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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 08:38:18 -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/Dec/12/t13868556947sdkf9ofztw12k9.htm/, Retrieved Tue, 07 Dec 2021 11:04:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232247, Retrieved Tue, 07 Dec 2021 11:04:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 13:38:18] [e13de47ca0b629216b947109e84252a5] [Current]
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Dataseries X:
16,68
16,68
16,69
16,61
16,58
16,6
16,6
16,62
16,62
16,6
16,63
16,66
16,66
16,65
16,5
16,39
16,34
16,35
16,35
16,38
16,36
16,38
16,39
16,41
16,41
16,41
16,45
16,41
16,44
16,47
16,47
16,49
16,54
16,62
16,69
16,72
16,72
16,71
16,89
16,93
16,91
16,93
16,93
16,93
16,95
16,93
16,95
16,95
16,95
16,95
16,92
16,91
16,9
16,96
16,96
16,95
16,92
16,87
16,87
16,88
16,88
16,86
16,88
16,88
16,88
16,88
16,88
16,87
16,92
16,94
17,03
17,02
17,02
17,02
16,99
17,03
16,98
16,89
16,89
16,9
16,89
16,96
16,97
16,97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232247&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232247&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232247&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
116.68NANA0.0253819NA
216.68NANA0.0147569NA
316.69NANA0.0159375NA
416.61NANA-0.00177083NA
516.58NANA-0.0232986NA
616.6NANA-0.0228125NA
716.616.609116.63-0.0209375-0.0090625
816.6216.610616.6279-0.01732640.00940972
916.6216.608616.6188-0.01010420.0113542
1016.616.591616.6017-0.01010420.0084375
1116.6316.603416.58250.02086810.0266319
1216.6616.591516.56210.02940970.0685069
1316.6616.566616.54120.02538190.0933681
1416.6516.535616.52080.01475690.11441
1516.516.515916.50.0159375-0.0159375
1616.3916.478216.48-0.00177083-0.0882292
1716.3416.437516.4608-0.0232986-0.0975347
1816.3516.417616.4404-0.0228125-0.0676042
1916.3516.398616.4196-0.0209375-0.0486458
2016.3816.381816.3992-0.0173264-0.00184028
2116.3616.37716.3871-0.0101042-0.0169792
2216.3816.375716.3858-0.01010420.00427083
2316.3916.411716.39080.0208681-0.0217014
2416.4116.429416.40.0294097-0.0194097
2516.4116.435416.410.0253819-0.0253819
2616.4116.434316.41960.0147569-0.0243403
2716.4516.447616.43170.01593750.00239583
2816.4116.447416.4492-0.00177083-0.0373958
2916.4416.448416.4717-0.0232986-0.00836806
3016.4716.474316.4971-0.0228125-0.00427083
3116.4716.50216.5229-0.0209375-0.0319792
3216.4916.53116.5483-0.0173264-0.0410069
3316.5416.569116.5792-0.0101042-0.0290625
3416.6216.609116.6192-0.01010420.0109375
