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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 computationMon, 06 Dec 2010 14:10:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/06/t12916445284fg76srpd7etibj.htm/, Retrieved Mon, 29 Apr 2024 00:52:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105612, Retrieved Mon, 29 Apr 2024 00:52:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [opgave 9 oef 2] [2010-12-06 14:10:24] [2d936dc014887261753404b7df36ea79] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,24
7,52
7,57
7,59
7,58
7,55
7,52
7,55
7,62
7,64
7,68
7,69
7,7
7,6
7,51
7,66
7,69
7,66
7,7
7,72
7,74
7,76
7,72
7,73
7,75
8,1
8,22
8,32
8,07
8,18
8,33
8,34
8,25
8,36
8,36
8,34
8,41
8,39
8,43
8,44
8,49
8,47
8,53
8,52
8,51
8,53
8,54
8,53
8,47
8,63
8,67
8,73
8,57
8,55
8,63
8,65
8,44
8,62
8,37
8,59
8,84
8,72
8,8
8,69
8,68
8,57
8,85
8,85
8,85
8,93
8,75
8,78
8,77
9,03
9,01
9,07
8,99
9,02
8,99
8,98
8,94
8,94
8,75
8,86

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105612&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]3 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=105612&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105612&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
17.24NANA-0.0279629629629631NA
27.52NANA0.0402314814814815NA
37.57NANA0.0494675925925928NA
47.59NANA0.076273148148148NA
57.58NANA-0.0101851851851851NA
67.55NANA-0.0324074074074065NA
77.527.612731481481487.581666666666670.0310648148148149-0.0927314814814819
87.557.625787037037047.604166666666670.0216203703703701-0.0757870370370375
97.627.569467592592597.605-0.03553240740740790.0505324074074087
107.647.621273148148157.605416666666670.01585648148148140.0187268518518522
117.687.53870370370377.61291666666667-0.07421296296296310.141296296296297
127.697.567870370370377.62208333333333-0.05421296296296310.122129629629631
137.77.60620370370377.63416666666667-0.02796296296296310.093796296296298
147.67.688981481481487.648750.0402314814814815-0.08898148148148
157.517.710300925925927.660833333333330.0494675925925928-0.200300925925925
167.667.747106481481487.670833333333330.076273148148148-0.0871064814814808
177.697.667314814814827.6775-0.01018518518518510.0226851851851846
187.667.648425925925937.68083333333333-0.03240740740740650.0115740740740735
197.77.715648148148157.684583333333330.0310648148148149-0.0156481481481467
207.727.729120370370377.70750.0216203703703701-0.00912037037037017
217.747.722384259259267.75791666666667-0.03553240740740790.0176157407407418
227.767.830856481481487.8150.0158564814814814-0.0708564814814823
237.727.784120370370377.85833333333333-0.0742129629629631-0.0641203703703699
247.737.841620370370377.89583333333333-0.0542129629629631-0.111620370370369
257.757.915787037037047.94375-0.0279629629629631-0.165787037037038
268.18.036064814814817.995833333333330.04023148148148150.0639351851851861
278.228.092384259259268.042916666666670.04946759259259280.127615740740740
288.328.165439814814828.089166666666670.0762731481481480.154560185185185
298.078.130648148148158.14083333333333-0.0101851851851851-0.0606481481481485
308.188.160509259259268.19291666666667-0.03240740740740650.0194907407407410
318.338.276898148148158.245833333333330.03106481481481490.0531018518518511
328.348.307037037037048.285416666666670.02162037037037010.0329629629629640
338.258.27071759259268.30625-0.0355324074074079-0.0207175925925931
348.368.335856481481488.320.01585648148148140.0241435185185175
358.368.268287037037048.3425-0.07421296296296310.0917129629629638
368.348.317870370370378.37208333333333-0.05421296296296310.0221296296296298
378.418.364537037037048.3925-0.02796296296296310.0454629629629633
388.398.448564814814818.408333333333330.0402314814814815-0.0585648148148135
398.438.476134259259268.426666666666670.0494675925925928-0.0461342592592597
408.448.520856481481488.444583333333330.076273148148148-0.080856481481483
