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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 May 2012 11:52:39 -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/04/t13361468288tidejqy57t2p7r.htm/, Retrieved Fri, 03 May 2024 09:30:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166205, Retrieved Fri, 03 May 2024 09:30:03 +0000

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Estimated Impact

146

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

-     [Classical Decomposition] [multiplicatief mo...] [2012-05-04 15:38:52] [74be16979710d4c4e7c6647856088456]
- R  D    [Classical Decomposition] [multiplicatief mo...] [2012-05-04 15:52:39] [e5023936a4a44f1411ffe7f6ed888868] [Current]
- R PD      [Classical Decomposition] [opdracht 9 verbet...] [2012-05-28 10:28:26] [a23b71380c738c5ecd118524e86d7af0] 

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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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166205&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166205&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166205&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' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	128.27	NA	NA	0.999111498852257	NA
2	128.38	NA	NA	1.00036304938694	NA
3	128.47	NA	NA	1.00016553237293	NA
4	128.52	NA	NA	0.999699037151439	NA
5	128.71	NA	NA	0.999604199617068	NA
6	128.92	NA	NA	0.999641313883786	NA
7	128.92	128.835958000421	128.826666666667	1.00007212275218	1.00065231788457
8	128.82	129.105234427832	128.919166666667	1.0014432901327	0.997790682700848
9	128.97	129.168910171344	129.035416666667	1.00103454933634	0.998460077033397
10	129.04	129.311835984849	129.162916666667	1.00115295722662	0.99789782595863
11	128.95	129.063321994329	129.2675	0.998420500081837	0.999121965926664
12	129.39	129.264242832821	129.355833333333	0.999291949205904	1.00097286894212
13	129.39	129.322494632689	129.4375	0.999111498852257	1.00052199246158
14	129.48	129.556601708165	129.509583333333	1.00036304938694	0.999408739445503
15	130.16	129.58603046626	129.564583333333	1.00016553237293	1.00442925469416
16	129.89	129.571408746463	129.610416666667	0.999699037151439	1.00245880828663
17	129.85	129.582024410359	129.633333333333	0.999604199617068	1.0020679997157
18	129.9	129.57184103676	129.618333333333	0.999641313883786	1.00253264104773
19	129.9	129.596012813712	129.586666666667	1.00007212275218	1.00234565230587
20	129.57	129.726129267715	129.539166666667	1.0014432901327	0.998796470159126
21	129.54	129.564735916061	129.430833333333	1.00103454933634	0.999809084502154
22	129.57	129.440734428092	129.291666666667	1.00115295722662	1.00099864677436
23	128.97	128.961815910154	129.165833333333	0.998420500081837	1.00006346134155
24	129.01	128.950298612112	129.041666666667	0.999291949205904	1.00046297983433
25	129.01	128.805454432033	128.92	0.999111498852257	1.00158801945825
26	128.72	128.865517568213	128.81875	1.00036304938694	0.998870779623911
27	128.32	128.747975097259	128.726666666667	1.00016553237293	0.996675869294754
28	128.39	128.594202937648	128.632916666667	0.999699037151439	0.998412036211718
29	128.33	128.499952864274	128.550833333333	0.999604199617068	0.998677409131401