3516.6916.681316.66040.02086810.00871528
3616.7216.728616.69920.0294097-0.00857639
3716.7216.762916.73750.0253819-0.0428819
3816.7116.789816.7750.0147569-0.0797569
3916.8916.826416.81040.01593750.0636458
4016.9316.838616.8404-0.001770830.0913542
4116.9116.840916.8642-0.02329860.0691319
4216.9316.861816.8846-0.02281250.0682292
4316.9316.882816.9037-0.02093750.0471875
4416.9316.90616.9233-0.01732640.0239931
4516.9516.924516.9346-0.01010420.0255208
4616.9316.924916.935-0.01010420.00510417
4716.9516.954616.93370.0208681-0.00461806
4816.9516.96416.93460.0294097-0.0139931
4916.9516.962516.93710.0253819-0.0124653
5016.9516.953916.93920.0147569-0.00392361
5116.9216.954716.93880.0159375-0.0346875
5216.9116.933216.935-0.00177083-0.0232292
5316.916.905916.9292-0.0232986-0.00586806
5416.9616.900116.9229-0.02281250.0598958
5516.9616.896116.9171-0.02093750.0638542
5616.9516.893116.9104-0.01732640.0569097
5716.9216.894916.905-0.01010420.0251042
5816.8716.89216.9021-0.0101042-0.0219792
5916.8716.920916.90.0208681-0.0508681
6016.8816.925216.89580.0294097-0.0452431
6116.8816.914516.88920.0253819-0.0345486
6216.8616.897316.88250.0147569-0.0372569
6316.8816.895116.87920.0159375-0.0151042
6416.8816.880316.8821-0.00177083-0.0003125
6516.8816.868416.8917-0.02329860.0116319
6616.8816.881416.9042-0.0228125-0.00135417
6716.8816.894916.9158-0.0209375-0.0148958
6816.8716.91116.9283-0.0173264-0.0410069
6916.9216.929516.9396-0.0101042-0.00947917
7016.9416.940316.9504-0.0101042-0.0003125
7117.0316.981716.96080.02086810.0482986
7217.0216.994816.96540.02940970.0251736
7317.0216.991616.96620.02538190.0283681
7417.0216.982716.96790.01475690.0373264
7516.9916.983916.96790.01593750.00614583
7617.0316.965716.9675-0.001770830.0642708
7716.9816.942516.9658-0.02329860.0374653
7816.8916.938416.9612-0.0228125-0.0484375
7916.89NANA-0.0209375NA
8016.9NANA-0.0173264NA
8116.89NANA-0.0101042NA
8216.96NANA-0.0101042NA
8316.97NANA0.0208681NA
8416.97NANA0.0294097NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 16.68 & NA & NA & 0.0253819 & NA \tabularnewline
2 & 16.68 & NA & NA & 0.0147569 & NA \tabularnewline
3 & 16.69 & NA & NA & 0.0159375 & NA \tabularnewline
4 & 16.61 & NA & NA & -0.00177083 & NA \tabularnewline
5 & 16.58 & NA & NA & -0.0232986 & NA \tabularnewline
6 & 16.6 & NA & NA & -0.0228125 & NA \tabularnewline
7 & 16.6 & 16.6091 & 16.63 & -0.0209375 & -0.0090625 \tabularnewline
8 & 16.62 & 16.6106 & 16.6279 & -0.0173264 & 0.00940972 \tabularnewline
9 & 16.62 & 16.6086 & 16.6188 & -0.0101042 & 0.0113542 \tabularnewline