418.498.448981481481488.45916666666666-0.01018518518518510.0410185185185199
428.478.442175925925938.47458333333333-0.03240740740740650.0278240740740756
438.538.516064814814818.4850.03106481481481490.0139351851851863
448.528.519120370370378.49750.02162037037037010.000879629629629619
458.518.48196759259268.5175-0.03553240740740790.028032407407407
468.538.555439814814818.539583333333330.0158564814814814-0.0254398148148152
478.548.480787037037048.555-0.07421296296296310.0592129629629632
488.538.50745370370378.56166666666667-0.05421296296296310.0225462962962943
498.478.54120370370378.56916666666667-0.0279629629629631-0.0712037037037039
508.638.618981481481488.578750.04023148148148150.0110185185185188
518.678.63071759259268.581250.04946759259259280.0392824074074039
528.738.658356481481488.582083333333330.0762731481481480.0716435185185187
538.578.568564814814828.57875-0.01018518518518510.00143518518518526
548.558.541759259259268.57416666666666-0.03240740740740650.00824074074074232
558.638.623148148148158.592083333333330.03106481481481490.00685185185185233
568.658.632870370370378.611250.02162037037037010.0171296296296308
578.448.584884259259268.62041666666667-0.0355324074074079-0.144884259259261
588.628.640023148148158.624166666666670.0158564814814814-0.0200231481481481
598.378.552870370370378.62708333333333-0.0742129629629631-0.18287037037037
608.598.578287037037048.6325-0.05421296296296310.0117129629629638
618.848.614537037037048.6425-0.02796296296296310.225462962962965
628.728.700231481481488.660.04023148148148150.0197685185185197
638.88.734884259259268.685416666666670.04946759259259280.0651157407407421
648.698.791689814814818.715416666666670.076273148148148-0.101689814814815
658.688.733981481481488.74416666666667-0.0101851851851851-0.0539814814814825
668.578.735509259259268.76791666666667-0.0324074074074065-0.165509259259260
678.858.803981481481488.772916666666670.03106481481481490.0460185185185171
688.858.804537037037038.782916666666670.02162037037037010.045462962962965
698.858.769050925925938.80458333333333-0.03553240740740790.0809490740740735
708.938.845023148148158.829166666666660.01585648148148140.0849768518518541
718.758.78370370370378.85791666666667-0.0742129629629631-0.0337037037037025
728.788.835370370370378.88958333333333-0.0542129629629631-0.0553703703703725
738.778.88620370370378.91416666666667-0.0279629629629631-0.116203703703704
749.038.965648148148158.925416666666670.04023148148148150.0643518518518515
759.018.984050925925938.934583333333330.04946759259259280.0259490740740738
769.079.015023148148158.938750.0762731481481480.054976851851853
778.998.928981481481488.93916666666667-0.01018518518518510.0610185185185177
789.028.91009259259268.9425-0.03240740740740650.109907407407407
798.99NANA0.0310648148148149NA
808.98NANA0.0216203703703701NA
818.94NANA-0.0355324074074079NA
828.94NANA0.0158564814814814NA
838.75NANA-0.0742129629629631NA
848.86NANA-0.0542129629629631NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 7.24 & NA & NA & -0.0279629629629631 & NA \tabularnewline
2 & 7.52 & NA & NA & 0.0402314814814815 & NA \tabularnewline
3 & 7.57 & NA & NA & 0.0494675925925928 & NA \tabularnewline
4 & 7.59 & NA & NA & 0.076273148148148 & NA \tabularnewline
5 & 7.58 & NA & NA & -0.0101851851851851 & NA \tabularnewline
6 & 7.55 & NA & NA & -0.0324074074074065 & NA \tabularnewline
7 & 7.52 & 7.61273148148148 & 7.58166666666667 & 0.0310648148148149 & -0.0927314814814819 \tabularnewline
8 & 7.55 & 7.62578703703704 & 7.60416666666667 & 0.0216203703703701 & -0.0757870370370375 \tabularnewline
9 & 7.62 & 7.56946759259259 & 7.605 & -0.0355324074074079 & 0.0505324074074087 \tabularnewline
10 & 7.64 & 7.62127314814815 & 7.60541666666667 & 0.0158564814814814 & 0.0187268518518522 \tabularnewline
11 & 7.68 & 7.5387037037037 & 7.61291666666667 & -0.0742129629629631 & 0.141296296296297 \tabularnewline
