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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 15 Jan 2013 07:58:45 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Jan/15/t1358254791r81gskjd5dbx375.htm/, Retrieved Sat, 27 Apr 2024 15:53:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205451, Retrieved Sat, 27 Apr 2024 15:53:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Exponential Smoothing] [] [2012-12-21 09:01:13] [227684cba395e1e45653f76e88b62d57]
- RMPD    [Classical Decomposition] [] [2013-01-15 12:58:45] [c9eeded7548c00546c4c5f04921b1379] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102,89
102,64
103,33
103,56
103,6
104,24
105,31
105,4
105,89
105,89
105,54
106,15
106,14
105,85
106,27
106,51
106,82
106,53
107,14
107,39
107,33
107,53
107,42
108,25
108,26
108,93
109,43
109,61
109,74
110,12
110,16
110,44
111,23
112,86
112,77
113,04
112,79
113,87
114,28
115,51
116,76
116,91
116,47
116,94
117,24
116,82
117,48
117,11
117,31
117,77
118,37
117,91
118,12
118,02
117,77
117,85
118,68
118,9
118,6
118,21
118,37
117,43
117,5
116,71
116,98
117,74
117,44
117,85
118,54
118,73
118,68
118,19

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205451&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]4 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=205451&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205451&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1102.89NANA0.998235277017077NA
2102.64NANA0.998175897607331NA
3103.33NANA0.999872477356396NA
4103.56NANA0.998774937155425NA
5103.6NANA1.00063815660022NA
6104.24NANA1.00028858214185NA
7105.31104.663746584551104.6720833333330.9999203536557541.00617456795249
8105.4104.912171182141104.941250.9997229038356281.00464987820157
9105.89105.375299169588105.19751.001690146339871.00488445427408
10105.89105.713055973215105.4429166666671.002561948351661.00167381431893
11105.54105.714496321067105.71.000137145894680.998349362413483
12106.15105.927695037254105.9295833333330.9999821740441131.00209864816437
13106.14105.914010685608106.101250.9982352770170771.00213370556859
14105.85106.066586786379106.2604166666670.9981758976073310.997958011161279
15106.27106.389764498978106.4033333333330.9998724773563960.998874285514755
16106.51106.401158680063106.5316666666670.9987749371554251.00102293359666
17106.82106.746410815851106.6783333333331.000638156600221.00068938321754
18106.53106.874999985128106.8441666666671.000288582141850.996771929963268
19107.14107.011476248239107.020.9999203536557541.0012010277427
20107.39107.206951797653107.2366666666670.9997229038356281.00170742847621
21107.33107.678351764381107.4966666666671.001690146339870.996764885804126
22107.53108.033569149504107.75751.002561948351660.995338771518261
23107.42108.023146232841108.0083333333331.000137145894680.994416509295695
24108.25108.277653146257108.2795833333330.9999821740441130.999744608924798
25108.26108.363430496589108.5550.9982352770170770.999045522127577
26108.93108.609439885534108.8079166666670.9981758976073311.0029514940396
27109.43109.083587598389109.09750.9998724773563961.00317566014501
28109.61109.347960900895109.4820833333330.9987749371554251.00239637846875
29109.74109.997234027106109.9270833333331.000638156600220.997661450041166
30110.12110.381428252444110.3495833333331.000288582141850.997631592047837
