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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 05:26:32 -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/t12599296814qhlsr9zd2uavkh.htm/, Retrieved Sat, 27 Apr 2024 20:51:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63405, Retrieved Sat, 27 Apr 2024 20:51:49 +0000

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Estimated Impact

108

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] [] [2009-12-04 12:26:32] [026d431dc78a3ce53a040b5408fc0322] [Current]
-    D        [Classical Decomposition] [ws9 AD-HOC Foreca...] [2009-12-04 15:31:13] [af8eb90b4bf1bcfcc4325c143dbee260] 
-    D          [Classical Decomposition] [ADHOCForecasting(1)] [2009-12-09 17:49:53] [aba88da643e3763d32ff92bd8f92a385] 

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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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63405&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63405&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63405&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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	111.5	NA	NA	0.970345123254729	NA
2	108.1	NA	NA	0.997393067626448	NA
3	124.5	NA	NA	1.04265743467351	NA
4	106.3	NA	NA	0.930855956060765	NA
5	111.1	NA	NA	0.999731638887545	NA
6	121.3	NA	NA	1.05364263259105	NA
7	116.5	120.004807543497	113.75	1.05498731906371	0.97079444052917
8	117.4	120.033066346249	114.0625	1.05234469125478	0.978063825024238
9	123.6	118.529247348539	114.354166666667	1.03651008794496	1.04278060280388
10	98.4	103.635613336888	114.279166666667	0.906863572423273	0.949480558195101
11	107.2	106.146330518168	114.454166666667	0.92741342329027	1.00992657472649
12	118.9	118.035885810925	114.904166666667	1.02725505292896	1.00732077522983
13	111.9	111.735240942782	115.15	0.970345123254729	1.00147454872633
14	115.2	115.090848395195	115.391666666667	0.997393067626448	1.00094839517066
15	124.4	120.544232666191	115.6125	1.04265743467351	1.03198632774482
16	104.6	107.924990972279	115.941666666667	0.930855956060765	0.969191649289713
17	117	116.231299666163	116.2625	0.999731638887545	1.00661353986443
18	126.2	122.806439006123	116.554166666667	1.05364263259105	1.02763341255835
19	117.5	123.266476671602	116.841666666667	1.05498731906371	0.953219424880902
20	122.2	123.181330880919	117.054166666667	1.05234469125478	0.99203344472818
21	124.1	121.807210501665	117.516666666667	1.03651008794496	1.01882310159548
22	105.8	107.002344349509	117.991666666667	0.906863572423273	0.988763383112598
23	107.5	109.825070430553	118.420833333333	0.92741342329027	0.97882932902808
24	125.6	122.00793868225	118.770833333333	1.02725505292896	1.02944120978148
25	112.1	115.972414647661	119.516666666667	0.970345123254729	0.9666091746091
26	120.1	120.273136542404	120.5875	0.997393067626448	0.998560472044036
27	130.6	126.400491924274	121.229166666667	1.04265743467351	1.03322382699461
28	109.8	113.358862615783	121.779166666667	0.930855956060765	0.968605342946624
29	122.1	122.392145890808	122.425	0.999731638887545	0.997613034000823
30	129.5	129.778041091767	123.170833333333	1.05364263259105	0.997857564427483