30	128.44	128.423086560222	128.469166666667	0.999641313883786	1.00013170092879
31	128.44	128.395092872974	128.385833333333	1.00007212275218	1.0003497573468
32	128.6	128.510210206279	128.325	1.0014432901327	1.0006986977422
33	128.3	128.441074634431	128.308333333333	1.00103454933634	0.998901639254949
34	128.56	128.457518794683	128.309583333333	1.00115295722662	1.00079778284898
35	128.01	128.111910459459	128.314583333333	0.998420500081837	0.999204520023987
36	128.01	128.230808408684	128.321666666667	0.999291949205904	0.998278039330612
37	128.01	128.209317904385	128.323333333333	0.999111498852257	0.998445371150534
38	128.26	128.410769198679	128.364166666667	1.00036304938694	0.99882588353282
39	128.38	128.482097759903	128.460833333333	1.00016553237293	0.999205354195772
40	128.36	128.516726262269	128.555416666667	0.999699037151439	0.99878049910835
41	128.48	128.600746287735	128.651666666667	0.999604199617068	0.999061076306159
42	128.46	128.725061540457	128.77125	0.999641313883786	0.997940870741987
43	128.46	128.903046171989	128.89375	1.00007212275218	0.996562950332474
44	129.56	129.220817674235	129.034583333333	1.0014432901327	1.00262482726754
45	129.66	129.30571822642	129.172083333333	1.00103454933634	1.00273987707922
46	129.47	129.441985869289	129.292916666667	1.00115295722662	1.00021642228774
47	129.41	129.213501077883	129.417916666667	0.998420500081837	1.00152073057752
48	129.48	129.454524674815	129.54625	0.999291949205904	1.00019678976265
49	129.48	129.563530281787	129.67875	0.999111498852257	0.999355294799351
50	130.17	129.805858834637	129.75875	1.00036304938694	1.00280527526748
51	129.77	129.821902837644	129.800416666667	1.00016553237293	0.99960019968503
52	129.87	129.836328991309	129.875416666667	0.999699037151439	1.00025933426301
53	129.97	129.956459483466	130.007916666667	0.999604199617068	1.00010419271645
54	130.05	130.140387034031	130.187083333333	0.999641313883786	0.999305465151202
55	130.05	NA	NA	1.00007212275218	NA
56	129.89	NA	NA	1.0014432901327	NA
57	130.33	NA	NA	1.00103454933634	NA
58	130.6	NA	NA	1.00115295722662	NA
59	131.46	NA	NA	0.998420500081837	NA
60	131.73	NA	NA	0.999291949205904	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 128.27 & NA & NA & 0.999111498852257 & NA \tabularnewline
2 & 128.38 & NA & NA & 1.00036304938694 & NA \tabularnewline
3 & 128.47 & NA & NA & 1.00016553237293 & NA \tabularnewline
4 & 128.52 & NA & NA & 0.999699037151439 & NA \tabularnewline
5 & 128.71 & NA & NA & 0.999604199617068 & NA \tabularnewline
6 & 128.92 & NA & NA & 0.999641313883786 & NA \tabularnewline
7 & 128.92 & 128.835958000421 & 128.826666666667 & 1.00007212275218 & 1.00065231788457 \tabularnewline
8 & 128.82 & 129.105234427832 & 128.919166666667 & 1.0014432901327 & 0.997790682700848 \tabularnewline
9 & 128.97 & 129.168910171344 & 129.035416666667 & 1.00103454933634 & 0.998460077033397 \tabularnewline
10 & 129.04 & 129.311835984849 & 129.162916666667 & 1.00115295722662 & 0.99789782595863 \tabularnewline
11 & 128.95 & 129.063321994329 & 129.2675 & 0.998420500081837 & 0.999121965926664 \tabularnewline
12 & 129.39 & 129.264242832821 & 129.355833333333 & 0.999291949205904 & 1.00097286894212 \tabularnewline
13 & 129.39 & 129.322494632689 & 129.4375 & 0.999111498852257 & 1.00052199246158 \tabularnewline