31110.16110.729096796435110.7379166666670.9999203536557540.994860458426018
32110.44111.101705610513111.13250.9997229038356280.994044145345233
33111.23111.728936293643111.5404166666671.001690146339870.995534403976319
34112.86112.275241659321111.9883333333331.002561948351661.00520825724386
35112.77112.542099237042112.5266666666671.000137145894681.00202502676335
36113.04113.100067180585113.1020833333330.9999821740441130.999468902343894
37112.79113.447359576164113.6479166666670.9982352770170770.994205598273776
38113.87113.973387615301114.1816666666670.9981758976073310.999092879333814
39114.28114.688289447504114.7029166666670.9998724773563960.996440007524124
40115.51114.977306140437115.1183333333330.9987749371554251.00463303479134
41116.76115.553277391629115.4795833333331.000638156600221.01044299768566
42116.91115.878847585132115.8454166666671.000288582141851.00889853874419
43116.47116.194078162644116.2033333333330.9999203536557541.00237466350884
44116.94116.521869954142116.5541666666670.9997229038356281.00358842546917
45117.24117.084639609407116.8870833333331.001690146339871.00132690668145
46116.82117.457651464009117.15751.002561948351660.994571222427306
47117.48117.330255823012117.3141666666671.000137145894681.00127626225595
48117.11117.414990261585117.4170833333330.9999821740441130.997402458911712
49117.31117.310114166854117.51750.9982352770170770.999999026794448
50117.77117.395051410974117.6095833333330.9981758976073311.00319390455151
51118.37117.692489628428117.70750.9998724773563961.00575661517325
52117.91117.709787906005117.8541666666670.9987749371554251.00170089588603
53118.12118.062794501869117.98751.000638156600221.00048453450871
54118.02118.11407577931118.081.000288582141850.999203517627436
55117.77118.1605881915118.170.9999203536557540.996694429187612
56117.85118.167247233371118.20.9997229038356280.997315269325479
57118.68118.349273419161118.1495833333331.001690146339871.00279449608168
58118.9118.365805495558118.0633333333331.002561948351661.0045130813093
59118.6117.982011863087117.9658333333331.000137145894681.00523798608919
60118.21117.904564867628117.9066666666670.9999821740441131.00259052847288
61118.37117.673222248869117.881250.9982352770170771.00592129405326
62117.43117.652497611232117.86750.9981758976073310.998108857731459
63117.5117.846636635354117.8616666666670.9998724773563960.997058578460527
64116.71117.704377875095117.848750.9987749371554250.99155190407488
65116.98117.920203564553117.8451.000638156600220.99202678136458
66117.74117.881508683962117.84751.000288582141850.998799568434933
67117.44NANA0.999920353655754NA
68117.85NANA0.999722903835628NA
69118.54NANA1.00169014633987NA
70118.73NANA1.00256194835166NA
71118.68NANA1.00013714589468NA
72118.19NANA0.999982174044113NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 102.89 & NA & NA & 0.998235277017077 & NA \tabularnewline
2 & 102.64 & NA & NA & 0.998175897607331 & NA \tabularnewline
3 & 103.33 & NA & NA & 0.999872477356396 & NA \tabularnewline
4 & 103.56 & NA & NA & 0.998774937155425 & NA \tabularnewline
5 & 103.6 & NA & NA & 1.00063815660022 & NA \tabularnewline
6 & 104.24 & NA & NA & 1.00028858214185 & NA \tabularnewline
7 & 105.31 & 104.663746584551 & 104.672083333333 & 0.999920353655754 & 1.00617456795249 \tabularnewline
8 & 105.4 & 104.912171182141 & 104.94125 & 0.999722903835628 & 1.00464987820157 \tabularnewline