31	132.1	130.937113637295	124.1125	1.05498731906371	1.00888125857063
32	133.3	131.714092419177	125.1625	1.05234469125478	1.01204053075639
33	128.4	130.608908665131	126.008333333333	1.03651008794496	0.983087611038888
34	114.7	115.194345287066	127.025	0.906863572423273	0.995708597624004
35	114.1	119.195810228382	128.525	0.92741342329027	0.957248411511962
36	136.9	133.264941970596	129.729166666667	1.02725505292896	1.02727692651685
37	123.4	127.361840531863	131.254166666667	0.970345123254729	0.968893033303235
38	134	132.748861496632	133.095833333333	0.997393067626448	1.00942485298377
39	137	140.128814814142	134.395833333333	1.04265743467351	0.977671867001146
40	127.8	126.530474394043	135.929166666667	0.930855956060765	1.01003335846196
41	140.1	138.021283845416	138.058333333333	0.999731638887545	1.01506083769596
42	140.4	146.763638364662	139.291666666667	1.05364263259105	0.95664022481611
43	157.8	148.265280352916	140.5375	1.05498731906371	1.06430851258223
44	151.8	149.546950166398	142.108333333333	1.05234469125478	1.01506583605413
45	141.1	148.134566735467	142.916666666667	1.03651008794496	0.95251232112469
46	138.8	130.54301125033	143.95	0.906863572423273	1.06325109763123
47	141.1	134.227636130878	144.733333333333	0.92741342329027	1.05119932129640
48	139.5	149.491291577487	145.525	1.02725505292896	0.933164725034783
49	150.7	142.139388138097	146.483333333333	0.970345123254729	1.06022687992428
50	144.4	146.113928602826	146.495833333333	0.997393067626448	0.988269916364476
51	146	152.988256508449	146.729166666667	1.04265743467351	0.95432161482236
52	143.6	136.843582673900	147.008333333333	0.930855956060765	1.04937328586464
53	143.1	146.331553093669	146.370833333333	0.999731638887545	0.977916225001723
54	156.4	154.077674305898	146.233333333333	1.05364263259105	1.015072434761
55	164.8	NA	NA	1.05498731906371	NA
56	145.1	NA	NA	1.05234469125478	NA
57	153.4	NA	NA	1.03651008794496	NA
58	133.2	NA	NA	0.906863572423273	NA
59	131.4	NA	NA	0.92741342329027	NA
60	145.9	NA	NA	1.02725505292896	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 111.5 & NA & NA & 0.970345123254729 & NA \tabularnewline
2 & 108.1 & NA & NA & 0.997393067626448 & NA \tabularnewline
3 & 124.5 & NA & NA & 1.04265743467351 & NA \tabularnewline
4 & 106.3 & NA & NA & 0.930855956060765 & NA \tabularnewline
5 & 111.1 & NA & NA & 0.999731638887545 & NA \tabularnewline
6 & 121.3 & NA & NA & 1.05364263259105 & NA \tabularnewline
7 & 116.5 & 120.004807543497 & 113.75 & 1.05498731906371 & 0.97079444052917 \tabularnewline
8 & 117.4 & 120.033066346249 & 114.0625 & 1.05234469125478 & 0.978063825024238 \tabularnewline
9 & 123.6 & 118.529247348539 & 114.354166666667 & 1.03651008794496 & 1.04278060280388 \tabularnewline
10 & 98.4 & 103.635613336888 & 114.279166666667 & 0.906863572423273 & 0.949480558195101 \tabularnewline
11 & 107.2 & 106.146330518168 & 114.454166666667 & 0.92741342329027 & 1.00992657472649 \tabularnewline
12 & 118.9 & 118.035885810925 & 114.904166666667 & 1.02725505292896 & 1.00732077522983 \tabularnewline
13 & 111.9 & 111.735240942782 & 115.15 & 0.970345123254729 & 1.00147454872633 \tabularnewline