10 & 16.6 & 16.5916 & 16.6017 & -0.0101042 & 0.0084375 \tabularnewline
11 & 16.63 & 16.6034 & 16.5825 & 0.0208681 & 0.0266319 \tabularnewline
12 & 16.66 & 16.5915 & 16.5621 & 0.0294097 & 0.0685069 \tabularnewline
13 & 16.66 & 16.5666 & 16.5412 & 0.0253819 & 0.0933681 \tabularnewline
14 & 16.65 & 16.5356 & 16.5208 & 0.0147569 & 0.11441 \tabularnewline
15 & 16.5 & 16.5159 & 16.5 & 0.0159375 & -0.0159375 \tabularnewline
16 & 16.39 & 16.4782 & 16.48 & -0.00177083 & -0.0882292 \tabularnewline
17 & 16.34 & 16.4375 & 16.4608 & -0.0232986 & -0.0975347 \tabularnewline
18 & 16.35 & 16.4176 & 16.4404 & -0.0228125 & -0.0676042 \tabularnewline
19 & 16.35 & 16.3986 & 16.4196 & -0.0209375 & -0.0486458 \tabularnewline
20 & 16.38 & 16.3818 & 16.3992 & -0.0173264 & -0.00184028 \tabularnewline
21 & 16.36 & 16.377 & 16.3871 & -0.0101042 & -0.0169792 \tabularnewline
22 & 16.38 & 16.3757 & 16.3858 & -0.0101042 & 0.00427083 \tabularnewline
23 & 16.39 & 16.4117 & 16.3908 & 0.0208681 & -0.0217014 \tabularnewline
24 & 16.41 & 16.4294 & 16.4 & 0.0294097 & -0.0194097 \tabularnewline
25 & 16.41 & 16.4354 & 16.41 & 0.0253819 & -0.0253819 \tabularnewline
26 & 16.41 & 16.4343 & 16.4196 & 0.0147569 & -0.0243403 \tabularnewline
27 & 16.45 & 16.4476 & 16.4317 & 0.0159375 & 0.00239583 \tabularnewline
28 & 16.41 & 16.4474 & 16.4492 & -0.00177083 & -0.0373958 \tabularnewline
29 & 16.44 & 16.4484 & 16.4717 & -0.0232986 & -0.00836806 \tabularnewline
30 & 16.47 & 16.4743 & 16.4971 & -0.0228125 & -0.00427083 \tabularnewline
31 & 16.47 & 16.502 & 16.5229 & -0.0209375 & -0.0319792 \tabularnewline
32 & 16.49 & 16.531 & 16.5483 & -0.0173264 & -0.0410069 \tabularnewline
33 & 16.54 & 16.5691 & 16.5792 & -0.0101042 & -0.0290625 \tabularnewline
34 & 16.62 & 16.6091 & 16.6192 & -0.0101042 & 0.0109375 \tabularnewline
35 & 16.69 & 16.6813 & 16.6604 & 0.0208681 & 0.00871528 \tabularnewline
36 & 16.72 & 16.7286 & 16.6992 & 0.0294097 & -0.00857639 \tabularnewline
37 & 16.72 & 16.7629 & 16.7375 & 0.0253819 & -0.0428819 \tabularnewline
38 & 16.71 & 16.7898 & 16.775 & 0.0147569 & -0.0797569 \tabularnewline
39 & 16.89 & 16.8264 & 16.8104 & 0.0159375 & 0.0636458 \tabularnewline
40 & 16.93 & 16.8386 & 16.8404 & -0.00177083 & 0.0913542 \tabularnewline
41 & 16.91 & 16.8409 & 16.8642 & -0.0232986 & 0.0691319 \tabularnewline
42 & 16.93 & 16.8618 & 16.8846 & -0.0228125 & 0.0682292 \tabularnewline
43 & 16.93 & 16.8828 & 16.9037 & -0.0209375 & 0.0471875 \tabularnewline
44 & 16.93 & 16.906 & 16.9233 & -0.0173264 & 0.0239931 \tabularnewline