9 & 105.89 & 105.375299169588 & 105.1975 & 1.00169014633987 & 1.00488445427408 \tabularnewline
10 & 105.89 & 105.713055973215 & 105.442916666667 & 1.00256194835166 & 1.00167381431893 \tabularnewline
11 & 105.54 & 105.714496321067 & 105.7 & 1.00013714589468 & 0.998349362413483 \tabularnewline
12 & 106.15 & 105.927695037254 & 105.929583333333 & 0.999982174044113 & 1.00209864816437 \tabularnewline
13 & 106.14 & 105.914010685608 & 106.10125 & 0.998235277017077 & 1.00213370556859 \tabularnewline
14 & 105.85 & 106.066586786379 & 106.260416666667 & 0.998175897607331 & 0.997958011161279 \tabularnewline
15 & 106.27 & 106.389764498978 & 106.403333333333 & 0.999872477356396 & 0.998874285514755 \tabularnewline
16 & 106.51 & 106.401158680063 & 106.531666666667 & 0.998774937155425 & 1.00102293359666 \tabularnewline
17 & 106.82 & 106.746410815851 & 106.678333333333 & 1.00063815660022 & 1.00068938321754 \tabularnewline
18 & 106.53 & 106.874999985128 & 106.844166666667 & 1.00028858214185 & 0.996771929963268 \tabularnewline
19 & 107.14 & 107.011476248239 & 107.02 & 0.999920353655754 & 1.0012010277427 \tabularnewline
20 & 107.39 & 107.206951797653 & 107.236666666667 & 0.999722903835628 & 1.00170742847621 \tabularnewline
21 & 107.33 & 107.678351764381 & 107.496666666667 & 1.00169014633987 & 0.996764885804126 \tabularnewline
22 & 107.53 & 108.033569149504 & 107.7575 & 1.00256194835166 & 0.995338771518261 \tabularnewline
23 & 107.42 & 108.023146232841 & 108.008333333333 & 1.00013714589468 & 0.994416509295695 \tabularnewline
24 & 108.25 & 108.277653146257 & 108.279583333333 & 0.999982174044113 & 0.999744608924798 \tabularnewline
25 & 108.26 & 108.363430496589 & 108.555 & 0.998235277017077 & 0.999045522127577 \tabularnewline
26 & 108.93 & 108.609439885534 & 108.807916666667 & 0.998175897607331 & 1.0029514940396 \tabularnewline
27 & 109.43 & 109.083587598389 & 109.0975 & 0.999872477356396 & 1.00317566014501 \tabularnewline
28 & 109.61 & 109.347960900895 & 109.482083333333 & 0.998774937155425 & 1.00239637846875 \tabularnewline
29 & 109.74 & 109.997234027106 & 109.927083333333 & 1.00063815660022 & 0.997661450041166 \tabularnewline
30 & 110.12 & 110.381428252444 & 110.349583333333 & 1.00028858214185 & 0.997631592047837 \tabularnewline
31 & 110.16 & 110.729096796435 & 110.737916666667 & 0.999920353655754 & 0.994860458426018 \tabularnewline
32 & 110.44 & 111.101705610513 & 111.1325 & 0.999722903835628 & 0.994044145345233 \tabularnewline
33 & 111.23 & 111.728936293643 & 111.540416666667 & 1.00169014633987 & 0.995534403976319 \tabularnewline
34 & 112.86 & 112.275241659321 & 111.988333333333 & 1.00256194835166 & 1.00520825724386 \tabularnewline
35 & 112.77 & 112.542099237042 & 112.526666666667 & 1.00013714589468 & 1.00202502676335 \tabularnewline
36 & 113.04 & 113.100067180585 & 113.102083333333 & 0.999982174044113 & 0.999468902343894 \tabularnewline
37 & 112.79 & 113.447359576164 & 113.647916666667 & 0.998235277017077 & 0.994205598273776 \tabularnewline
38 & 113.87 & 113.973387615301 & 114.181666666667 & 0.998175897607331 & 0.999092879333814 \tabularnewline
39 & 114.28 & 114.688289447504 & 114.702916666667 & 0.999872477356396 & 0.996440007524124 \tabularnewline
40 & 115.51 & 114.977306140437 & 115.118333333333 & 0.998774937155425 & 1.00463303479134 \tabularnewline