14 & 115.2 & 115.090848395195 & 115.391666666667 & 0.997393067626448 & 1.00094839517066 \tabularnewline
15 & 124.4 & 120.544232666191 & 115.6125 & 1.04265743467351 & 1.03198632774482 \tabularnewline
16 & 104.6 & 107.924990972279 & 115.941666666667 & 0.930855956060765 & 0.969191649289713 \tabularnewline
17 & 117 & 116.231299666163 & 116.2625 & 0.999731638887545 & 1.00661353986443 \tabularnewline
18 & 126.2 & 122.806439006123 & 116.554166666667 & 1.05364263259105 & 1.02763341255835 \tabularnewline
19 & 117.5 & 123.266476671602 & 116.841666666667 & 1.05498731906371 & 0.953219424880902 \tabularnewline
20 & 122.2 & 123.181330880919 & 117.054166666667 & 1.05234469125478 & 0.99203344472818 \tabularnewline
21 & 124.1 & 121.807210501665 & 117.516666666667 & 1.03651008794496 & 1.01882310159548 \tabularnewline
22 & 105.8 & 107.002344349509 & 117.991666666667 & 0.906863572423273 & 0.988763383112598 \tabularnewline
23 & 107.5 & 109.825070430553 & 118.420833333333 & 0.92741342329027 & 0.97882932902808 \tabularnewline
24 & 125.6 & 122.00793868225 & 118.770833333333 & 1.02725505292896 & 1.02944120978148 \tabularnewline
25 & 112.1 & 115.972414647661 & 119.516666666667 & 0.970345123254729 & 0.9666091746091 \tabularnewline
26 & 120.1 & 120.273136542404 & 120.5875 & 0.997393067626448 & 0.998560472044036 \tabularnewline
27 & 130.6 & 126.400491924274 & 121.229166666667 & 1.04265743467351 & 1.03322382699461 \tabularnewline
28 & 109.8 & 113.358862615783 & 121.779166666667 & 0.930855956060765 & 0.968605342946624 \tabularnewline
29 & 122.1 & 122.392145890808 & 122.425 & 0.999731638887545 & 0.997613034000823 \tabularnewline
30 & 129.5 & 129.778041091767 & 123.170833333333 & 1.05364263259105 & 0.997857564427483 \tabularnewline
31 & 132.1 & 130.937113637295 & 124.1125 & 1.05498731906371 & 1.00888125857063 \tabularnewline
32 & 133.3 & 131.714092419177 & 125.1625 & 1.05234469125478 & 1.01204053075639 \tabularnewline
33 & 128.4 & 130.608908665131 & 126.008333333333 & 1.03651008794496 & 0.983087611038888 \tabularnewline
34 & 114.7 & 115.194345287066 & 127.025 & 0.906863572423273 & 0.995708597624004 \tabularnewline
35 & 114.1 & 119.195810228382 & 128.525 & 0.92741342329027 & 0.957248411511962 \tabularnewline
36 & 136.9 & 133.264941970596 & 129.729166666667 & 1.02725505292896 & 1.02727692651685 \tabularnewline
37 & 123.4 & 127.361840531863 & 131.254166666667 & 0.970345123254729 & 0.968893033303235 \tabularnewline
38 & 134 & 132.748861496632 & 133.095833333333 & 0.997393067626448 & 1.00942485298377 \tabularnewline
39 & 137 & 140.128814814142 & 134.395833333333 & 1.04265743467351 & 0.977671867001146 \tabularnewline
40 & 127.8 & 126.530474394043 & 135.929166666667 & 0.930855956060765 & 1.01003335846196 \tabularnewline
41 & 140.1 & 138.021283845416 & 138.058333333333 & 0.999731638887545 & 1.01506083769596 \tabularnewline
42 & 140.4 & 146.763638364662 & 139.291666666667 & 1.05364263259105 & 0.95664022481611 \tabularnewline
43 & 157.8 & 148.265280352916 & 140.5375 & 1.05498731906371 & 1.06430851258223 \tabularnewline
44 & 151.8 & 149.546950166398 & 142.108333333333 & 1.05234469125478 & 1.01506583605413 \tabularnewline
45 & 141.1 & 148.134566735467 & 142.916666666667 & 1.03651008794496 & 0.95251232112469 \tabularnewline