12 & 7.69 & 7.56787037037037 & 7.62208333333333 & -0.0542129629629631 & 0.122129629629631 \tabularnewline
13 & 7.7 & 7.6062037037037 & 7.63416666666667 & -0.0279629629629631 & 0.093796296296298 \tabularnewline
14 & 7.6 & 7.68898148148148 & 7.64875 & 0.0402314814814815 & -0.08898148148148 \tabularnewline
15 & 7.51 & 7.71030092592592 & 7.66083333333333 & 0.0494675925925928 & -0.200300925925925 \tabularnewline
16 & 7.66 & 7.74710648148148 & 7.67083333333333 & 0.076273148148148 & -0.0871064814814808 \tabularnewline
17 & 7.69 & 7.66731481481482 & 7.6775 & -0.0101851851851851 & 0.0226851851851846 \tabularnewline
18 & 7.66 & 7.64842592592593 & 7.68083333333333 & -0.0324074074074065 & 0.0115740740740735 \tabularnewline
19 & 7.7 & 7.71564814814815 & 7.68458333333333 & 0.0310648148148149 & -0.0156481481481467 \tabularnewline
20 & 7.72 & 7.72912037037037 & 7.7075 & 0.0216203703703701 & -0.00912037037037017 \tabularnewline
21 & 7.74 & 7.72238425925926 & 7.75791666666667 & -0.0355324074074079 & 0.0176157407407418 \tabularnewline
22 & 7.76 & 7.83085648148148 & 7.815 & 0.0158564814814814 & -0.0708564814814823 \tabularnewline
23 & 7.72 & 7.78412037037037 & 7.85833333333333 & -0.0742129629629631 & -0.0641203703703699 \tabularnewline
24 & 7.73 & 7.84162037037037 & 7.89583333333333 & -0.0542129629629631 & -0.111620370370369 \tabularnewline
25 & 7.75 & 7.91578703703704 & 7.94375 & -0.0279629629629631 & -0.165787037037038 \tabularnewline
26 & 8.1 & 8.03606481481481 & 7.99583333333333 & 0.0402314814814815 & 0.0639351851851861 \tabularnewline
27 & 8.22 & 8.09238425925926 & 8.04291666666667 & 0.0494675925925928 & 0.127615740740740 \tabularnewline
28 & 8.32 & 8.16543981481482 & 8.08916666666667 & 0.076273148148148 & 0.154560185185185 \tabularnewline
29 & 8.07 & 8.13064814814815 & 8.14083333333333 & -0.0101851851851851 & -0.0606481481481485 \tabularnewline
30 & 8.18 & 8.16050925925926 & 8.19291666666667 & -0.0324074074074065 & 0.0194907407407410 \tabularnewline
31 & 8.33 & 8.27689814814815 & 8.24583333333333 & 0.0310648148148149 & 0.0531018518518511 \tabularnewline
32 & 8.34 & 8.30703703703704 & 8.28541666666667 & 0.0216203703703701 & 0.0329629629629640 \tabularnewline
33 & 8.25 & 8.2707175925926 & 8.30625 & -0.0355324074074079 & -0.0207175925925931 \tabularnewline
34 & 8.36 & 8.33585648148148 & 8.32 & 0.0158564814814814 & 0.0241435185185175 \tabularnewline
35 & 8.36 & 8.26828703703704 & 8.3425 & -0.0742129629629631 & 0.0917129629629638 \tabularnewline
36 & 8.34 & 8.31787037037037 & 8.37208333333333 & -0.0542129629629631 & 0.0221296296296298 \tabularnewline
37 & 8.41 & 8.36453703703704 & 8.3925 & -0.0279629629629631 & 0.0454629629629633 \tabularnewline
38 & 8.39 & 8.44856481481481 & 8.40833333333333 & 0.0402314814814815 & -0.0585648148148135 \tabularnewline
39 & 8.43 & 8.47613425925926 & 8.42666666666667 & 0.0494675925925928 & -0.0461342592592597 \tabularnewline
40 & 8.44 & 8.52085648148148 & 8.44458333333333 & 0.076273148148148 & -0.080856481481483 \tabularnewline
41 & 8.49 & 8.44898148148148 & 8.45916666666666 & -0.0101851851851851 & 0.0410185185185199 \tabularnewline
42 & 8.47 & 8.44217592592593 & 8.47458333333333 & -0.0324074074074065 & 0.0278240740740756 \tabularnewline
43 & 8.53 & 8.51606481481481 & 8.485 & 0.0310648148148149 & 0.0139351851851863 \tabularnewline
44 & 8.52 & 8.51912037037037 & 8.4975 & 0.0216203703703701 & 0.000879629629629619 \tabularnewline
45 & 8.51 & 8.4819675925926 & 8.5175 & -0.0355324074074079 & 0.028032407407407 \tabularnewline
46 & 8.53 & 8.55543981481481 & 8.53958333333333 & 0.0158564814814814 & -0.0254398148148152 \tabularnewline
47 & 8.54 & 8.48078703703704 & 8.555 & -0.0742129629629631 & 0.0592129629629632 \tabularnewline
48 & 8.53 & 8.5074537037037 & 8.56166666666667 & -0.0542129629629631 & 0.0225462962962943 \tabularnewline
49 & 8.47 & 8.5412037037037 & 8.56916666666667 & -0.0279629629629631 & -0.0712037037037039 \tabularnewline