41 & 116.76 & 115.553277391629 & 115.479583333333 & 1.00063815660022 & 1.01044299768566 \tabularnewline
42 & 116.91 & 115.878847585132 & 115.845416666667 & 1.00028858214185 & 1.00889853874419 \tabularnewline
43 & 116.47 & 116.194078162644 & 116.203333333333 & 0.999920353655754 & 1.00237466350884 \tabularnewline
44 & 116.94 & 116.521869954142 & 116.554166666667 & 0.999722903835628 & 1.00358842546917 \tabularnewline
45 & 117.24 & 117.084639609407 & 116.887083333333 & 1.00169014633987 & 1.00132690668145 \tabularnewline
46 & 116.82 & 117.457651464009 & 117.1575 & 1.00256194835166 & 0.994571222427306 \tabularnewline
47 & 117.48 & 117.330255823012 & 117.314166666667 & 1.00013714589468 & 1.00127626225595 \tabularnewline
48 & 117.11 & 117.414990261585 & 117.417083333333 & 0.999982174044113 & 0.997402458911712 \tabularnewline
49 & 117.31 & 117.310114166854 & 117.5175 & 0.998235277017077 & 0.999999026794448 \tabularnewline
50 & 117.77 & 117.395051410974 & 117.609583333333 & 0.998175897607331 & 1.00319390455151 \tabularnewline
51 & 118.37 & 117.692489628428 & 117.7075 & 0.999872477356396 & 1.00575661517325 \tabularnewline
52 & 117.91 & 117.709787906005 & 117.854166666667 & 0.998774937155425 & 1.00170089588603 \tabularnewline
53 & 118.12 & 118.062794501869 & 117.9875 & 1.00063815660022 & 1.00048453450871 \tabularnewline
54 & 118.02 & 118.11407577931 & 118.08 & 1.00028858214185 & 0.999203517627436 \tabularnewline
55 & 117.77 & 118.1605881915 & 118.17 & 0.999920353655754 & 0.996694429187612 \tabularnewline
56 & 117.85 & 118.167247233371 & 118.2 & 0.999722903835628 & 0.997315269325479 \tabularnewline
57 & 118.68 & 118.349273419161 & 118.149583333333 & 1.00169014633987 & 1.00279449608168 \tabularnewline
58 & 118.9 & 118.365805495558 & 118.063333333333 & 1.00256194835166 & 1.0045130813093 \tabularnewline
59 & 118.6 & 117.982011863087 & 117.965833333333 & 1.00013714589468 & 1.00523798608919 \tabularnewline
60 & 118.21 & 117.904564867628 & 117.906666666667 & 0.999982174044113 & 1.00259052847288 \tabularnewline
61 & 118.37 & 117.673222248869 & 117.88125 & 0.998235277017077 & 1.00592129405326 \tabularnewline
62 & 117.43 & 117.652497611232 & 117.8675 & 0.998175897607331 & 0.998108857731459 \tabularnewline
63 & 117.5 & 117.846636635354 & 117.861666666667 & 0.999872477356396 & 0.997058578460527 \tabularnewline
64 & 116.71 & 117.704377875095 & 117.84875 & 0.998774937155425 & 0.99155190407488 \tabularnewline
65 & 116.98 & 117.920203564553 & 117.845 & 1.00063815660022 & 0.99202678136458 \tabularnewline
66 & 117.74 & 117.881508683962 & 117.8475 & 1.00028858214185 & 0.998799568434933 \tabularnewline
67 & 117.44 & NA & NA & 0.999920353655754 & NA \tabularnewline
68 & 117.85 & NA & NA & 0.999722903835628 & NA \tabularnewline
69 & 118.54 & NA & NA & 1.00169014633987 & NA \tabularnewline
70 & 118.73 & NA & NA & 1.00256194835166 & NA \tabularnewline
71 & 118.68 & NA & NA & 1.00013714589468 & NA \tabularnewline