46 & 138.8 & 130.54301125033 & 143.95 & 0.906863572423273 & 1.06325109763123 \tabularnewline
47 & 141.1 & 134.227636130878 & 144.733333333333 & 0.92741342329027 & 1.05119932129640 \tabularnewline
48 & 139.5 & 149.491291577487 & 145.525 & 1.02725505292896 & 0.933164725034783 \tabularnewline
49 & 150.7 & 142.139388138097 & 146.483333333333 & 0.970345123254729 & 1.06022687992428 \tabularnewline
50 & 144.4 & 146.113928602826 & 146.495833333333 & 0.997393067626448 & 0.988269916364476 \tabularnewline
51 & 146 & 152.988256508449 & 146.729166666667 & 1.04265743467351 & 0.95432161482236 \tabularnewline
52 & 143.6 & 136.843582673900 & 147.008333333333 & 0.930855956060765 & 1.04937328586464 \tabularnewline
53 & 143.1 & 146.331553093669 & 146.370833333333 & 0.999731638887545 & 0.977916225001723 \tabularnewline
54 & 156.4 & 154.077674305898 & 146.233333333333 & 1.05364263259105 & 1.015072434761 \tabularnewline
55 & 164.8 & NA & NA & 1.05498731906371 & NA \tabularnewline
56 & 145.1 & NA & NA & 1.05234469125478 & NA \tabularnewline
57 & 153.4 & NA & NA & 1.03651008794496 & NA \tabularnewline
58 & 133.2 & NA & NA & 0.906863572423273 & NA \tabularnewline
59 & 131.4 & NA & NA & 0.92741342329027 & NA \tabularnewline
60 & 145.9 & NA & NA & 1.02725505292896 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63405&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]111.5[/C][C]NA[/C][C]NA[/C][C]0.970345123254729[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]108.1[/C][C]NA[/C][C]NA[/C][C]0.997393067626448[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]124.5[/C][C]NA[/C][C]NA[/C][C]1.04265743467351[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]106.3[/C][C]NA[/C][C]NA[/C][C]0.930855956060765[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]111.1[/C][C]NA[/C][C]NA[/C][C]0.999731638887545[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]121.3[/C][C]NA[/C][C]NA[/C][C]1.05364263259105[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]116.5[/C][C]120.004807543497[/C][C]113.75[/C][C]1.05498731906371[/C][C]0.97079444052917[/C][/ROW]
[ROW][C]8[/C][C]117.4[/C][C]120.033066346249[/C][C]114.0625[/C][C]1.05234469125478[/C][C]0.978063825024238[/C][/ROW]
[ROW][C]9[/C][C]123.6[/C][C]118.529247348539[/C][C]114.354166666667[/C][C]1.03651008794496[/C][C]1.04278060280388[/C][/ROW]
[ROW][C]10[/C][C]98.4[/C][C]103.635613336888[/C][C]114.279166666667[/C][C]0.906863572423273[/C][C]0.949480558195101[/C][/ROW]
[ROW][C]11[/C][C]107.2[/C][C]106.146330518168[/C][C]114.454166666667[/C][C]0.92741342329027[/C][C]1.00992657472649[/C][/ROW]
[ROW][C]12[/C][C]118.9[/C][C]118.035885810925[/C][C]114.904166666667[/C][C]1.02725505292896[/C][C]1.00732077522983[/C][/ROW]
[ROW][C]13[/C][C]111.9[/C][C]111.735240942782[/C][C]115.15[/C][C]0.970345123254729[/C][C]1.00147454872633[/C][/ROW]
[ROW][C]14[/C][C]115.2[/C][C]115.090848395195[/C][C]115.391666666667[/C][C]0.997393067626448[/C][C]1.00094839517066[/C][/ROW]
[ROW][C]15[/C][C]124.4[/C][C]120.544232666191[/C][C]115.6125[/C][C]1.04265743467351[/C][C]1.03198632774482[/C][/ROW]
[ROW][C]16[/C][C]104.6[/C][C]107.924990972279[/C][C]115.941666666667[/C][C]0.930855956060765[/C][C]0.969191649289713[/C][/ROW]