45 & 16.95 & 16.9245 & 16.9346 & -0.0101042 & 0.0255208 \tabularnewline
46 & 16.93 & 16.9249 & 16.935 & -0.0101042 & 0.00510417 \tabularnewline
47 & 16.95 & 16.9546 & 16.9337 & 0.0208681 & -0.00461806 \tabularnewline
48 & 16.95 & 16.964 & 16.9346 & 0.0294097 & -0.0139931 \tabularnewline
49 & 16.95 & 16.9625 & 16.9371 & 0.0253819 & -0.0124653 \tabularnewline
50 & 16.95 & 16.9539 & 16.9392 & 0.0147569 & -0.00392361 \tabularnewline
51 & 16.92 & 16.9547 & 16.9388 & 0.0159375 & -0.0346875 \tabularnewline
52 & 16.91 & 16.9332 & 16.935 & -0.00177083 & -0.0232292 \tabularnewline
53 & 16.9 & 16.9059 & 16.9292 & -0.0232986 & -0.00586806 \tabularnewline
54 & 16.96 & 16.9001 & 16.9229 & -0.0228125 & 0.0598958 \tabularnewline
55 & 16.96 & 16.8961 & 16.9171 & -0.0209375 & 0.0638542 \tabularnewline
56 & 16.95 & 16.8931 & 16.9104 & -0.0173264 & 0.0569097 \tabularnewline
57 & 16.92 & 16.8949 & 16.905 & -0.0101042 & 0.0251042 \tabularnewline
58 & 16.87 & 16.892 & 16.9021 & -0.0101042 & -0.0219792 \tabularnewline
59 & 16.87 & 16.9209 & 16.9 & 0.0208681 & -0.0508681 \tabularnewline
60 & 16.88 & 16.9252 & 16.8958 & 0.0294097 & -0.0452431 \tabularnewline
61 & 16.88 & 16.9145 & 16.8892 & 0.0253819 & -0.0345486 \tabularnewline
62 & 16.86 & 16.8973 & 16.8825 & 0.0147569 & -0.0372569 \tabularnewline
63 & 16.88 & 16.8951 & 16.8792 & 0.0159375 & -0.0151042 \tabularnewline
64 & 16.88 & 16.8803 & 16.8821 & -0.00177083 & -0.0003125 \tabularnewline
65 & 16.88 & 16.8684 & 16.8917 & -0.0232986 & 0.0116319 \tabularnewline
66 & 16.88 & 16.8814 & 16.9042 & -0.0228125 & -0.00135417 \tabularnewline
67 & 16.88 & 16.8949 & 16.9158 & -0.0209375 & -0.0148958 \tabularnewline
68 & 16.87 & 16.911 & 16.9283 & -0.0173264 & -0.0410069 \tabularnewline
69 & 16.92 & 16.9295 & 16.9396 & -0.0101042 & -0.00947917 \tabularnewline
70 & 16.94 & 16.9403 & 16.9504 & -0.0101042 & -0.0003125 \tabularnewline
71 & 17.03 & 16.9817 & 16.9608 & 0.0208681 & 0.0482986 \tabularnewline
72 & 17.02 & 16.9948 & 16.9654 & 0.0294097 & 0.0251736 \tabularnewline
73 & 17.02 & 16.9916 & 16.9662 & 0.0253819 & 0.0283681 \tabularnewline
74 & 17.02 & 16.9827 & 16.9679 & 0.0147569 & 0.0373264 \tabularnewline
75 & 16.99 & 16.9839 & 16.9679 & 0.0159375 & 0.00614583 \tabularnewline
76 & 17.03 & 16.9657 & 16.9675 & -0.00177083 & 0.0642708 \tabularnewline
77 & 16.98 & 16.9425 & 16.9658 & -0.0232986 & 0.0374653 \tabularnewline
78 & 16.89 & 16.9384 & 16.9612 & -0.0228125 & -0.0484375 \tabularnewline
79 & 16.89 & NA & NA & -0.0209375 & NA \tabularnewline
80 & 16.9 & NA & NA & -0.0173264 & NA \tabularnewline