72 & 118.19 & NA & NA & 0.999982174044113 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205451&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]102.89[/C][C]NA[/C][C]NA[/C][C]0.998235277017077[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102.64[/C][C]NA[/C][C]NA[/C][C]0.998175897607331[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.33[/C][C]NA[/C][C]NA[/C][C]0.999872477356396[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]103.56[/C][C]NA[/C][C]NA[/C][C]0.998774937155425[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]103.6[/C][C]NA[/C][C]NA[/C][C]1.00063815660022[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]104.24[/C][C]NA[/C][C]NA[/C][C]1.00028858214185[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]105.31[/C][C]104.663746584551[/C][C]104.672083333333[/C][C]0.999920353655754[/C][C]1.00617456795249[/C][/ROW]
[ROW][C]8[/C][C]105.4[/C][C]104.912171182141[/C][C]104.94125[/C][C]0.999722903835628[/C][C]1.00464987820157[/C][/ROW]
[ROW][C]9[/C][C]105.89[/C][C]105.375299169588[/C][C]105.1975[/C][C]1.00169014633987[/C][C]1.00488445427408[/C][/ROW]
[ROW][C]10[/C][C]105.89[/C][C]105.713055973215[/C][C]105.442916666667[/C][C]1.00256194835166[/C][C]1.00167381431893[/C][/ROW]
[ROW][C]11[/C][C]105.54[/C][C]105.714496321067[/C][C]105.7[/C][C]1.00013714589468[/C][C]0.998349362413483[/C][/ROW]
[ROW][C]12[/C][C]106.15[/C][C]105.927695037254[/C][C]105.929583333333[/C][C]0.999982174044113[/C][C]1.00209864816437[/C][/ROW]
[ROW][C]13[/C][C]106.14[/C][C]105.914010685608[/C][C]106.10125[/C][C]0.998235277017077[/C][C]1.00213370556859[/C][/ROW]
[ROW][C]14[/C][C]105.85[/C][C]106.066586786379[/C][C]106.260416666667[/C][C]0.998175897607331[/C][C]0.997958011161279[/C][/ROW]
[ROW][C]15[/C][C]106.27[/C][C]106.389764498978[/C][C]106.403333333333[/C][C]0.999872477356396[/C][C]0.998874285514755[/C][/ROW]
[ROW][C]16[/C][C]106.51[/C][C]106.401158680063[/C][C]106.531666666667[/C][C]0.998774937155425[/C][C]1.00102293359666[/C][/ROW]
[ROW][C]17[/C][C]106.82[/C][C]106.746410815851[/C][C]106.678333333333[/C][C]1.00063815660022[/C][C]1.00068938321754[/C][/ROW]
[ROW][C]18[/C][C]106.53[/C][C]106.874999985128[/C][C]106.844166666667[/C][C]1.00028858214185[/C][C]0.996771929963268[/C][/ROW]
[ROW][C]19[/C][C]107.14[/C][C]107.011476248239[/C][C]107.02[/C][C]0.999920353655754[/C][C]1.0012010277427[/C][/ROW]
[ROW][C]20[/C][C]107.39[/C][C]107.206951797653[/C][C]107.236666666667[/C][C]0.999722903835628[/C][C]1.00170742847621[/C][/ROW]
[ROW][C]21[/C][C]107.33[/C][C]107.678351764381[/C][C]107.496666666667[/C][C]1.00169014633987[/C][C]0.996764885804126[/C][/ROW]
[ROW][C]22[/C][C]107.53[/C][C]108.033569149504[/C][C]107.7575[/C][C]1.00256194835166[/C][C]0.995338771518261[/C][/ROW]
[ROW][C]23[/C][C]107.42[/C][C]108.023146232841[/C][C]108.008333333333[/C][C]1.00013714589468[/C][C]0.994416509295695[/C][/ROW]
[ROW][C]24[/C][C]108.25[/C][C]108.277653146257[/C][C]108.279583333333[/C][C]0.999982174044113[/C][C]0.999744608924798[/C][/ROW]
[ROW][C]25[/C][C]108.26[/C][C]108.363430496589[/C][C]108.555[/C][C]0.998235277017077[/C][C]0.999045522127577[/C][/ROW]
[ROW][C]26[/C][C]108.93[/C][C]108.609439885534[/C][C]108.807916666667[/C][C]0.998175897607331[/C][C]1.0029514940396[/C][/ROW]
[ROW][C]27[/C][C]109.43[/C][C]109.083587598389[/C][C]109.0975[/C][C]0.999872477356396[/C][C]1.00317566014501[/C][/ROW]
[ROW][C]28[/C][C]109.61[/C][C]109.347960900895[/C][C]109.482083333333[/C][C]0.998774937155425[/C][C]1.00239637846875[/C][/ROW]
[ROW][C]29[/C][C]109.74[/C][C]109.997234027106[/C][C]109.927083333333[/C][C]1.00063815660022[/C][C]0.997661450041166[/C][/ROW]
[ROW][C]30[/C][C]110.12[/C][C]110.381428252444[/C][C]110.349583333333[/C][C]1.00028858214185[/C][C]0.997631592047837[/C][/ROW]