[ROW][C]17[/C][C]117[/C][C]116.231299666163[/C][C]116.2625[/C][C]0.999731638887545[/C][C]1.00661353986443[/C][/ROW]
[ROW][C]18[/C][C]126.2[/C][C]122.806439006123[/C][C]116.554166666667[/C][C]1.05364263259105[/C][C]1.02763341255835[/C][/ROW]
[ROW][C]19[/C][C]117.5[/C][C]123.266476671602[/C][C]116.841666666667[/C][C]1.05498731906371[/C][C]0.953219424880902[/C][/ROW]
[ROW][C]20[/C][C]122.2[/C][C]123.181330880919[/C][C]117.054166666667[/C][C]1.05234469125478[/C][C]0.99203344472818[/C][/ROW]
[ROW][C]21[/C][C]124.1[/C][C]121.807210501665[/C][C]117.516666666667[/C][C]1.03651008794496[/C][C]1.01882310159548[/C][/ROW]
[ROW][C]22[/C][C]105.8[/C][C]107.002344349509[/C][C]117.991666666667[/C][C]0.906863572423273[/C][C]0.988763383112598[/C][/ROW]
[ROW][C]23[/C][C]107.5[/C][C]109.825070430553[/C][C]118.420833333333[/C][C]0.92741342329027[/C][C]0.97882932902808[/C][/ROW]
[ROW][C]24[/C][C]125.6[/C][C]122.00793868225[/C][C]118.770833333333[/C][C]1.02725505292896[/C][C]1.02944120978148[/C][/ROW]
[ROW][C]25[/C][C]112.1[/C][C]115.972414647661[/C][C]119.516666666667[/C][C]0.970345123254729[/C][C]0.9666091746091[/C][/ROW]
[ROW][C]26[/C][C]120.1[/C][C]120.273136542404[/C][C]120.5875[/C][C]0.997393067626448[/C][C]0.998560472044036[/C][/ROW]
[ROW][C]27[/C][C]130.6[/C][C]126.400491924274[/C][C]121.229166666667[/C][C]1.04265743467351[/C][C]1.03322382699461[/C][/ROW]
[ROW][C]28[/C][C]109.8[/C][C]113.358862615783[/C][C]121.779166666667[/C][C]0.930855956060765[/C][C]0.968605342946624[/C][/ROW]
[ROW][C]29[/C][C]122.1[/C][C]122.392145890808[/C][C]122.425[/C][C]0.999731638887545[/C][C]0.997613034000823[/C][/ROW]
[ROW][C]30[/C][C]129.5[/C][C]129.778041091767[/C][C]123.170833333333[/C][C]1.05364263259105[/C][C]0.997857564427483[/C][/ROW]
[ROW][C]31[/C][C]132.1[/C][C]130.937113637295[/C][C]124.1125[/C][C]1.05498731906371[/C][C]1.00888125857063[/C][/ROW]
[ROW][C]32[/C][C]133.3[/C][C]131.714092419177[/C][C]125.1625[/C][C]1.05234469125478[/C][C]1.01204053075639[/C][/ROW]
[ROW][C]33[/C][C]128.4[/C][C]130.608908665131[/C][C]126.008333333333[/C][C]1.03651008794496[/C][C]0.983087611038888[/C][/ROW]
[ROW][C]34[/C][C]114.7[/C][C]115.194345287066[/C][C]127.025[/C][C]0.906863572423273[/C][C]0.995708597624004[/C][/ROW]
[ROW][C]35[/C][C]114.1[/C][C]119.195810228382[/C][C]128.525[/C][C]0.92741342329027[/C][C]0.957248411511962[/C][/ROW]
[ROW][C]36[/C][C]136.9[/C][C]133.264941970596[/C][C]129.729166666667[/C][C]1.02725505292896[/C][C]1.02727692651685[/C][/ROW]
[ROW][C]37[/C][C]123.4[/C][C]127.361840531863[/C][C]131.254166666667[/C][C]0.970345123254729[/C][C]0.968893033303235[/C][/ROW]
[ROW][C]38[/C][C]134[/C][C]132.748861496632[/C][C]133.095833333333[/C][C]0.997393067626448[/C][C]1.00942485298377[/C][/ROW]
[ROW][C]39[/C][C]137[/C][C]140.128814814142[/C][C]134.395833333333[/C][C]1.04265743467351[/C][C]0.977671867001146[/C][/ROW]
[ROW][C]40[/C][C]127.8[/C][C]126.530474394043[/C][C]135.929166666667[/C][C]0.930855956060765[/C][C]1.01003335846196[/C][/ROW]
[ROW][C]41[/C][C]140.1[/C][C]138.021283845416[/C][C]138.058333333333[/C][C]0.999731638887545[/C][C]1.01506083769596[/C][/ROW]
[ROW][C]42[/C][C]140.4[/C][C]146.763638364662[/C][C]139.291666666667[/C][C]1.05364263259105[/C][C]0.95664022481611[/C][/ROW]