81 & 16.89 & NA & NA & -0.0101042 & NA \tabularnewline
82 & 16.96 & NA & NA & -0.0101042 & NA \tabularnewline
83 & 16.97 & NA & NA & 0.0208681 & NA \tabularnewline
84 & 16.97 & NA & NA & 0.0294097 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232247&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]16.68[/C][C]NA[/C][C]NA[/C][C]0.0253819[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]16.68[/C][C]NA[/C][C]NA[/C][C]0.0147569[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]16.69[/C][C]NA[/C][C]NA[/C][C]0.0159375[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]16.61[/C][C]NA[/C][C]NA[/C][C]-0.00177083[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]16.58[/C][C]NA[/C][C]NA[/C][C]-0.0232986[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]16.6[/C][C]NA[/C][C]NA[/C][C]-0.0228125[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]16.6[/C][C]16.6091[/C][C]16.63[/C][C]-0.0209375[/C][C]-0.0090625[/C][/ROW]
[ROW][C]8[/C][C]16.62[/C][C]16.6106[/C][C]16.6279[/C][C]-0.0173264[/C][C]0.00940972[/C][/ROW]
[ROW][C]9[/C][C]16.62[/C][C]16.6086[/C][C]16.6188[/C][C]-0.0101042[/C][C]0.0113542[/C][/ROW]
[ROW][C]10[/C][C]16.6[/C][C]16.5916[/C][C]16.6017[/C][C]-0.0101042[/C][C]0.0084375[/C][/ROW]
[ROW][C]11[/C][C]16.63[/C][C]16.6034[/C][C]16.5825[/C][C]0.0208681[/C][C]0.0266319[/C][/ROW]
[ROW][C]12[/C][C]16.66[/C][C]16.5915[/C][C]16.5621[/C][C]0.0294097[/C][C]0.0685069[/C][/ROW]
[ROW][C]13[/C][C]16.66[/C][C]16.5666[/C][C]16.5412[/C][C]0.0253819[/C][C]0.0933681[/C][/ROW]
[ROW][C]14[/C][C]16.65[/C][C]16.5356[/C][C]16.5208[/C][C]0.0147569[/C][C]0.11441[/C][/ROW]
[ROW][C]15[/C][C]16.5[/C][C]16.5159[/C][C]16.5[/C][C]0.0159375[/C][C]-0.0159375[/C][/ROW]
[ROW][C]16[/C][C]16.39[/C][C]16.4782[/C][C]16.48[/C][C]-0.00177083[/C][C]-0.0882292[/C][/ROW]
[ROW][C]17[/C][C]16.34[/C][C]16.4375[/C][C]16.4608[/C][C]-0.0232986[/C][C]-0.0975347[/C][/ROW]
[ROW][C]18[/C][C]16.35[/C][C]16.4176[/C][C]16.4404[/C][C]-0.0228125[/C][C]-0.0676042[/C][/ROW]
[ROW][C]19[/C][C]16.35[/C][C]16.3986[/C][C]16.4196[/C][C]-0.0209375[/C][C]-0.0486458[/C][/ROW]
[ROW][C]20[/C][C]16.38[/C][C]16.3818[/C][C]16.3992[/C][C]-0.0173264[/C][C]-0.00184028[/C][/ROW]
[ROW][C]21[/C][C]16.36[/C][C]16.377[/C][C]16.3871[/C][C]-0.0101042[/C][C]-0.0169792[/C][/ROW]
[ROW][C]22[/C][C]16.38[/C][C]16.3757[/C][C]16.3858[/C][C]-0.0101042[/C][C]0.00427083[/C][/ROW]
[ROW][C]23[/C][C]16.39[/C][C]16.4117[/C][C]16.3908[/C][C]0.0208681[/C][C]-0.0217014[/C][/ROW]
[ROW][C]24[/C][C]16.41[/C][C]16.4294[/C][C]16.4[/C][C]0.0294097[/C][C]-0.0194097[/C][/ROW]
