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rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 12:51:43 -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/t1259956364l5dcrusotlpdkuc.htm/, Retrieved Sun, 28 Apr 2024 12:58:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64108, Retrieved Sun, 28 Apr 2024 12:58:41 +0000

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No (this computation is public)

User-defined keywords

ws9.8

Estimated Impact

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] [WS 9] [2009-12-03 15:08:45] [3e19a07d230ba260a720e0e03e0f40f2]
-   PD        [Classical Decomposition] [ws9] [2009-12-04 19:51:43] [682632737e024f9e62885141c5f654cd] [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	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=64108&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=64108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64108&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	126.51	NA	NA	0.969637405271937	NA
2	131.02	NA	NA	1.0060251944183	NA
3	136.51	NA	NA	1.03540392750211	NA
4	138.04	NA	NA	1.04900960884383	NA
5	132.92	NA	NA	1.01866562184587	NA
6	129.61	NA	NA	0.98277443952445	NA
7	122.96	120.961555636422	126.079166666667	0.959409542706017	1.01652131830699
8	124.04	122.888334516291	125.195416666667	0.98157215166656	1.00937164205408
9	121.29	122.341431798437	124.523333333333	0.982477970381214	0.991405758597227
10	124.56	127.708142921957	123.934583333333	1.03044799512074	0.97534892568377
11	118.53	123.394273764207	123.490833333333	0.999218083103665	0.96057942061799
12	113.14	121.472067628367	123.277083333333	0.985358059615301	0.931407542564778
13	114.15	119.636691171550	123.382916666667	0.969637405271937	0.954138725186885
14	122.17	124.879164914637	124.13125	1.0060251944183	0.97830570923109
15	129.23	129.963469561762	125.519583333333	1.03540392750211	0.994356340560655
16	131.19	133.485161463367	127.24875	1.04900960884383	0.982805868171371
17	129.12	131.274165355250	128.86875	1.01866562184587	0.983590332877602
18	128.28	128.094820447617	130.34	0.98277443952445	1.00144564434172
19	126.83	126.258695574088	131.600416666667	0.959409542706017	1.00452487191725
20	138.13	129.926206843741	132.365416666667	0.98157215166656	1.06314194307332
21	140.52	130.489449099465	132.816666666667	0.982477970381214	1.0768686738258
22	146.83	137.272417730003	133.21625	1.03044799512074	1.06962492850382
23	135.14	133.515520264312	133.62	0.999218083103665	1.01216697304158
24	131.84	131.843371771676	133.8025	0.985358059615301	0.999974425929563
25	125.7	129.518104362442	133.57375	0.969637405271937	0.970520689897083
26	128.98	133.387203819265	132.588333333333	1.0060251944183	0.966959320736367
27	133.25	135.585281469796	130.949166666667	1.03540392750211	0.982776290726542
28	136.76	135.508438746424	129.1775	1.04900960884383	1.00923603921020
29	133.24	130.343784087298	127.955416666667	1.01866562184587	1.02221982377589
30	128.54	125.198911765818	127.393333333333	0.98277443952445	1.02668624021614
31	121.08	121.860602328733	127.01625	0.959409542706017	0.993594301079955
32	120.23	124.293209658364	126.626666666667	0.98157215166656	0.967309479982596