14 & 129.48 & 129.556601708165 & 129.509583333333 & 1.00036304938694 & 0.999408739445503 \tabularnewline
15 & 130.16 & 129.58603046626 & 129.564583333333 & 1.00016553237293 & 1.00442925469416 \tabularnewline
16 & 129.89 & 129.571408746463 & 129.610416666667 & 0.999699037151439 & 1.00245880828663 \tabularnewline
17 & 129.85 & 129.582024410359 & 129.633333333333 & 0.999604199617068 & 1.0020679997157 \tabularnewline
18 & 129.9 & 129.57184103676 & 129.618333333333 & 0.999641313883786 & 1.00253264104773 \tabularnewline
19 & 129.9 & 129.596012813712 & 129.586666666667 & 1.00007212275218 & 1.00234565230587 \tabularnewline
20 & 129.57 & 129.726129267715 & 129.539166666667 & 1.0014432901327 & 0.998796470159126 \tabularnewline
21 & 129.54 & 129.564735916061 & 129.430833333333 & 1.00103454933634 & 0.999809084502154 \tabularnewline
22 & 129.57 & 129.440734428092 & 129.291666666667 & 1.00115295722662 & 1.00099864677436 \tabularnewline
23 & 128.97 & 128.961815910154 & 129.165833333333 & 0.998420500081837 & 1.00006346134155 \tabularnewline
24 & 129.01 & 128.950298612112 & 129.041666666667 & 0.999291949205904 & 1.00046297983433 \tabularnewline
25 & 129.01 & 128.805454432033 & 128.92 & 0.999111498852257 & 1.00158801945825 \tabularnewline
26 & 128.72 & 128.865517568213 & 128.81875 & 1.00036304938694 & 0.998870779623911 \tabularnewline
27 & 128.32 & 128.747975097259 & 128.726666666667 & 1.00016553237293 & 0.996675869294754 \tabularnewline
28 & 128.39 & 128.594202937648 & 128.632916666667 & 0.999699037151439 & 0.998412036211718 \tabularnewline
29 & 128.33 & 128.499952864274 & 128.550833333333 & 0.999604199617068 & 0.998677409131401 \tabularnewline
30 & 128.44 & 128.423086560222 & 128.469166666667 & 0.999641313883786 & 1.00013170092879 \tabularnewline
31 & 128.44 & 128.395092872974 & 128.385833333333 & 1.00007212275218 & 1.0003497573468 \tabularnewline
32 & 128.6 & 128.510210206279 & 128.325 & 1.0014432901327 & 1.0006986977422 \tabularnewline
33 & 128.3 & 128.441074634431 & 128.308333333333 & 1.00103454933634 & 0.998901639254949 \tabularnewline
34 & 128.56 & 128.457518794683 & 128.309583333333 & 1.00115295722662 & 1.00079778284898 \tabularnewline
35 & 128.01 & 128.111910459459 & 128.314583333333 & 0.998420500081837 & 0.999204520023987 \tabularnewline
36 & 128.01 & 128.230808408684 & 128.321666666667 & 0.999291949205904 & 0.998278039330612 \tabularnewline
37 & 128.01 & 128.209317904385 & 128.323333333333 & 0.999111498852257 & 0.998445371150534 \tabularnewline
38 & 128.26 & 128.410769198679 & 128.364166666667 & 1.00036304938694 & 0.99882588353282 \tabularnewline
39 & 128.38 & 128.482097759903 & 128.460833333333 & 1.00016553237293 & 0.999205354195772 \tabularnewline
40 & 128.36 & 128.516726262269 & 128.555416666667 & 0.999699037151439 & 0.99878049910835 \tabularnewline
41 & 128.48 & 128.600746287735 & 128.651666666667 & 0.999604199617068 & 0.999061076306159 \tabularnewline
42 & 128.46 & 128.725061540457 & 128.77125 & 0.999641313883786 & 0.997940870741987 \tabularnewline
43 & 128.46 & 128.903046171989 & 128.89375 & 1.00007212275218 & 0.996562950332474 \tabularnewline
44 & 129.56 & 129.220817674235 & 129.034583333333 & 1.0014432901327 & 1.00262482726754 \tabularnewline