[ROW][C]31[/C][C]110.16[/C][C]110.729096796435[/C][C]110.737916666667[/C][C]0.999920353655754[/C][C]0.994860458426018[/C][/ROW]
[ROW][C]32[/C][C]110.44[/C][C]111.101705610513[/C][C]111.1325[/C][C]0.999722903835628[/C][C]0.994044145345233[/C][/ROW]
[ROW][C]33[/C][C]111.23[/C][C]111.728936293643[/C][C]111.540416666667[/C][C]1.00169014633987[/C][C]0.995534403976319[/C][/ROW]
[ROW][C]34[/C][C]112.86[/C][C]112.275241659321[/C][C]111.988333333333[/C][C]1.00256194835166[/C][C]1.00520825724386[/C][/ROW]
[ROW][C]35[/C][C]112.77[/C][C]112.542099237042[/C][C]112.526666666667[/C][C]1.00013714589468[/C][C]1.00202502676335[/C][/ROW]
[ROW][C]36[/C][C]113.04[/C][C]113.100067180585[/C][C]113.102083333333[/C][C]0.999982174044113[/C][C]0.999468902343894[/C][/ROW]
[ROW][C]37[/C][C]112.79[/C][C]113.447359576164[/C][C]113.647916666667[/C][C]0.998235277017077[/C][C]0.994205598273776[/C][/ROW]
[ROW][C]38[/C][C]113.87[/C][C]113.973387615301[/C][C]114.181666666667[/C][C]0.998175897607331[/C][C]0.999092879333814[/C][/ROW]
[ROW][C]39[/C][C]114.28[/C][C]114.688289447504[/C][C]114.702916666667[/C][C]0.999872477356396[/C][C]0.996440007524124[/C][/ROW]
[ROW][C]40[/C][C]115.51[/C][C]114.977306140437[/C][C]115.118333333333[/C][C]0.998774937155425[/C][C]1.00463303479134[/C][/ROW]
[ROW][C]41[/C][C]116.76[/C][C]115.553277391629[/C][C]115.479583333333[/C][C]1.00063815660022[/C][C]1.01044299768566[/C][/ROW]
[ROW][C]42[/C][C]116.91[/C][C]115.878847585132[/C][C]115.845416666667[/C][C]1.00028858214185[/C][C]1.00889853874419[/C][/ROW]
[ROW][C]43[/C][C]116.47[/C][C]116.194078162644[/C][C]116.203333333333[/C][C]0.999920353655754[/C][C]1.00237466350884[/C][/ROW]
[ROW][C]44[/C][C]116.94[/C][C]116.521869954142[/C][C]116.554166666667[/C][C]0.999722903835628[/C][C]1.00358842546917[/C][/ROW]
[ROW][C]45[/C][C]117.24[/C][C]117.084639609407[/C][C]116.887083333333[/C][C]1.00169014633987[/C][C]1.00132690668145[/C][/ROW]
[ROW][C]46[/C][C]116.82[/C][C]117.457651464009[/C][C]117.1575[/C][C]1.00256194835166[/C][C]0.994571222427306[/C][/ROW]
[ROW][C]47[/C][C]117.48[/C][C]117.330255823012[/C][C]117.314166666667[/C][C]1.00013714589468[/C][C]1.00127626225595[/C][/ROW]
[ROW][C]48[/C][C]117.11[/C][C]117.414990261585[/C][C]117.417083333333[/C][C]0.999982174044113[/C][C]0.997402458911712[/C][/ROW]
[ROW][C]49[/C][C]117.31[/C][C]117.310114166854[/C][C]117.5175[/C][C]0.998235277017077[/C][C]0.999999026794448[/C][/ROW]
[ROW][C]50[/C][C]117.77[/C][C]117.395051410974[/C][C]117.609583333333[/C][C]0.998175897607331[/C][C]1.00319390455151[/C][/ROW]
[ROW][C]51[/C][C]118.37[/C][C]117.692489628428[/C][C]117.7075[/C][C]0.999872477356396[/C][C]1.00575661517325[/C][/ROW]
[ROW][C]52[/C][C]117.91[/C][C]117.709787906005[/C][C]117.854166666667[/C][C]0.998774937155425[/C][C]1.00170089588603[/C][/ROW]
[ROW][C]53[/C][C]118.12[/C][C]118.062794501869[/C][C]117.9875[/C][C]1.00063815660022[/C][C]1.00048453450871[/C][/ROW]
[ROW][C]54[/C][C]118.02[/C][C]118.11407577931[/C][C]118.08[/C][C]1.00028858214185[/C][C]0.999203517627436[/C][/ROW]
[ROW][C]55[/C][C]117.77[/C][C]118.1605881915[/C][C]118.17[/C][C]0.999920353655754[/C][C]0.996694429187612[/C][/ROW]
[ROW][C]56[/C][C]117.85[/C][C]118.167247233371[/C][C]118.2[/C][C]0.999722903835628[/C][C]0.997315269325479[/C][/ROW]
[ROW][C]57[/C][C]118.68[/C][C]118.349273419161[/C][C]118.149583333333[/C][C]1.00169014633987[/C][C]1.00279449608168[/C][/ROW]