33	119.08	123.903162405522	126.112916666667	0.982477970381214	0.961073129112427
34	125.75	129.349131354187	125.527083333333	1.03044799512074	0.972175063593341
35	126.89	124.898929661014	124.996666666667	0.999218083103665	1.01594145237585
36	126.6	122.808870062579	124.63375	0.985358059615301	1.03087016382033
37	121.89	120.635013683395	124.4125	0.969637405271937	1.01040316802134
38	123.44	125.064441221275	124.315416666667	1.0060251944183	0.987011166360218
39	126.46	128.868098490126	124.461666666667	1.03540392750211	0.981313463003334
40	129.49	130.995074904374	124.875	1.04900960884383	0.988510446629596
41	127.78	127.714353450908	125.374166666667	1.01866562184587	1.00051401073817
42	125.29	123.798048700146	125.967916666667	0.98277443952445	1.01205149285889
43	119.02	121.783449811341	126.935833333333	0.959409542706017	0.977308494580984
44	119.96	125.991738469144	128.357083333333	0.98157215166656	0.952125920775186
45	122.86	127.633303766402	129.909583333333	0.982477970381214	0.962601424349724
46	131.89	135.299539172678	131.301666666667	1.03044799512074	0.97480006810425
47	132.73	132.298555907265	132.402083333333	0.999218083103665	1.00326113984976
48	135.01	131.116259636852	133.064583333333	0.985358059615301	1.02969685357051
49	136.71	129.351649941204	133.402083333333	0.969637405271937	1.05688640277987
50	142.73	134.692521509023	133.885833333333	1.0060251944183	1.05967278955750
51	144.43	139.748036676657	134.969583333333	1.03540392750211	1.03350289159465
52	144.93	143.296898004753	136.602083333333	1.04900960884383	1.01139663187401
53	138.75	140.773646722972	138.194166666667	1.01866562184587	0.985624818493518
54	130.22	136.819400534495	139.2175	0.98277443952445	0.951765608468433
55	122.19	NA	NA	0.959409542706017	NA
56	128.4	NA	NA	0.98157215166656	NA
57	140.43	NA	NA	0.982477970381214	NA
58	153.5	NA	NA	1.03044799512074	NA
59	149.33	NA	NA	0.999218083103665	NA
60	142.97	NA	NA	0.985358059615301	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 126.51 & NA & NA & 0.969637405271937 & NA \tabularnewline
2 & 131.02 & NA & NA & 1.0060251944183 & NA \tabularnewline
3 & 136.51 & NA & NA & 1.03540392750211 & NA \tabularnewline
4 & 138.04 & NA & NA & 1.04900960884383 & NA \tabularnewline
5 & 132.92 & NA & NA & 1.01866562184587 & NA \tabularnewline
6 & 129.61 & NA & NA & 0.98277443952445 & NA \tabularnewline
7 & 122.96 & 120.961555636422 & 126.079166666667 & 0.959409542706017 & 1.01652131830699 \tabularnewline
8 & 124.04 & 122.888334516291 & 125.195416666667 & 0.98157215166656 & 1.00937164205408 \tabularnewline
9 & 121.29 & 122.341431798437 & 124.523333333333 & 0.982477970381214 & 0.991405758597227 \tabularnewline
10 & 124.56 & 127.708142921957 & 123.934583333333 & 1.03044799512074 & 0.97534892568377 \tabularnewline
11 & 118.53 & 123.394273764207 & 123.490833333333 & 0.999218083103665 & 0.96057942061799 \tabularnewline
12 & 113.14 & 121.472067628367 & 123.277083333333 & 0.985358059615301 & 0.931407542564778 \tabularnewline
13 & 114.15 & 119.636691171550 & 123.382916666667 & 0.969637405271937 & 0.954138725186885 \tabularnewline
14 & 122.17 & 124.879164914637 & 124.13125 & 1.0060251944183 & 0.97830570923109 \tabularnewline
15 & 129.23 & 129.963469561762 & 125.519583333333 & 1.03540392750211 & 0.994356340560655 \tabularnewline