[ROW][C]43[/C][C]157.8[/C][C]148.265280352916[/C][C]140.5375[/C][C]1.05498731906371[/C][C]1.06430851258223[/C][/ROW]
[ROW][C]44[/C][C]151.8[/C][C]149.546950166398[/C][C]142.108333333333[/C][C]1.05234469125478[/C][C]1.01506583605413[/C][/ROW]
[ROW][C]45[/C][C]141.1[/C][C]148.134566735467[/C][C]142.916666666667[/C][C]1.03651008794496[/C][C]0.95251232112469[/C][/ROW]
[ROW][C]46[/C][C]138.8[/C][C]130.54301125033[/C][C]143.95[/C][C]0.906863572423273[/C][C]1.06325109763123[/C][/ROW]
[ROW][C]47[/C][C]141.1[/C][C]134.227636130878[/C][C]144.733333333333[/C][C]0.92741342329027[/C][C]1.05119932129640[/C][/ROW]
[ROW][C]48[/C][C]139.5[/C][C]149.491291577487[/C][C]145.525[/C][C]1.02725505292896[/C][C]0.933164725034783[/C][/ROW]
[ROW][C]49[/C][C]150.7[/C][C]142.139388138097[/C][C]146.483333333333[/C][C]0.970345123254729[/C][C]1.06022687992428[/C][/ROW]
[ROW][C]50[/C][C]144.4[/C][C]146.113928602826[/C][C]146.495833333333[/C][C]0.997393067626448[/C][C]0.988269916364476[/C][/ROW]
[ROW][C]51[/C][C]146[/C][C]152.988256508449[/C][C]146.729166666667[/C][C]1.04265743467351[/C][C]0.95432161482236[/C][/ROW]
[ROW][C]52[/C][C]143.6[/C][C]136.843582673900[/C][C]147.008333333333[/C][C]0.930855956060765[/C][C]1.04937328586464[/C][/ROW]
[ROW][C]53[/C][C]143.1[/C][C]146.331553093669[/C][C]146.370833333333[/C][C]0.999731638887545[/C][C]0.977916225001723[/C][/ROW]
[ROW][C]54[/C][C]156.4[/C][C]154.077674305898[/C][C]146.233333333333[/C][C]1.05364263259105[/C][C]1.015072434761[/C][/ROW]
[ROW][C]55[/C][C]164.8[/C][C]NA[/C][C]NA[/C][C]1.05498731906371[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]145.1[/C][C]NA[/C][C]NA[/C][C]1.05234469125478[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]153.4[/C][C]NA[/C][C]NA[/C][C]1.03651008794496[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]133.2[/C][C]NA[/C][C]NA[/C][C]0.906863572423273[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]131.4[/C][C]NA[/C][C]NA[/C][C]0.92741342329027[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]145.9[/C][C]NA[/C][C]NA[/C][C]1.02725505292896[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63405&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63405&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	111.5	NA	NA	0.970345123254729	NA
2	108.1	NA	NA	0.997393067626448	NA
3	124.5	NA	NA	1.04265743467351	NA
4	106.3	NA	NA	0.930855956060765	NA
5	111.1	NA	NA	0.999731638887545	NA
6	121.3	NA	NA	1.05364263259105	NA
7	116.5	120.004807543497	113.75	1.05498731906371	0.97079444052917
8	117.4	120.033066346249	114.0625	1.05234469125478	0.978063825024238
9	123.6	118.529247348539	114.354166666667	1.03651008794496	1.04278060280388
10	98.4	103.635613336888	114.279166666667	0.906863572423273	0.949480558195101
11	107.2	106.146330518168	114.454166666667	0.92741342329027	1.00992657472649
12	118.9	118.035885810925	114.904166666667	1.02725505292896	1.00732077522983
13	111.9	111.735240942782	115.15	0.970345123254729	1.00147454872633
14	115.2	115.090848395195	115.391666666667	0.997393067626448	1.00094839517066
15	124.4	120.544232666191	115.6125	1.04265743467351	1.03198632774482
