51	117.41	117.467534114940	117.21375	1.00216513945625	0.99951021262706
52	117.68	117.699177803465	117.485416666667	1.00181946953812	0.99983706085443
53	117.85	117.862737096554	117.729166666667	1.00113455682792	0.99989193279515
54	118.21	118.009420784260	117.9925	1.00014340559154	1.00169968816394
55	118.92	NA	NA	1.00165631145922	NA
56	119.03	NA	NA	1.00087075922268	NA
57	119.17	NA	NA	1.00144513823205	NA
58	118.95	NA	NA	0.999443514171352	NA
59	118.92	NA	NA	0.998080784029506	NA
60	118.9	NA	NA	0.995165355133756	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