50 & 8.63 & 8.61898148148148 & 8.57875 & 0.0402314814814815 & 0.0110185185185188 \tabularnewline
51 & 8.67 & 8.6307175925926 & 8.58125 & 0.0494675925925928 & 0.0392824074074039 \tabularnewline
52 & 8.73 & 8.65835648148148 & 8.58208333333333 & 0.076273148148148 & 0.0716435185185187 \tabularnewline
53 & 8.57 & 8.56856481481482 & 8.57875 & -0.0101851851851851 & 0.00143518518518526 \tabularnewline
54 & 8.55 & 8.54175925925926 & 8.57416666666666 & -0.0324074074074065 & 0.00824074074074232 \tabularnewline
55 & 8.63 & 8.62314814814815 & 8.59208333333333 & 0.0310648148148149 & 0.00685185185185233 \tabularnewline
56 & 8.65 & 8.63287037037037 & 8.61125 & 0.0216203703703701 & 0.0171296296296308 \tabularnewline
57 & 8.44 & 8.58488425925926 & 8.62041666666667 & -0.0355324074074079 & -0.144884259259261 \tabularnewline
58 & 8.62 & 8.64002314814815 & 8.62416666666667 & 0.0158564814814814 & -0.0200231481481481 \tabularnewline
59 & 8.37 & 8.55287037037037 & 8.62708333333333 & -0.0742129629629631 & -0.18287037037037 \tabularnewline
60 & 8.59 & 8.57828703703704 & 8.6325 & -0.0542129629629631 & 0.0117129629629638 \tabularnewline
61 & 8.84 & 8.61453703703704 & 8.6425 & -0.0279629629629631 & 0.225462962962965 \tabularnewline
62 & 8.72 & 8.70023148148148 & 8.66 & 0.0402314814814815 & 0.0197685185185197 \tabularnewline
63 & 8.8 & 8.73488425925926 & 8.68541666666667 & 0.0494675925925928 & 0.0651157407407421 \tabularnewline
64 & 8.69 & 8.79168981481481 & 8.71541666666667 & 0.076273148148148 & -0.101689814814815 \tabularnewline
65 & 8.68 & 8.73398148148148 & 8.74416666666667 & -0.0101851851851851 & -0.0539814814814825 \tabularnewline
66 & 8.57 & 8.73550925925926 & 8.76791666666667 & -0.0324074074074065 & -0.165509259259260 \tabularnewline
67 & 8.85 & 8.80398148148148 & 8.77291666666667 & 0.0310648148148149 & 0.0460185185185171 \tabularnewline
68 & 8.85 & 8.80453703703703 & 8.78291666666667 & 0.0216203703703701 & 0.045462962962965 \tabularnewline
69 & 8.85 & 8.76905092592593 & 8.80458333333333 & -0.0355324074074079 & 0.0809490740740735 \tabularnewline
70 & 8.93 & 8.84502314814815 & 8.82916666666666 & 0.0158564814814814 & 0.0849768518518541 \tabularnewline
71 & 8.75 & 8.7837037037037 & 8.85791666666667 & -0.0742129629629631 & -0.0337037037037025 \tabularnewline
72 & 8.78 & 8.83537037037037 & 8.88958333333333 & -0.0542129629629631 & -0.0553703703703725 \tabularnewline
73 & 8.77 & 8.8862037037037 & 8.91416666666667 & -0.0279629629629631 & -0.116203703703704 \tabularnewline
74 & 9.03 & 8.96564814814815 & 8.92541666666667 & 0.0402314814814815 & 0.0643518518518515 \tabularnewline
75 & 9.01 & 8.98405092592593 & 8.93458333333333 & 0.0494675925925928 & 0.0259490740740738 \tabularnewline
76 & 9.07 & 9.01502314814815 & 8.93875 & 0.076273148148148 & 0.054976851851853 \tabularnewline
77 & 8.99 & 8.92898148148148 & 8.93916666666667 & -0.0101851851851851 & 0.0610185185185177 \tabularnewline
78 & 9.02 & 8.9100925925926 & 8.9425 & -0.0324074074074065 & 0.109907407407407 \tabularnewline
79 & 8.99 & NA & NA & 0.0310648148148149 & NA \tabularnewline
80 & 8.98 & NA & NA & 0.0216203703703701 & NA \tabularnewline
81 & 8.94 & NA & NA & -0.0355324074074079 & NA \tabularnewline
82 & 8.94 & NA & NA & 0.0158564814814814 & NA \tabularnewline
83 & 8.75 & NA & NA & -0.0742129629629631 & NA \tabularnewline
84 & 8.86 & NA & NA & -0.0542129629629631 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105612&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]7.24[/C][C]NA[/C][C]NA[/C][C]-0.0279629629629631[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]7.52[/C][C]NA[/C][C]NA[/C][C]0.0402314814814815[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]7.57[/C][C]NA[/C][C]NA[/C][C]0.0494675925925928[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]7.59[/C][C]NA[/C][C]NA[/C][C]0.076273148148148[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]7.58[/C][C]NA[/C][C]NA[/C][C]-0.0101851851851851[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]7.55[/C][C]NA[/C][C]NA[/C][C]-0.0324074074074065[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]7.52[/C][C]7.61273148148148[/C][C]7.58166666666667[/C][C]0.0310648148148149[/C][C]-0.0927314814814819[/C][/ROW]