16 & 131.19 & 133.485161463367 & 127.24875 & 1.04900960884383 & 0.982805868171371 \tabularnewline
17 & 129.12 & 131.274165355250 & 128.86875 & 1.01866562184587 & 0.983590332877602 \tabularnewline
18 & 128.28 & 128.094820447617 & 130.34 & 0.98277443952445 & 1.00144564434172 \tabularnewline
19 & 126.83 & 126.258695574088 & 131.600416666667 & 0.959409542706017 & 1.00452487191725 \tabularnewline
20 & 138.13 & 129.926206843741 & 132.365416666667 & 0.98157215166656 & 1.06314194307332 \tabularnewline
21 & 140.52 & 130.489449099465 & 132.816666666667 & 0.982477970381214 & 1.0768686738258 \tabularnewline
22 & 146.83 & 137.272417730003 & 133.21625 & 1.03044799512074 & 1.06962492850382 \tabularnewline
23 & 135.14 & 133.515520264312 & 133.62 & 0.999218083103665 & 1.01216697304158 \tabularnewline
24 & 131.84 & 131.843371771676 & 133.8025 & 0.985358059615301 & 0.999974425929563 \tabularnewline
25 & 125.7 & 129.518104362442 & 133.57375 & 0.969637405271937 & 0.970520689897083 \tabularnewline
26 & 128.98 & 133.387203819265 & 132.588333333333 & 1.0060251944183 & 0.966959320736367 \tabularnewline
27 & 133.25 & 135.585281469796 & 130.949166666667 & 1.03540392750211 & 0.982776290726542 \tabularnewline
28 & 136.76 & 135.508438746424 & 129.1775 & 1.04900960884383 & 1.00923603921020 \tabularnewline
29 & 133.24 & 130.343784087298 & 127.955416666667 & 1.01866562184587 & 1.02221982377589 \tabularnewline
30 & 128.54 & 125.198911765818 & 127.393333333333 & 0.98277443952445 & 1.02668624021614 \tabularnewline
31 & 121.08 & 121.860602328733 & 127.01625 & 0.959409542706017 & 0.993594301079955 \tabularnewline
32 & 120.23 & 124.293209658364 & 126.626666666667 & 0.98157215166656 & 0.967309479982596 \tabularnewline
33 & 119.08 & 123.903162405522 & 126.112916666667 & 0.982477970381214 & 0.961073129112427 \tabularnewline
34 & 125.75 & 129.349131354187 & 125.527083333333 & 1.03044799512074 & 0.972175063593341 \tabularnewline
35 & 126.89 & 124.898929661014 & 124.996666666667 & 0.999218083103665 & 1.01594145237585 \tabularnewline
36 & 126.6 & 122.808870062579 & 124.63375 & 0.985358059615301 & 1.03087016382033 \tabularnewline
37 & 121.89 & 120.635013683395 & 124.4125 & 0.969637405271937 & 1.01040316802134 \tabularnewline
38 & 123.44 & 125.064441221275 & 124.315416666667 & 1.0060251944183 & 0.987011166360218 \tabularnewline
39 & 126.46 & 128.868098490126 & 124.461666666667 & 1.03540392750211 & 0.981313463003334 \tabularnewline
40 & 129.49 & 130.995074904374 & 124.875 & 1.04900960884383 & 0.988510446629596 \tabularnewline
41 & 127.78 & 127.714353450908 & 125.374166666667 & 1.01866562184587 & 1.00051401073817 \tabularnewline
42 & 125.29 & 123.798048700146 & 125.967916666667 & 0.98277443952445 & 1.01205149285889 \tabularnewline
43 & 119.02 & 121.783449811341 & 126.935833333333 & 0.959409542706017 & 0.977308494580984 \tabularnewline
44 & 119.96 & 125.991738469144 & 128.357083333333 & 0.98157215166656 & 0.952125920775186 \tabularnewline
45 & 122.86 & 127.633303766402 & 129.909583333333 & 0.982477970381214 & 0.962601424349724 \tabularnewline
46 & 131.89 & 135.299539172678 & 131.301666666667 & 1.03044799512074 & 0.97480006810425 \tabularnewline