[ROW][C]58[/C][C]118.9[/C][C]118.365805495558[/C][C]118.063333333333[/C][C]1.00256194835166[/C][C]1.0045130813093[/C][/ROW]
[ROW][C]59[/C][C]118.6[/C][C]117.982011863087[/C][C]117.965833333333[/C][C]1.00013714589468[/C][C]1.00523798608919[/C][/ROW]
[ROW][C]60[/C][C]118.21[/C][C]117.904564867628[/C][C]117.906666666667[/C][C]0.999982174044113[/C][C]1.00259052847288[/C][/ROW]
[ROW][C]61[/C][C]118.37[/C][C]117.673222248869[/C][C]117.88125[/C][C]0.998235277017077[/C][C]1.00592129405326[/C][/ROW]
[ROW][C]62[/C][C]117.43[/C][C]117.652497611232[/C][C]117.8675[/C][C]0.998175897607331[/C][C]0.998108857731459[/C][/ROW]
[ROW][C]63[/C][C]117.5[/C][C]117.846636635354[/C][C]117.861666666667[/C][C]0.999872477356396[/C][C]0.997058578460527[/C][/ROW]
[ROW][C]64[/C][C]116.71[/C][C]117.704377875095[/C][C]117.84875[/C][C]0.998774937155425[/C][C]0.99155190407488[/C][/ROW]
[ROW][C]65[/C][C]116.98[/C][C]117.920203564553[/C][C]117.845[/C][C]1.00063815660022[/C][C]0.99202678136458[/C][/ROW]
[ROW][C]66[/C][C]117.74[/C][C]117.881508683962[/C][C]117.8475[/C][C]1.00028858214185[/C][C]0.998799568434933[/C][/ROW]
[ROW][C]67[/C][C]117.44[/C][C]NA[/C][C]NA[/C][C]0.999920353655754[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]117.85[/C][C]NA[/C][C]NA[/C][C]0.999722903835628[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]118.54[/C][C]NA[/C][C]NA[/C][C]1.00169014633987[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]118.73[/C][C]NA[/C][C]NA[/C][C]1.00256194835166[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]118.68[/C][C]NA[/C][C]NA[/C][C]1.00013714589468[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]118.19[/C][C]NA[/C][C]NA[/C][C]0.999982174044113[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205451&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205451&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1102.89NANA0.998235277017077NA
2102.64NANA0.998175897607331NA
3103.33NANA0.999872477356396NA
4103.56NANA0.998774937155425NA
5103.6NANA1.00063815660022NA
6104.24NANA1.00028858214185NA
7105.31104.663746584551104.6720833333330.9999203536557541.00617456795249
8105.4104.912171182141104.941250.9997229038356281.00464987820157
9105.89105.375299169588105.19751.001690146339871.00488445427408
10105.89105.713055973215105.4429166666671.002561948351661.00167381431893
11105.54105.714496321067105.71.000137145894680.998349362413483
12106.15105.927695037254105.9295833333330.9999821740441131.00209864816437
13106.14105.914010685608106.101250.9982352770170771.00213370556859
14105.85106.066586786379106.2604166666670.9981758976073310.997958011161279
15106.27106.389764498978106.4033333333330.9998724773563960.998874285514755
16106.51106.401158680063106.5316666666670.9987749371554251.00102293359666
17106.82106.746410815851106.6783333333331.000638156600221.00068938321754
18106.53106.874999985128106.8441666666671.000288582141850.996771929963268
19107.14107.011476248239107.020.9999203536557541.0012010277427
20107.39107.206951797653107.2366666666670.9997229038356281.00170742847621
21107.33107.678351764381107.4966666666671.001690146339870.996764885804126
22107.53108.033569149504107.75751.002561948351660.995338771518261
23107.42108.023146232841108.0083333333331.000137145894680.994416509295695