[ROW][C]8[/C][C]7.55[/C][C]7.62578703703704[/C][C]7.60416666666667[/C][C]0.0216203703703701[/C][C]-0.0757870370370375[/C][/ROW]
[ROW][C]9[/C][C]7.62[/C][C]7.56946759259259[/C][C]7.605[/C][C]-0.0355324074074079[/C][C]0.0505324074074087[/C][/ROW]
[ROW][C]10[/C][C]7.64[/C][C]7.62127314814815[/C][C]7.60541666666667[/C][C]0.0158564814814814[/C][C]0.0187268518518522[/C][/ROW]
[ROW][C]11[/C][C]7.68[/C][C]7.5387037037037[/C][C]7.61291666666667[/C][C]-0.0742129629629631[/C][C]0.141296296296297[/C][/ROW]
[ROW][C]12[/C][C]7.69[/C][C]7.56787037037037[/C][C]7.62208333333333[/C][C]-0.0542129629629631[/C][C]0.122129629629631[/C][/ROW]
[ROW][C]13[/C][C]7.7[/C][C]7.6062037037037[/C][C]7.63416666666667[/C][C]-0.0279629629629631[/C][C]0.093796296296298[/C][/ROW]
[ROW][C]14[/C][C]7.6[/C][C]7.68898148148148[/C][C]7.64875[/C][C]0.0402314814814815[/C][C]-0.08898148148148[/C][/ROW]
[ROW][C]15[/C][C]7.51[/C][C]7.71030092592592[/C][C]7.66083333333333[/C][C]0.0494675925925928[/C][C]-0.200300925925925[/C][/ROW]
[ROW][C]16[/C][C]7.66[/C][C]7.74710648148148[/C][C]7.67083333333333[/C][C]0.076273148148148[/C][C]-0.0871064814814808[/C][/ROW]
[ROW][C]17[/C][C]7.69[/C][C]7.66731481481482[/C][C]7.6775[/C][C]-0.0101851851851851[/C][C]0.0226851851851846[/C][/ROW]
[ROW][C]18[/C][C]7.66[/C][C]7.64842592592593[/C][C]7.68083333333333[/C][C]-0.0324074074074065[/C][C]0.0115740740740735[/C][/ROW]
[ROW][C]19[/C][C]7.7[/C][C]7.71564814814815[/C][C]7.68458333333333[/C][C]0.0310648148148149[/C][C]-0.0156481481481467[/C][/ROW]
[ROW][C]20[/C][C]7.72[/C][C]7.72912037037037[/C][C]7.7075[/C][C]0.0216203703703701[/C][C]-0.00912037037037017[/C][/ROW]
[ROW][C]21[/C][C]7.74[/C][C]7.72238425925926[/C][C]7.75791666666667[/C][C]-0.0355324074074079[/C][C]0.0176157407407418[/C][/ROW]
[ROW][C]22[/C][C]7.76[/C][C]7.83085648148148[/C][C]7.815[/C][C]0.0158564814814814[/C][C]-0.0708564814814823[/C][/ROW]
[ROW][C]23[/C][C]7.72[/C][C]7.78412037037037[/C][C]7.85833333333333[/C][C]-0.0742129629629631[/C][C]-0.0641203703703699[/C][/ROW]
[ROW][C]24[/C][C]7.73[/C][C]7.84162037037037[/C][C]7.89583333333333[/C][C]-0.0542129629629631[/C][C]-0.111620370370369[/C][/ROW]
[ROW][C]25[/C][C]7.75[/C][C]7.91578703703704[/C][C]7.94375[/C][C]-0.0279629629629631[/C][C]-0.165787037037038[/C][/ROW]
[ROW][C]26[/C][C]8.1[/C][C]8.03606481481481[/C][C]7.99583333333333[/C][C]0.0402314814814815[/C][C]0.0639351851851861[/C][/ROW]
[ROW][C]27[/C][C]8.22[/C][C]8.09238425925926[/C][C]8.04291666666667[/C][C]0.0494675925925928[/C][C]0.127615740740740[/C][/ROW]
[ROW][C]28[/C][C]8.32[/C][C]8.16543981481482[/C][C]8.08916666666667[/C][C]0.076273148148148[/C][C]0.154560185185185[/C][/ROW]
[ROW][C]29[/C][C]8.07[/C][C]8.13064814814815[/C][C]8.14083333333333[/C][C]-0.0101851851851851[/C][C]-0.0606481481481485[/C][/ROW]
[ROW][C]30[/C][C]8.18[/C][C]8.16050925925926[/C][C]8.19291666666667[/C][C]-0.0324074074074065[/C][C]0.0194907407407410[/C][/ROW]
[ROW][C]31[/C][C]8.33[/C][C]8.27689814814815[/C][C]8.24583333333333[/C][C]0.0310648148148149[/C][C]0.0531018518518511[/C][/ROW]
[ROW][C]32[/C][C]8.34[/C][C]8.30703703703704[/C][C]8.28541666666667[/C][C]0.0216203703703701[/C][C]0.0329629629629640[/C][/ROW]
[ROW][C]33[/C][C]8.25[/C][C]8.2707175925926[/C][C]8.30625[/C][C]-0.0355324074074079[/C][C]-0.0207175925925931[/C][/ROW]
[ROW][C]34[/C][C]8.36[/C][C]8.33585648148148[/C][C]8.32[/C][C]0.0158564814814814[/C][C]0.0241435185185175[/C][/ROW]
[ROW][C]35[/C][C]8.36[/C][C]8.26828703703704[/C][C]8.3425[/C][C]-0.0742129629629631[/C][C]0.0917129629629638[/C][/ROW]
[ROW][C]36[/C][C]8.34[/C][C]8.31787037037037[/C][C]8.37208333333333[/C][C]-0.0542129629629631[/C][C]0.0221296296296298[/C][/ROW]