[ROW][C]25[/C][C]16.41[/C][C]16.4354[/C][C]16.41[/C][C]0.0253819[/C][C]-0.0253819[/C][/ROW]
[ROW][C]26[/C][C]16.41[/C][C]16.4343[/C][C]16.4196[/C][C]0.0147569[/C][C]-0.0243403[/C][/ROW]
[ROW][C]27[/C][C]16.45[/C][C]16.4476[/C][C]16.4317[/C][C]0.0159375[/C][C]0.00239583[/C][/ROW]
[ROW][C]28[/C][C]16.41[/C][C]16.4474[/C][C]16.4492[/C][C]-0.00177083[/C][C]-0.0373958[/C][/ROW]
[ROW][C]29[/C][C]16.44[/C][C]16.4484[/C][C]16.4717[/C][C]-0.0232986[/C][C]-0.00836806[/C][/ROW]
[ROW][C]30[/C][C]16.47[/C][C]16.4743[/C][C]16.4971[/C][C]-0.0228125[/C][C]-0.00427083[/C][/ROW]
[ROW][C]31[/C][C]16.47[/C][C]16.502[/C][C]16.5229[/C][C]-0.0209375[/C][C]-0.0319792[/C][/ROW]
[ROW][C]32[/C][C]16.49[/C][C]16.531[/C][C]16.5483[/C][C]-0.0173264[/C][C]-0.0410069[/C][/ROW]
[ROW][C]33[/C][C]16.54[/C][C]16.5691[/C][C]16.5792[/C][C]-0.0101042[/C][C]-0.0290625[/C][/ROW]
[ROW][C]34[/C][C]16.62[/C][C]16.6091[/C][C]16.6192[/C][C]-0.0101042[/C][C]0.0109375[/C][/ROW]
[ROW][C]35[/C][C]16.69[/C][C]16.6813[/C][C]16.6604[/C][C]0.0208681[/C][C]0.00871528[/C][/ROW]
[ROW][C]36[/C][C]16.72[/C][C]16.7286[/C][C]16.6992[/C][C]0.0294097[/C][C]-0.00857639[/C][/ROW]
[ROW][C]37[/C][C]16.72[/C][C]16.7629[/C][C]16.7375[/C][C]0.0253819[/C][C]-0.0428819[/C][/ROW]
[ROW][C]38[/C][C]16.71[/C][C]16.7898[/C][C]16.775[/C][C]0.0147569[/C][C]-0.0797569[/C][/ROW]
[ROW][C]39[/C][C]16.89[/C][C]16.8264[/C][C]16.8104[/C][C]0.0159375[/C][C]0.0636458[/C][/ROW]
[ROW][C]40[/C][C]16.93[/C][C]16.8386[/C][C]16.8404[/C][C]-0.00177083[/C][C]0.0913542[/C][/ROW]
[ROW][C]41[/C][C]16.91[/C][C]16.8409[/C][C]16.8642[/C][C]-0.0232986[/C][C]0.0691319[/C][/ROW]
[ROW][C]42[/C][C]16.93[/C][C]16.8618[/C][C]16.8846[/C][C]-0.0228125[/C][C]0.0682292[/C][/ROW]
[ROW][C]43[/C][C]16.93[/C][C]16.8828[/C][C]16.9037[/C][C]-0.0209375[/C][C]0.0471875[/C][/ROW]
[ROW][C]44[/C][C]16.93[/C][C]16.906[/C][C]16.9233[/C][C]-0.0173264[/C][C]0.0239931[/C][/ROW]
[ROW][C]45[/C][C]16.95[/C][C]16.9245[/C][C]16.9346[/C][C]-0.0101042[/C][C]0.0255208[/C][/ROW]
[ROW][C]46[/C][C]16.93[/C][C]16.9249[/C][C]16.935[/C][C]-0.0101042[/C][C]0.00510417[/C][/ROW]
[ROW][C]47[/C][C]16.95[/C][C]16.9546[/C][C]16.9337[/C][C]0.0208681[/C][C]-0.00461806[/C][/ROW]
[ROW][C]48[/C][C]16.95[/C][C]16.964[/C][C]16.9346[/C][C]0.0294097[/C][C]-0.0139931[/C][/ROW]
[ROW][C]49[/C][C]16.95[/C][C]16.9625[/C][C]16.9371[/C][C]0.0253819[/C][C]-0.0124653[/C][/ROW]
[ROW][C]50[/C][C]16.95[/C][C]16.9539[/C][C]16.9392[/C][C]0.0147569[/C][C]-0.00392361[/C][/ROW]