24108.25108.277653146257108.2795833333330.9999821740441130.999744608924798
25108.26108.363430496589108.5550.9982352770170770.999045522127577
26108.93108.609439885534108.8079166666670.9981758976073311.0029514940396
27109.43109.083587598389109.09750.9998724773563961.00317566014501
28109.61109.347960900895109.4820833333330.9987749371554251.00239637846875
29109.74109.997234027106109.9270833333331.000638156600220.997661450041166
30110.12110.381428252444110.3495833333331.000288582141850.997631592047837
31110.16110.729096796435110.7379166666670.9999203536557540.994860458426018
32110.44111.101705610513111.13250.9997229038356280.994044145345233
33111.23111.728936293643111.5404166666671.001690146339870.995534403976319
34112.86112.275241659321111.9883333333331.002561948351661.00520825724386
35112.77112.542099237042112.5266666666671.000137145894681.00202502676335
36113.04113.100067180585113.1020833333330.9999821740441130.999468902343894
37112.79113.447359576164113.6479166666670.9982352770170770.994205598273776
38113.87113.973387615301114.1816666666670.9981758976073310.999092879333814
39114.28114.688289447504114.7029166666670.9998724773563960.996440007524124
40115.51114.977306140437115.1183333333330.9987749371554251.00463303479134
41116.76115.553277391629115.4795833333331.000638156600221.01044299768566
42116.91115.878847585132115.8454166666671.000288582141851.00889853874419
43116.47116.194078162644116.2033333333330.9999203536557541.00237466350884
44116.94116.521869954142116.5541666666670.9997229038356281.00358842546917
45117.24117.084639609407116.8870833333331.001690146339871.00132690668145
46116.82117.457651464009117.15751.002561948351660.994571222427306
47117.48117.330255823012117.3141666666671.000137145894681.00127626225595
48117.11117.414990261585117.4170833333330.9999821740441130.997402458911712
49117.31117.310114166854117.51750.9982352770170770.999999026794448
50117.77117.395051410974117.6095833333330.9981758976073311.00319390455151
51118.37117.692489628428117.70750.9998724773563961.00575661517325
52117.91117.709787906005117.8541666666670.9987749371554251.00170089588603
53118.12118.062794501869117.98751.000638156600221.00048453450871
54118.02118.11407577931118.081.000288582141850.999203517627436
55117.77118.1605881915118.170.9999203536557540.996694429187612
56117.85118.167247233371118.20.9997229038356280.997315269325479
57118.68118.349273419161118.1495833333331.001690146339871.00279449608168
58118.9118.365805495558118.0633333333331.002561948351661.0045130813093
59118.6117.982011863087117.9658333333331.000137145894681.00523798608919
60118.21117.904564867628117.9066666666670.9999821740441131.00259052847288
61118.37117.673222248869117.881250.9982352770170771.00592129405326
62117.43117.652497611232117.86750.9981758976073310.998108857731459
63117.5117.846636635354117.8616666666670.9998724773563960.997058578460527
64116.71117.704377875095117.848750.9987749371554250.99155190407488
65116.98117.920203564553117.8451.000638156600220.99202678136458
66117.74117.881508683962117.84751.000288582141850.998799568434933
67117.44NANA0.999920353655754NA
68117.85NANA0.999722903835628NA
69118.54NANA1.00169014633987NA
70118.73NANA1.00256194835166NA
71118.68NANA1.00013714589468NA
72118.19NANA0.999982174044113NA


Figures (Output of Computation)

Input Parameters & R Code

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')