[ROW][C]37[/C][C]8.41[/C][C]8.36453703703704[/C][C]8.3925[/C][C]-0.0279629629629631[/C][C]0.0454629629629633[/C][/ROW]
[ROW][C]38[/C][C]8.39[/C][C]8.44856481481481[/C][C]8.40833333333333[/C][C]0.0402314814814815[/C][C]-0.0585648148148135[/C][/ROW]
[ROW][C]39[/C][C]8.43[/C][C]8.47613425925926[/C][C]8.42666666666667[/C][C]0.0494675925925928[/C][C]-0.0461342592592597[/C][/ROW]
[ROW][C]40[/C][C]8.44[/C][C]8.52085648148148[/C][C]8.44458333333333[/C][C]0.076273148148148[/C][C]-0.080856481481483[/C][/ROW]
[ROW][C]41[/C][C]8.49[/C][C]8.44898148148148[/C][C]8.45916666666666[/C][C]-0.0101851851851851[/C][C]0.0410185185185199[/C][/ROW]
[ROW][C]42[/C][C]8.47[/C][C]8.44217592592593[/C][C]8.47458333333333[/C][C]-0.0324074074074065[/C][C]0.0278240740740756[/C][/ROW]
[ROW][C]43[/C][C]8.53[/C][C]8.51606481481481[/C][C]8.485[/C][C]0.0310648148148149[/C][C]0.0139351851851863[/C][/ROW]
[ROW][C]44[/C][C]8.52[/C][C]8.51912037037037[/C][C]8.4975[/C][C]0.0216203703703701[/C][C]0.000879629629629619[/C][/ROW]
[ROW][C]45[/C][C]8.51[/C][C]8.4819675925926[/C][C]8.5175[/C][C]-0.0355324074074079[/C][C]0.028032407407407[/C][/ROW]
[ROW][C]46[/C][C]8.53[/C][C]8.55543981481481[/C][C]8.53958333333333[/C][C]0.0158564814814814[/C][C]-0.0254398148148152[/C][/ROW]
[ROW][C]47[/C][C]8.54[/C][C]8.48078703703704[/C][C]8.555[/C][C]-0.0742129629629631[/C][C]0.0592129629629632[/C][/ROW]
[ROW][C]48[/C][C]8.53[/C][C]8.5074537037037[/C][C]8.56166666666667[/C][C]-0.0542129629629631[/C][C]0.0225462962962943[/C][/ROW]
[ROW][C]49[/C][C]8.47[/C][C]8.5412037037037[/C][C]8.56916666666667[/C][C]-0.0279629629629631[/C][C]-0.0712037037037039[/C][/ROW]
[ROW][C]50[/C][C]8.63[/C][C]8.61898148148148[/C][C]8.57875[/C][C]0.0402314814814815[/C][C]0.0110185185185188[/C][/ROW]
[ROW][C]51[/C][C]8.67[/C][C]8.6307175925926[/C][C]8.58125[/C][C]0.0494675925925928[/C][C]0.0392824074074039[/C][/ROW]
[ROW][C]52[/C][C]8.73[/C][C]8.65835648148148[/C][C]8.58208333333333[/C][C]0.076273148148148[/C][C]0.0716435185185187[/C][/ROW]
[ROW][C]53[/C][C]8.57[/C][C]8.56856481481482[/C][C]8.57875[/C][C]-0.0101851851851851[/C][C]0.00143518518518526[/C][/ROW]
[ROW][C]54[/C][C]8.55[/C][C]8.54175925925926[/C][C]8.57416666666666[/C][C]-0.0324074074074065[/C][C]0.00824074074074232[/C][/ROW]
[ROW][C]55[/C][C]8.63[/C][C]8.62314814814815[/C][C]8.59208333333333[/C][C]0.0310648148148149[/C][C]0.00685185185185233[/C][/ROW]
[ROW][C]56[/C][C]8.65[/C][C]8.63287037037037[/C][C]8.61125[/C][C]0.0216203703703701[/C][C]0.0171296296296308[/C][/ROW]
[ROW][C]57[/C][C]8.44[/C][C]8.58488425925926[/C][C]8.62041666666667[/C][C]-0.0355324074074079[/C][C]-0.144884259259261[/C][/ROW]
[ROW][C]58[/C][C]8.62[/C][C]8.64002314814815[/C][C]8.62416666666667[/C][C]0.0158564814814814[/C][C]-0.0200231481481481[/C][/ROW]
[ROW][C]59[/C][C]8.37[/C][C]8.55287037037037[/C][C]8.62708333333333[/C][C]-0.0742129629629631[/C][C]-0.18287037037037[/C][/ROW]
[ROW][C]60[/C][C]8.59[/C][C]8.57828703703704[/C][C]8.6325[/C][C]-0.0542129629629631[/C][C]0.0117129629629638[/C][/ROW]
[ROW][C]61[/C][C]8.84[/C][C]8.61453703703704[/C][C]8.6425[/C][C]-0.0279629629629631[/C][C]0.225462962962965[/C][/ROW]
[ROW][C]62[/C][C]8.72[/C][C]8.70023148148148[/C][C]8.66[/C][C]0.0402314814814815[/C][C]0.0197685185185197[/C][/ROW]
[ROW][C]63[/C][C]8.8[/C][C]8.73488425925926[/C][C]8.68541666666667[/C][C]0.0494675925925928[/C][C]0.0651157407407421[/C][/ROW]
[ROW][C]64[/C][C]8.69[/C][C]8.79168981481481[/C][C]8.71541666666667[/C][C]0.076273148148148[/C][C]-0.101689814814815[/C][/ROW]
[ROW][C]65[/C][C]8.68[/C][C]8.73398148148148[/C][C]8.74416666666667[/C][C]-0.0101851851851851[/C][C]-0.0539814814814825[/C][/ROW]
[ROW][C]66[/C][C]8.57[/C][C]8.73550925925926[/C][C]8.76791666666667[/C][C]-0.0324074074074065[/C][C]-0.165509259259260[/C][/ROW]
[ROW][C]67[/C][C]8.85[/C][C]8.80398148148148[/C][C]8.77291666666667[/C][C]0.0310648148148149[/C][C]0.0460185185185171[/C][/ROW]