16	104.6	107.924990972279	115.941666666667	0.930855956060765	0.969191649289713
17	117	116.231299666163	116.2625	0.999731638887545	1.00661353986443
18	126.2	122.806439006123	116.554166666667	1.05364263259105	1.02763341255835
19	117.5	123.266476671602	116.841666666667	1.05498731906371	0.953219424880902
20	122.2	123.181330880919	117.054166666667	1.05234469125478	0.99203344472818
21	124.1	121.807210501665	117.516666666667	1.03651008794496	1.01882310159548
22	105.8	107.002344349509	117.991666666667	0.906863572423273	0.988763383112598
23	107.5	109.825070430553	118.420833333333	0.92741342329027	0.97882932902808
24	125.6	122.00793868225	118.770833333333	1.02725505292896	1.02944120978148
25	112.1	115.972414647661	119.516666666667	0.970345123254729	0.9666091746091
26	120.1	120.273136542404	120.5875	0.997393067626448	0.998560472044036
27	130.6	126.400491924274	121.229166666667	1.04265743467351	1.03322382699461
28	109.8	113.358862615783	121.779166666667	0.930855956060765	0.968605342946624
29	122.1	122.392145890808	122.425	0.999731638887545	0.997613034000823
30	129.5	129.778041091767	123.170833333333	1.05364263259105	0.997857564427483
31	132.1	130.937113637295	124.1125	1.05498731906371	1.00888125857063
32	133.3	131.714092419177	125.1625	1.05234469125478	1.01204053075639
33	128.4	130.608908665131	126.008333333333	1.03651008794496	0.983087611038888
34	114.7	115.194345287066	127.025	0.906863572423273	0.995708597624004
35	114.1	119.195810228382	128.525	0.92741342329027	0.957248411511962
36	136.9	133.264941970596	129.729166666667	1.02725505292896	1.02727692651685
37	123.4	127.361840531863	131.254166666667	0.970345123254729	0.968893033303235
38	134	132.748861496632	133.095833333333	0.997393067626448	1.00942485298377
39	137	140.128814814142	134.395833333333	1.04265743467351	0.977671867001146
40	127.8	126.530474394043	135.929166666667	0.930855956060765	1.01003335846196
41	140.1	138.021283845416	138.058333333333	0.999731638887545	1.01506083769596
42	140.4	146.763638364662	139.291666666667	1.05364263259105	0.95664022481611
43	157.8	148.265280352916	140.5375	1.05498731906371	1.06430851258223
44	151.8	149.546950166398	142.108333333333	1.05234469125478	1.01506583605413
45	141.1	148.134566735467	142.916666666667	1.03651008794496	0.95251232112469
46	138.8	130.54301125033	143.95	0.906863572423273	1.06325109763123
47	141.1	134.227636130878	144.733333333333	0.92741342329027	1.05119932129640
48	139.5	149.491291577487	145.525	1.02725505292896	0.933164725034783
49	150.7	142.139388138097	146.483333333333	0.970345123254729	1.06022687992428
50	144.4	146.113928602826	146.495833333333	0.997393067626448	0.988269916364476
51	146	152.988256508449	146.729166666667	1.04265743467351	0.95432161482236
52	143.6	136.843582673900	147.008333333333	0.930855956060765	1.04937328586464
53	143.1	146.331553093669	146.370833333333	0.999731638887545	0.977916225001723
54	156.4	154.077674305898	146.233333333333	1.05364263259105	1.015072434761
55	164.8	NA	NA	1.05498731906371	NA
56	145.1	NA	NA	1.05234469125478	NA
57	153.4	NA	NA	1.03651008794496	NA
58	133.2	NA	NA	0.906863572423273	NA
59	131.4	NA	NA	0.92741342329027	NA
60	145.9	NA	NA	1.02725505292896	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