47 & 132.73 & 132.298555907265 & 132.402083333333 & 0.999218083103665 & 1.00326113984976 \tabularnewline
48 & 135.01 & 131.116259636852 & 133.064583333333 & 0.985358059615301 & 1.02969685357051 \tabularnewline
49 & 136.71 & 129.351649941204 & 133.402083333333 & 0.969637405271937 & 1.05688640277987 \tabularnewline
50 & 142.73 & 134.692521509023 & 133.885833333333 & 1.0060251944183 & 1.05967278955750 \tabularnewline
51 & 144.43 & 139.748036676657 & 134.969583333333 & 1.03540392750211 & 1.03350289159465 \tabularnewline
52 & 144.93 & 143.296898004753 & 136.602083333333 & 1.04900960884383 & 1.01139663187401 \tabularnewline
53 & 138.75 & 140.773646722972 & 138.194166666667 & 1.01866562184587 & 0.985624818493518 \tabularnewline
54 & 130.22 & 136.819400534495 & 139.2175 & 0.98277443952445 & 0.951765608468433 \tabularnewline
55 & 122.19 & NA & NA & 0.959409542706017 & NA \tabularnewline
56 & 128.4 & NA & NA & 0.98157215166656 & NA \tabularnewline
57 & 140.43 & NA & NA & 0.982477970381214 & NA \tabularnewline
58 & 153.5 & NA & NA & 1.03044799512074 & NA \tabularnewline
59 & 149.33 & NA & NA & 0.999218083103665 & NA \tabularnewline
60 & 142.97 & NA & NA & 0.985358059615301 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64108&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]126.51[/C][C]NA[/C][C]NA[/C][C]0.969637405271937[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]131.02[/C][C]NA[/C][C]NA[/C][C]1.0060251944183[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]136.51[/C][C]NA[/C][C]NA[/C][C]1.03540392750211[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]138.04[/C][C]NA[/C][C]NA[/C][C]1.04900960884383[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]132.92[/C][C]NA[/C][C]NA[/C][C]1.01866562184587[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]129.61[/C][C]NA[/C][C]NA[/C][C]0.98277443952445[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]122.96[/C][C]120.961555636422[/C][C]126.079166666667[/C][C]0.959409542706017[/C][C]1.01652131830699[/C][/ROW]
[ROW][C]8[/C][C]124.04[/C][C]122.888334516291[/C][C]125.195416666667[/C][C]0.98157215166656[/C][C]1.00937164205408[/C][/ROW]
[ROW][C]9[/C][C]121.29[/C][C]122.341431798437[/C][C]124.523333333333[/C][C]0.982477970381214[/C][C]0.991405758597227[/C][/ROW]
[ROW][C]10[/C][C]124.56[/C][C]127.708142921957[/C][C]123.934583333333[/C][C]1.03044799512074[/C][C]0.97534892568377[/C][/ROW]
[ROW][C]11[/C][C]118.53[/C][C]123.394273764207[/C][C]123.490833333333[/C][C]0.999218083103665[/C][C]0.96057942061799[/C][/ROW]
[ROW][C]12[/C][C]113.14[/C][C]121.472067628367[/C][C]123.277083333333[/C][C]0.985358059615301[/C][C]0.931407542564778[/C][/ROW]
[ROW][C]13[/C][C]114.15[/C][C]119.636691171550[/C][C]123.382916666667[/C][C]0.969637405271937[/C][C]0.954138725186885[/C][/ROW]
[ROW][C]14[/C][C]122.17[/C][C]124.879164914637[/C][C]124.13125[/C][C]1.0060251944183[/C][C]0.97830570923109[/C][/ROW]
[ROW][C]15[/C][C]129.23[/C][C]129.963469561762[/C][C]125.519583333333[/C][C]1.03540392750211[/C][C]0.994356340560655[/C][/ROW]
[ROW][C]16[/C][C]131.19[/C][C]133.485161463367[/C][C]127.24875[/C][C]1.04900960884383[/C][C]0.982805868171371[/C][/ROW]
[ROW][C]17[/C][C]129.12[/C][C]131.274165355250[/C][C]128.86875[/C][C]1.01866562184587[/C][C]0.983590332877602[/C][/ROW]