45 & 129.66 & 129.30571822642 & 129.172083333333 & 1.00103454933634 & 1.00273987707922 \tabularnewline
46 & 129.47 & 129.441985869289 & 129.292916666667 & 1.00115295722662 & 1.00021642228774 \tabularnewline
47 & 129.41 & 129.213501077883 & 129.417916666667 & 0.998420500081837 & 1.00152073057752 \tabularnewline
48 & 129.48 & 129.454524674815 & 129.54625 & 0.999291949205904 & 1.00019678976265 \tabularnewline
49 & 129.48 & 129.563530281787 & 129.67875 & 0.999111498852257 & 0.999355294799351 \tabularnewline
50 & 130.17 & 129.805858834637 & 129.75875 & 1.00036304938694 & 1.00280527526748 \tabularnewline
51 & 129.77 & 129.821902837644 & 129.800416666667 & 1.00016553237293 & 0.99960019968503 \tabularnewline
52 & 129.87 & 129.836328991309 & 129.875416666667 & 0.999699037151439 & 1.00025933426301 \tabularnewline
53 & 129.97 & 129.956459483466 & 130.007916666667 & 0.999604199617068 & 1.00010419271645 \tabularnewline
54 & 130.05 & 130.140387034031 & 130.187083333333 & 0.999641313883786 & 0.999305465151202 \tabularnewline
55 & 130.05 & NA & NA & 1.00007212275218 & NA \tabularnewline
56 & 129.89 & NA & NA & 1.0014432901327 & NA \tabularnewline
57 & 130.33 & NA & NA & 1.00103454933634 & NA \tabularnewline
58 & 130.6 & NA & NA & 1.00115295722662 & NA \tabularnewline
59 & 131.46 & NA & NA & 0.998420500081837 & NA \tabularnewline
60 & 131.73 & NA & NA & 0.999291949205904 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166205&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]128.27[/C][C]NA[/C][C]NA[/C][C]0.999111498852257[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]128.38[/C][C]NA[/C][C]NA[/C][C]1.00036304938694[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]128.47[/C][C]NA[/C][C]NA[/C][C]1.00016553237293[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]128.52[/C][C]NA[/C][C]NA[/C][C]0.999699037151439[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]128.71[/C][C]NA[/C][C]NA[/C][C]0.999604199617068[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]128.92[/C][C]NA[/C][C]NA[/C][C]0.999641313883786[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]128.92[/C][C]128.835958000421[/C][C]128.826666666667[/C][C]1.00007212275218[/C][C]1.00065231788457[/C][/ROW]
[ROW][C]8[/C][C]128.82[/C][C]129.105234427832[/C][C]128.919166666667[/C][C]1.0014432901327[/C][C]0.997790682700848[/C][/ROW]
[ROW][C]9[/C][C]128.97[/C][C]129.168910171344[/C][C]129.035416666667[/C][C]1.00103454933634[/C][C]0.998460077033397[/C][/ROW]
[ROW][C]10[/C][C]129.04[/C][C]129.311835984849[/C][C]129.162916666667[/C][C]1.00115295722662[/C][C]0.99789782595863[/C][/ROW]
[ROW][C]11[/C][C]128.95[/C][C]129.063321994329[/C][C]129.2675[/C][C]0.998420500081837[/C][C]0.999121965926664[/C][/ROW]
[ROW][C]12[/C][C]129.39[/C][C]129.264242832821[/C][C]129.355833333333[/C][C]0.999291949205904[/C][C]1.00097286894212[/C][/ROW]
[ROW][C]13[/C][C]129.39[/C][C]129.322494632689[/C][C]129.4375[/C][C]0.999111498852257[/C][C]1.00052199246158[/C][/ROW]
[ROW][C]14[/C][C]129.48[/C][C]129.556601708165[/C][C]129.509583333333[/C][C]1.00036304938694[/C][C]0.999408739445503[/C][/ROW]
[ROW][C]15[/C][C]130.16[/C][C]129.58603046626[/C][C]129.564583333333[/C][C]1.00016553237293[/C][C]1.00442925469416[/C][/ROW]
[ROW][C]16[/C][C]129.89[/C][C]129.571408746463[/C][C]129.610416666667[/C][C]0.999699037151439[/C][C]1.00245880828663[/C][/ROW]