[ROW][C]68[/C][C]8.85[/C][C]8.80453703703703[/C][C]8.78291666666667[/C][C]0.0216203703703701[/C][C]0.045462962962965[/C][/ROW]
[ROW][C]69[/C][C]8.85[/C][C]8.76905092592593[/C][C]8.80458333333333[/C][C]-0.0355324074074079[/C][C]0.0809490740740735[/C][/ROW]
[ROW][C]70[/C][C]8.93[/C][C]8.84502314814815[/C][C]8.82916666666666[/C][C]0.0158564814814814[/C][C]0.0849768518518541[/C][/ROW]
[ROW][C]71[/C][C]8.75[/C][C]8.7837037037037[/C][C]8.85791666666667[/C][C]-0.0742129629629631[/C][C]-0.0337037037037025[/C][/ROW]
[ROW][C]72[/C][C]8.78[/C][C]8.83537037037037[/C][C]8.88958333333333[/C][C]-0.0542129629629631[/C][C]-0.0553703703703725[/C][/ROW]
[ROW][C]73[/C][C]8.77[/C][C]8.8862037037037[/C][C]8.91416666666667[/C][C]-0.0279629629629631[/C][C]-0.116203703703704[/C][/ROW]
[ROW][C]74[/C][C]9.03[/C][C]8.96564814814815[/C][C]8.92541666666667[/C][C]0.0402314814814815[/C][C]0.0643518518518515[/C][/ROW]
[ROW][C]75[/C][C]9.01[/C][C]8.98405092592593[/C][C]8.93458333333333[/C][C]0.0494675925925928[/C][C]0.0259490740740738[/C][/ROW]
[ROW][C]76[/C][C]9.07[/C][C]9.01502314814815[/C][C]8.93875[/C][C]0.076273148148148[/C][C]0.054976851851853[/C][/ROW]
[ROW][C]77[/C][C]8.99[/C][C]8.92898148148148[/C][C]8.93916666666667[/C][C]-0.0101851851851851[/C][C]0.0610185185185177[/C][/ROW]
[ROW][C]78[/C][C]9.02[/C][C]8.9100925925926[/C][C]8.9425[/C][C]-0.0324074074074065[/C][C]0.109907407407407[/C][/ROW]
[ROW][C]79[/C][C]8.99[/C][C]NA[/C][C]NA[/C][C]0.0310648148148149[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]8.98[/C][C]NA[/C][C]NA[/C][C]0.0216203703703701[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]8.94[/C][C]NA[/C][C]NA[/C][C]-0.0355324074074079[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]8.94[/C][C]NA[/C][C]NA[/C][C]0.0158564814814814[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]8.75[/C][C]NA[/C][C]NA[/C][C]-0.0742129629629631[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]8.86[/C][C]NA[/C][C]NA[/C][C]-0.0542129629629631[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105612&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105612&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
17.24NANA-0.0279629629629631NA
27.52NANA0.0402314814814815NA
37.57NANA0.0494675925925928NA
47.59NANA0.076273148148148NA
57.58NANA-0.0101851851851851NA
67.55NANA-0.0324074074074065NA
77.527.612731481481487.581666666666670.0310648148148149-0.0927314814814819
87.557.625787037037047.604166666666670.0216203703703701-0.0757870370370375
97.627.569467592592597.605-0.03553240740740790.0505324074074087
107.647.621273148148157.605416666666670.01585648148148140.0187268518518522
117.687.53870370370377.61291666666667-0.07421296296296310.141296296296297
127.697.567870370370377.62208333333333-0.05421296296296310.122129629629631
137.77.60620370370377.63416666666667-0.02796296296296310.093796296296298
147.67.688981481481487.648750.0402314814814815-0.08898148148148
157.517.710300925925927.660833333333330.0494675925925928-0.200300925925925
167.667.747106481481487.670833333333330.076273148148148-0.0871064814814808
177.697.667314814814827.6775-0.01018518518518510.0226851851851846
187.667.648425925925937.68083333333333-0.03240740740740650.0115740740740735
197.77.715648148148157.684583333333330.0310648148148149-0.0156481481481467
207.727.729120370370377.70750.0216203703703701-0.00912037037037017
217.747.722384259259267.75791666666667-0.03553240740740790.0176157407407418
227.767.830856481481487.8150.0158564814814814-0.0708564814814823
237.727.784120370370377.85833333333333-0.0742129629629631-0.0641203703703699
247.737.841620370370377.89583333333333-0.0542129629629631-0.111620370370369
257.757.915787037037047.94375-0.0279629629629631-0.165787037037038
268.18.036064814814817.995833333333330.04023148148148150.0639351851851861
278.228.092384259259268.042916666666670.04946759259259280.127615740740740
288.328.165439814814828.089166666666670.0762731481481480.154560185185185