[ROW][C]18[/C][C]128.28[/C][C]128.094820447617[/C][C]130.34[/C][C]0.98277443952445[/C][C]1.00144564434172[/C][/ROW]
[ROW][C]19[/C][C]126.83[/C][C]126.258695574088[/C][C]131.600416666667[/C][C]0.959409542706017[/C][C]1.00452487191725[/C][/ROW]
[ROW][C]20[/C][C]138.13[/C][C]129.926206843741[/C][C]132.365416666667[/C][C]0.98157215166656[/C][C]1.06314194307332[/C][/ROW]
[ROW][C]21[/C][C]140.52[/C][C]130.489449099465[/C][C]132.816666666667[/C][C]0.982477970381214[/C][C]1.0768686738258[/C][/ROW]
[ROW][C]22[/C][C]146.83[/C][C]137.272417730003[/C][C]133.21625[/C][C]1.03044799512074[/C][C]1.06962492850382[/C][/ROW]
[ROW][C]23[/C][C]135.14[/C][C]133.515520264312[/C][C]133.62[/C][C]0.999218083103665[/C][C]1.01216697304158[/C][/ROW]
[ROW][C]24[/C][C]131.84[/C][C]131.843371771676[/C][C]133.8025[/C][C]0.985358059615301[/C][C]0.999974425929563[/C][/ROW]
[ROW][C]25[/C][C]125.7[/C][C]129.518104362442[/C][C]133.57375[/C][C]0.969637405271937[/C][C]0.970520689897083[/C][/ROW]
[ROW][C]26[/C][C]128.98[/C][C]133.387203819265[/C][C]132.588333333333[/C][C]1.0060251944183[/C][C]0.966959320736367[/C][/ROW]
[ROW][C]27[/C][C]133.25[/C][C]135.585281469796[/C][C]130.949166666667[/C][C]1.03540392750211[/C][C]0.982776290726542[/C][/ROW]
[ROW][C]28[/C][C]136.76[/C][C]135.508438746424[/C][C]129.1775[/C][C]1.04900960884383[/C][C]1.00923603921020[/C][/ROW]
[ROW][C]29[/C][C]133.24[/C][C]130.343784087298[/C][C]127.955416666667[/C][C]1.01866562184587[/C][C]1.02221982377589[/C][/ROW]
[ROW][C]30[/C][C]128.54[/C][C]125.198911765818[/C][C]127.393333333333[/C][C]0.98277443952445[/C][C]1.02668624021614[/C][/ROW]
[ROW][C]31[/C][C]121.08[/C][C]121.860602328733[/C][C]127.01625[/C][C]0.959409542706017[/C][C]0.993594301079955[/C][/ROW]
[ROW][C]32[/C][C]120.23[/C][C]124.293209658364[/C][C]126.626666666667[/C][C]0.98157215166656[/C][C]0.967309479982596[/C][/ROW]
[ROW][C]33[/C][C]119.08[/C][C]123.903162405522[/C][C]126.112916666667[/C][C]0.982477970381214[/C][C]0.961073129112427[/C][/ROW]
[ROW][C]34[/C][C]125.75[/C][C]129.349131354187[/C][C]125.527083333333[/C][C]1.03044799512074[/C][C]0.972175063593341[/C][/ROW]
[ROW][C]35[/C][C]126.89[/C][C]124.898929661014[/C][C]124.996666666667[/C][C]0.999218083103665[/C][C]1.01594145237585[/C][/ROW]
[ROW][C]36[/C][C]126.6[/C][C]122.808870062579[/C][C]124.63375[/C][C]0.985358059615301[/C][C]1.03087016382033[/C][/ROW]
[ROW][C]37[/C][C]121.89[/C][C]120.635013683395[/C][C]124.4125[/C][C]0.969637405271937[/C][C]1.01040316802134[/C][/ROW]
[ROW][C]38[/C][C]123.44[/C][C]125.064441221275[/C][C]124.315416666667[/C][C]1.0060251944183[/C][C]0.987011166360218[/C][/ROW]
[ROW][C]39[/C][C]126.46[/C][C]128.868098490126[/C][C]124.461666666667[/C][C]1.03540392750211[/C][C]0.981313463003334[/C][/ROW]
[ROW][C]40[/C][C]129.49[/C][C]130.995074904374[/C][C]124.875[/C][C]1.04900960884383[/C][C]0.988510446629596[/C][/ROW]
[ROW][C]41[/C][C]127.78[/C][C]127.714353450908[/C][C]125.374166666667[/C][C]1.01866562184587[/C][C]1.00051401073817[/C][/ROW]
[ROW][C]42[/C][C]125.29[/C][C]123.798048700146[/C][C]125.967916666667[/C][C]0.98277443952445[/C][C]1.01205149285889[/C][/ROW]