[ROW][C]17[/C][C]129.85[/C][C]129.582024410359[/C][C]129.633333333333[/C][C]0.999604199617068[/C][C]1.0020679997157[/C][/ROW]
[ROW][C]18[/C][C]129.9[/C][C]129.57184103676[/C][C]129.618333333333[/C][C]0.999641313883786[/C][C]1.00253264104773[/C][/ROW]
[ROW][C]19[/C][C]129.9[/C][C]129.596012813712[/C][C]129.586666666667[/C][C]1.00007212275218[/C][C]1.00234565230587[/C][/ROW]
[ROW][C]20[/C][C]129.57[/C][C]129.726129267715[/C][C]129.539166666667[/C][C]1.0014432901327[/C][C]0.998796470159126[/C][/ROW]
[ROW][C]21[/C][C]129.54[/C][C]129.564735916061[/C][C]129.430833333333[/C][C]1.00103454933634[/C][C]0.999809084502154[/C][/ROW]
[ROW][C]22[/C][C]129.57[/C][C]129.440734428092[/C][C]129.291666666667[/C][C]1.00115295722662[/C][C]1.00099864677436[/C][/ROW]
[ROW][C]23[/C][C]128.97[/C][C]128.961815910154[/C][C]129.165833333333[/C][C]0.998420500081837[/C][C]1.00006346134155[/C][/ROW]
[ROW][C]24[/C][C]129.01[/C][C]128.950298612112[/C][C]129.041666666667[/C][C]0.999291949205904[/C][C]1.00046297983433[/C][/ROW]
[ROW][C]25[/C][C]129.01[/C][C]128.805454432033[/C][C]128.92[/C][C]0.999111498852257[/C][C]1.00158801945825[/C][/ROW]
[ROW][C]26[/C][C]128.72[/C][C]128.865517568213[/C][C]128.81875[/C][C]1.00036304938694[/C][C]0.998870779623911[/C][/ROW]
[ROW][C]27[/C][C]128.32[/C][C]128.747975097259[/C][C]128.726666666667[/C][C]1.00016553237293[/C][C]0.996675869294754[/C][/ROW]
[ROW][C]28[/C][C]128.39[/C][C]128.594202937648[/C][C]128.632916666667[/C][C]0.999699037151439[/C][C]0.998412036211718[/C][/ROW]
[ROW][C]29[/C][C]128.33[/C][C]128.499952864274[/C][C]128.550833333333[/C][C]0.999604199617068[/C][C]0.998677409131401[/C][/ROW]
[ROW][C]30[/C][C]128.44[/C][C]128.423086560222[/C][C]128.469166666667[/C][C]0.999641313883786[/C][C]1.00013170092879[/C][/ROW]
[ROW][C]31[/C][C]128.44[/C][C]128.395092872974[/C][C]128.385833333333[/C][C]1.00007212275218[/C][C]1.0003497573468[/C][/ROW]
[ROW][C]32[/C][C]128.6[/C][C]128.510210206279[/C][C]128.325[/C][C]1.0014432901327[/C][C]1.0006986977422[/C][/ROW]
[ROW][C]33[/C][C]128.3[/C][C]128.441074634431[/C][C]128.308333333333[/C][C]1.00103454933634[/C][C]0.998901639254949[/C][/ROW]
[ROW][C]34[/C][C]128.56[/C][C]128.457518794683[/C][C]128.309583333333[/C][C]1.00115295722662[/C][C]1.00079778284898[/C][/ROW]
[ROW][C]35[/C][C]128.01[/C][C]128.111910459459[/C][C]128.314583333333[/C][C]0.998420500081837[/C][C]0.999204520023987[/C][/ROW]
[ROW][C]36[/C][C]128.01[/C][C]128.230808408684[/C][C]128.321666666667[/C][C]0.999291949205904[/C][C]0.998278039330612[/C][/ROW]
[ROW][C]37[/C][C]128.01[/C][C]128.209317904385[/C][C]128.323333333333[/C][C]0.999111498852257[/C][C]0.998445371150534[/C][/ROW]
[ROW][C]38[/C][C]128.26[/C][C]128.410769198679[/C][C]128.364166666667[/C][C]1.00036304938694[/C][C]0.99882588353282[/C][/ROW]
[ROW][C]39[/C][C]128.38[/C][C]128.482097759903[/C][C]128.460833333333[/C][C]1.00016553237293[/C][C]0.999205354195772[/C][/ROW]
[ROW][C]40[/C][C]128.36[/C][C]128.516726262269[/C][C]128.555416666667[/C][C]0.999699037151439[/C][C]0.99878049910835[/C][/ROW]
[ROW][C]41[/C][C]128.48[/C][C]128.600746287735[/C][C]128.651666666667[/C][C]0.999604199617068[/C][C]0.999061076306159[/C][/ROW]