298.078.130648148148158.14083333333333-0.0101851851851851-0.0606481481481485
308.188.160509259259268.19291666666667-0.03240740740740650.0194907407407410
318.338.276898148148158.245833333333330.03106481481481490.0531018518518511
328.348.307037037037048.285416666666670.02162037037037010.0329629629629640
338.258.27071759259268.30625-0.0355324074074079-0.0207175925925931
348.368.335856481481488.320.01585648148148140.0241435185185175
358.368.268287037037048.3425-0.07421296296296310.0917129629629638
368.348.317870370370378.37208333333333-0.05421296296296310.0221296296296298
378.418.364537037037048.3925-0.02796296296296310.0454629629629633
388.398.448564814814818.408333333333330.0402314814814815-0.0585648148148135
398.438.476134259259268.426666666666670.0494675925925928-0.0461342592592597
408.448.520856481481488.444583333333330.076273148148148-0.080856481481483
418.498.448981481481488.45916666666666-0.01018518518518510.0410185185185199
428.478.442175925925938.47458333333333-0.03240740740740650.0278240740740756
438.538.516064814814818.4850.03106481481481490.0139351851851863
448.528.519120370370378.49750.02162037037037010.000879629629629619
458.518.48196759259268.5175-0.03553240740740790.028032407407407
468.538.555439814814818.539583333333330.0158564814814814-0.0254398148148152
478.548.480787037037048.555-0.07421296296296310.0592129629629632
488.538.50745370370378.56166666666667-0.05421296296296310.0225462962962943
498.478.54120370370378.56916666666667-0.0279629629629631-0.0712037037037039
508.638.618981481481488.578750.04023148148148150.0110185185185188
518.678.63071759259268.581250.04946759259259280.0392824074074039
528.738.658356481481488.582083333333330.0762731481481480.0716435185185187
538.578.568564814814828.57875-0.01018518518518510.00143518518518526
548.558.541759259259268.57416666666666-0.03240740740740650.00824074074074232
558.638.623148148148158.592083333333330.03106481481481490.00685185185185233
568.658.632870370370378.611250.02162037037037010.0171296296296308
578.448.584884259259268.62041666666667-0.0355324074074079-0.144884259259261
588.628.640023148148158.624166666666670.0158564814814814-0.0200231481481481
598.378.552870370370378.62708333333333-0.0742129629629631-0.18287037037037
608.598.578287037037048.6325-0.05421296296296310.0117129629629638
618.848.614537037037048.6425-0.02796296296296310.225462962962965
628.728.700231481481488.660.04023148148148150.0197685185185197
638.88.734884259259268.685416666666670.04946759259259280.0651157407407421
648.698.791689814814818.715416666666670.076273148148148-0.101689814814815
658.688.733981481481488.74416666666667-0.0101851851851851-0.0539814814814825
668.578.735509259259268.76791666666667-0.0324074074074065-0.165509259259260
678.858.803981481481488.772916666666670.03106481481481490.0460185185185171
688.858.804537037037038.782916666666670.02162037037037010.045462962962965
698.858.769050925925938.80458333333333-0.03553240740740790.0809490740740735
708.938.845023148148158.829166666666660.01585648148148140.0849768518518541
718.758.78370370370378.85791666666667-0.0742129629629631-0.0337037037037025
728.788.835370370370378.88958333333333-0.0542129629629631-0.0553703703703725
738.778.88620370370378.91416666666667-0.0279629629629631-0.116203703703704
749.038.965648148148158.925416666666670.04023148148148150.0643518518518515
759.018.984050925925938.934583333333330.04946759259259280.0259490740740738
769.079.015023148148158.938750.0762731481481480.054976851851853
778.998.928981481481488.93916666666667-0.01018518518518510.0610185185185177
789.028.91009259259268.9425-0.03240740740740650.109907407407407
798.99NANA0.0310648148148149NA
808.98NANA0.0216203703703701NA
818.94NANA-0.0355324074074079NA
828.94NANA0.0158564814814814NA
838.75NANA-0.0742129629629631NA
848.86NANA-0.0542129629629631NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; 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')