[ROW][C]43[/C][C]119.02[/C][C]121.783449811341[/C][C]126.935833333333[/C][C]0.959409542706017[/C][C]0.977308494580984[/C][/ROW]
[ROW][C]44[/C][C]119.96[/C][C]125.991738469144[/C][C]128.357083333333[/C][C]0.98157215166656[/C][C]0.952125920775186[/C][/ROW]
[ROW][C]45[/C][C]122.86[/C][C]127.633303766402[/C][C]129.909583333333[/C][C]0.982477970381214[/C][C]0.962601424349724[/C][/ROW]
[ROW][C]46[/C][C]131.89[/C][C]135.299539172678[/C][C]131.301666666667[/C][C]1.03044799512074[/C][C]0.97480006810425[/C][/ROW]
[ROW][C]47[/C][C]132.73[/C][C]132.298555907265[/C][C]132.402083333333[/C][C]0.999218083103665[/C][C]1.00326113984976[/C][/ROW]
[ROW][C]48[/C][C]135.01[/C][C]131.116259636852[/C][C]133.064583333333[/C][C]0.985358059615301[/C][C]1.02969685357051[/C][/ROW]
[ROW][C]49[/C][C]136.71[/C][C]129.351649941204[/C][C]133.402083333333[/C][C]0.969637405271937[/C][C]1.05688640277987[/C][/ROW]
[ROW][C]50[/C][C]142.73[/C][C]134.692521509023[/C][C]133.885833333333[/C][C]1.0060251944183[/C][C]1.05967278955750[/C][/ROW]
[ROW][C]51[/C][C]144.43[/C][C]139.748036676657[/C][C]134.969583333333[/C][C]1.03540392750211[/C][C]1.03350289159465[/C][/ROW]
[ROW][C]52[/C][C]144.93[/C][C]143.296898004753[/C][C]136.602083333333[/C][C]1.04900960884383[/C][C]1.01139663187401[/C][/ROW]
[ROW][C]53[/C][C]138.75[/C][C]140.773646722972[/C][C]138.194166666667[/C][C]1.01866562184587[/C][C]0.985624818493518[/C][/ROW]
[ROW][C]54[/C][C]130.22[/C][C]136.819400534495[/C][C]139.2175[/C][C]0.98277443952445[/C][C]0.951765608468433[/C][/ROW]
[ROW][C]55[/C][C]122.19[/C][C]NA[/C][C]NA[/C][C]0.959409542706017[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]128.4[/C][C]NA[/C][C]NA[/C][C]0.98157215166656[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]140.43[/C][C]NA[/C][C]NA[/C][C]0.982477970381214[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]153.5[/C][C]NA[/C][C]NA[/C][C]1.03044799512074[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]149.33[/C][C]NA[/C][C]NA[/C][C]0.999218083103665[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]142.97[/C][C]NA[/C][C]NA[/C][C]0.985358059615301[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64108&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	126.51	NA	NA	0.969637405271937	NA
2	131.02	NA	NA	1.0060251944183	NA
3	136.51	NA	NA	1.03540392750211	NA
4	138.04	NA	NA	1.04900960884383	NA
5	132.92	NA	NA	1.01866562184587	NA
6	129.61	NA	NA	0.98277443952445	NA
7	122.96	120.961555636422	126.079166666667	0.959409542706017	1.01652131830699
8	124.04	122.888334516291	125.195416666667	0.98157215166656	1.00937164205408
9	121.29	122.341431798437	124.523333333333	0.982477970381214	0.991405758597227
10	124.56	127.708142921957	123.934583333333	1.03044799512074	0.97534892568377
11	118.53	123.394273764207	123.490833333333	0.999218083103665	0.96057942061799
12	113.14	121.472067628367	123.277083333333	0.985358059615301	0.931407542564778
13	114.15	119.636691171550	123.382916666667	0.969637405271937	0.954138725186885
14	122.17	124.879164914637	124.13125	1.0060251944183	0.97830570923109
15	129.23	129.963469561762	125.519583333333	1.03540392750211	0.994356340560655
16	131.19	133.485161463367	127.24875	1.04900960884383	0.982805868171371
17	129.12	131.274165355250	128.86875	1.01866562184587	0.983590332877602