[ROW][C]42[/C][C]128.46[/C][C]128.725061540457[/C][C]128.77125[/C][C]0.999641313883786[/C][C]0.997940870741987[/C][/ROW]
[ROW][C]43[/C][C]128.46[/C][C]128.903046171989[/C][C]128.89375[/C][C]1.00007212275218[/C][C]0.996562950332474[/C][/ROW]
[ROW][C]44[/C][C]129.56[/C][C]129.220817674235[/C][C]129.034583333333[/C][C]1.0014432901327[/C][C]1.00262482726754[/C][/ROW]
[ROW][C]45[/C][C]129.66[/C][C]129.30571822642[/C][C]129.172083333333[/C][C]1.00103454933634[/C][C]1.00273987707922[/C][/ROW]
[ROW][C]46[/C][C]129.47[/C][C]129.441985869289[/C][C]129.292916666667[/C][C]1.00115295722662[/C][C]1.00021642228774[/C][/ROW]
[ROW][C]47[/C][C]129.41[/C][C]129.213501077883[/C][C]129.417916666667[/C][C]0.998420500081837[/C][C]1.00152073057752[/C][/ROW]
[ROW][C]48[/C][C]129.48[/C][C]129.454524674815[/C][C]129.54625[/C][C]0.999291949205904[/C][C]1.00019678976265[/C][/ROW]
[ROW][C]49[/C][C]129.48[/C][C]129.563530281787[/C][C]129.67875[/C][C]0.999111498852257[/C][C]0.999355294799351[/C][/ROW]
[ROW][C]50[/C][C]130.17[/C][C]129.805858834637[/C][C]129.75875[/C][C]1.00036304938694[/C][C]1.00280527526748[/C][/ROW]
[ROW][C]51[/C][C]129.77[/C][C]129.821902837644[/C][C]129.800416666667[/C][C]1.00016553237293[/C][C]0.99960019968503[/C][/ROW]
[ROW][C]52[/C][C]129.87[/C][C]129.836328991309[/C][C]129.875416666667[/C][C]0.999699037151439[/C][C]1.00025933426301[/C][/ROW]
[ROW][C]53[/C][C]129.97[/C][C]129.956459483466[/C][C]130.007916666667[/C][C]0.999604199617068[/C][C]1.00010419271645[/C][/ROW]
[ROW][C]54[/C][C]130.05[/C][C]130.140387034031[/C][C]130.187083333333[/C][C]0.999641313883786[/C][C]0.999305465151202[/C][/ROW]
[ROW][C]55[/C][C]130.05[/C][C]NA[/C][C]NA[/C][C]1.00007212275218[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]129.89[/C][C]NA[/C][C]NA[/C][C]1.0014432901327[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]130.33[/C][C]NA[/C][C]NA[/C][C]1.00103454933634[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]130.6[/C][C]NA[/C][C]NA[/C][C]1.00115295722662[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]131.46[/C][C]NA[/C][C]NA[/C][C]0.998420500081837[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]131.73[/C][C]NA[/C][C]NA[/C][C]0.999291949205904[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166205&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166205&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	128.27	NA	NA	0.999111498852257	NA
2	128.38	NA	NA	1.00036304938694	NA
3	128.47	NA	NA	1.00016553237293	NA
4	128.52	NA	NA	0.999699037151439	NA
5	128.71	NA	NA	0.999604199617068	NA
6	128.92	NA	NA	0.999641313883786	NA
7	128.92	128.835958000421	128.826666666667	1.00007212275218	1.00065231788457
8	128.82	129.105234427832	128.919166666667	1.0014432901327	0.997790682700848
9	128.97	129.168910171344	129.035416666667	1.00103454933634	0.998460077033397
10	129.04	129.311835984849	129.162916666667	1.00115295722662	0.99789782595863
11	128.95	129.063321994329	129.2675	0.998420500081837	0.999121965926664
12	129.39	129.264242832821	129.355833333333	0.999291949205904	1.00097286894212
13	129.39	129.322494632689	129.4375	0.999111498852257	1.00052199246158
14	129.48	129.556601708165	129.509583333333	1.00036304938694	0.999408739445503
15	130.16	129.58603046626	129.564583333333	1.00016553237293	1.00442925469416