18	128.28	128.094820447617	130.34	0.98277443952445	1.00144564434172
19	126.83	126.258695574088	131.600416666667	0.959409542706017	1.00452487191725
20	138.13	129.926206843741	132.365416666667	0.98157215166656	1.06314194307332
21	140.52	130.489449099465	132.816666666667	0.982477970381214	1.0768686738258
22	146.83	137.272417730003	133.21625	1.03044799512074	1.06962492850382
23	135.14	133.515520264312	133.62	0.999218083103665	1.01216697304158
24	131.84	131.843371771676	133.8025	0.985358059615301	0.999974425929563
25	125.7	129.518104362442	133.57375	0.969637405271937	0.970520689897083
26	128.98	133.387203819265	132.588333333333	1.0060251944183	0.966959320736367
27	133.25	135.585281469796	130.949166666667	1.03540392750211	0.982776290726542
28	136.76	135.508438746424	129.1775	1.04900960884383	1.00923603921020
29	133.24	130.343784087298	127.955416666667	1.01866562184587	1.02221982377589
30	128.54	125.198911765818	127.393333333333	0.98277443952445	1.02668624021614
31	121.08	121.860602328733	127.01625	0.959409542706017	0.993594301079955
32	120.23	124.293209658364	126.626666666667	0.98157215166656	0.967309479982596
33	119.08	123.903162405522	126.112916666667	0.982477970381214	0.961073129112427
34	125.75	129.349131354187	125.527083333333	1.03044799512074	0.972175063593341
35	126.89	124.898929661014	124.996666666667	0.999218083103665	1.01594145237585
36	126.6	122.808870062579	124.63375	0.985358059615301	1.03087016382033
37	121.89	120.635013683395	124.4125	0.969637405271937	1.01040316802134
38	123.44	125.064441221275	124.315416666667	1.0060251944183	0.987011166360218
39	126.46	128.868098490126	124.461666666667	1.03540392750211	0.981313463003334
40	129.49	130.995074904374	124.875	1.04900960884383	0.988510446629596
41	127.78	127.714353450908	125.374166666667	1.01866562184587	1.00051401073817
42	125.29	123.798048700146	125.967916666667	0.98277443952445	1.01205149285889
43	119.02	121.783449811341	126.935833333333	0.959409542706017	0.977308494580984
44	119.96	125.991738469144	128.357083333333	0.98157215166656	0.952125920775186
45	122.86	127.633303766402	129.909583333333	0.982477970381214	0.962601424349724
46	131.89	135.299539172678	131.301666666667	1.03044799512074	0.97480006810425
47	132.73	132.298555907265	132.402083333333	0.999218083103665	1.00326113984976
48	135.01	131.116259636852	133.064583333333	0.985358059615301	1.02969685357051
49	136.71	129.351649941204	133.402083333333	0.969637405271937	1.05688640277987
50	142.73	134.692521509023	133.885833333333	1.0060251944183	1.05967278955750
51	144.43	139.748036676657	134.969583333333	1.03540392750211	1.03350289159465
52	144.93	143.296898004753	136.602083333333	1.04900960884383	1.01139663187401
53	138.75	140.773646722972	138.194166666667	1.01866562184587	0.985624818493518
54	130.22	136.819400534495	139.2175	0.98277443952445	0.951765608468433
55	122.19	NA	NA	0.959409542706017	NA
56	128.4	NA	NA	0.98157215166656	NA
57	140.43	NA	NA	0.982477970381214	NA
58	153.5	NA	NA	1.03044799512074	NA
59	149.33	NA	NA	0.999218083103665	NA
60	142.97	NA	NA	0.985358059615301	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 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

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