16	129.89	129.571408746463	129.610416666667	0.999699037151439	1.00245880828663
17	129.85	129.582024410359	129.633333333333	0.999604199617068	1.0020679997157
18	129.9	129.57184103676	129.618333333333	0.999641313883786	1.00253264104773
19	129.9	129.596012813712	129.586666666667	1.00007212275218	1.00234565230587
20	129.57	129.726129267715	129.539166666667	1.0014432901327	0.998796470159126
21	129.54	129.564735916061	129.430833333333	1.00103454933634	0.999809084502154
22	129.57	129.440734428092	129.291666666667	1.00115295722662	1.00099864677436
23	128.97	128.961815910154	129.165833333333	0.998420500081837	1.00006346134155
24	129.01	128.950298612112	129.041666666667	0.999291949205904	1.00046297983433
25	129.01	128.805454432033	128.92	0.999111498852257	1.00158801945825
26	128.72	128.865517568213	128.81875	1.00036304938694	0.998870779623911
27	128.32	128.747975097259	128.726666666667	1.00016553237293	0.996675869294754
28	128.39	128.594202937648	128.632916666667	0.999699037151439	0.998412036211718
29	128.33	128.499952864274	128.550833333333	0.999604199617068	0.998677409131401
30	128.44	128.423086560222	128.469166666667	0.999641313883786	1.00013170092879
31	128.44	128.395092872974	128.385833333333	1.00007212275218	1.0003497573468
32	128.6	128.510210206279	128.325	1.0014432901327	1.0006986977422
33	128.3	128.441074634431	128.308333333333	1.00103454933634	0.998901639254949
34	128.56	128.457518794683	128.309583333333	1.00115295722662	1.00079778284898
35	128.01	128.111910459459	128.314583333333	0.998420500081837	0.999204520023987
36	128.01	128.230808408684	128.321666666667	0.999291949205904	0.998278039330612
37	128.01	128.209317904385	128.323333333333	0.999111498852257	0.998445371150534
38	128.26	128.410769198679	128.364166666667	1.00036304938694	0.99882588353282
39	128.38	128.482097759903	128.460833333333	1.00016553237293	0.999205354195772
40	128.36	128.516726262269	128.555416666667	0.999699037151439	0.99878049910835
41	128.48	128.600746287735	128.651666666667	0.999604199617068	0.999061076306159
42	128.46	128.725061540457	128.77125	0.999641313883786	0.997940870741987
43	128.46	128.903046171989	128.89375	1.00007212275218	0.996562950332474
44	129.56	129.220817674235	129.034583333333	1.0014432901327	1.00262482726754
45	129.66	129.30571822642	129.172083333333	1.00103454933634	1.00273987707922
46	129.47	129.441985869289	129.292916666667	1.00115295722662	1.00021642228774
47	129.41	129.213501077883	129.417916666667	0.998420500081837	1.00152073057752
48	129.48	129.454524674815	129.54625	0.999291949205904	1.00019678976265
49	129.48	129.563530281787	129.67875	0.999111498852257	0.999355294799351
50	130.17	129.805858834637	129.75875	1.00036304938694	1.00280527526748
51	129.77	129.821902837644	129.800416666667	1.00016553237293	0.99960019968503
52	129.87	129.836328991309	129.875416666667	0.999699037151439	1.00025933426301
53	129.97	129.956459483466	130.007916666667	0.999604199617068	1.00010419271645
54	130.05	130.140387034031	130.187083333333	0.999641313883786	0.999305465151202
55	130.05	NA	NA	1.00007212275218	NA
56	129.89	NA	NA	1.0014432901327	NA
57	130.33	NA	NA	1.00103454933634	NA
58	130.6	NA	NA	1.00115295722662	NA
59	131.46	NA	NA	0.998420500081837	NA
60	131.73	NA	NA	0.999291949205904	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