[ROW][C]51[/C][C]16.92[/C][C]16.9547[/C][C]16.9388[/C][C]0.0159375[/C][C]-0.0346875[/C][/ROW]
[ROW][C]52[/C][C]16.91[/C][C]16.9332[/C][C]16.935[/C][C]-0.00177083[/C][C]-0.0232292[/C][/ROW]
[ROW][C]53[/C][C]16.9[/C][C]16.9059[/C][C]16.9292[/C][C]-0.0232986[/C][C]-0.00586806[/C][/ROW]
[ROW][C]54[/C][C]16.96[/C][C]16.9001[/C][C]16.9229[/C][C]-0.0228125[/C][C]0.0598958[/C][/ROW]
[ROW][C]55[/C][C]16.96[/C][C]16.8961[/C][C]16.9171[/C][C]-0.0209375[/C][C]0.0638542[/C][/ROW]
[ROW][C]56[/C][C]16.95[/C][C]16.8931[/C][C]16.9104[/C][C]-0.0173264[/C][C]0.0569097[/C][/ROW]
[ROW][C]57[/C][C]16.92[/C][C]16.8949[/C][C]16.905[/C][C]-0.0101042[/C][C]0.0251042[/C][/ROW]
[ROW][C]58[/C][C]16.87[/C][C]16.892[/C][C]16.9021[/C][C]-0.0101042[/C][C]-0.0219792[/C][/ROW]
[ROW][C]59[/C][C]16.87[/C][C]16.9209[/C][C]16.9[/C][C]0.0208681[/C][C]-0.0508681[/C][/ROW]
[ROW][C]60[/C][C]16.88[/C][C]16.9252[/C][C]16.8958[/C][C]0.0294097[/C][C]-0.0452431[/C][/ROW]
[ROW][C]61[/C][C]16.88[/C][C]16.9145[/C][C]16.8892[/C][C]0.0253819[/C][C]-0.0345486[/C][/ROW]
[ROW][C]62[/C][C]16.86[/C][C]16.8973[/C][C]16.8825[/C][C]0.0147569[/C][C]-0.0372569[/C][/ROW]
[ROW][C]63[/C][C]16.88[/C][C]16.8951[/C][C]16.8792[/C][C]0.0159375[/C][C]-0.0151042[/C][/ROW]
[ROW][C]64[/C][C]16.88[/C][C]16.8803[/C][C]16.8821[/C][C]-0.00177083[/C][C]-0.0003125[/C][/ROW]
[ROW][C]65[/C][C]16.88[/C][C]16.8684[/C][C]16.8917[/C][C]-0.0232986[/C][C]0.0116319[/C][/ROW]
[ROW][C]66[/C][C]16.88[/C][C]16.8814[/C][C]16.9042[/C][C]-0.0228125[/C][C]-0.00135417[/C][/ROW]
[ROW][C]67[/C][C]16.88[/C][C]16.8949[/C][C]16.9158[/C][C]-0.0209375[/C][C]-0.0148958[/C][/ROW]
[ROW][C]68[/C][C]16.87[/C][C]16.911[/C][C]16.9283[/C][C]-0.0173264[/C][C]-0.0410069[/C][/ROW]
[ROW][C]69[/C][C]16.92[/C][C]16.9295[/C][C]16.9396[/C][C]-0.0101042[/C][C]-0.00947917[/C][/ROW]
[ROW][C]70[/C][C]16.94[/C][C]16.9403[/C][C]16.9504[/C][C]-0.0101042[/C][C]-0.0003125[/C][/ROW]
[ROW][C]71[/C][C]17.03[/C][C]16.9817[/C][C]16.9608[/C][C]0.0208681[/C][C]0.0482986[/C][/ROW]
[ROW][C]72[/C][C]17.02[/C][C]16.9948[/C][C]16.9654[/C][C]0.0294097[/C][C]0.0251736[/C][/ROW]
[ROW][C]73[/C][C]17.02[/C][C]16.9916[/C][C]16.9662[/C][C]0.0253819[/C][C]0.0283681[/C][/ROW]
[ROW][C]74[/C][C]17.02[/C][C]16.9827[/C][C]16.9679[/C][C]0.0147569[/C][C]0.0373264[/C][/ROW]
[ROW][C]75[/C][C]16.99[/C][C]16.9839[/C][C]16.9679[/C][C]0.0159375[/C][C]0.00614583[/C][/ROW]
[ROW][C]76[/C][C]17.03[/C][C]16.9657[/C][C]16.9675[/C][C]-0.00177083[/C][C]0.0642708[/C][/ROW]
[ROW][C]77[/C][C]16.98[/C][C]16.9425[/C][C]16.9658[/C][C]-0.0232986[/C][C]0.0374653[/C][/ROW]
[ROW][C]78[/C][C]16.89[/C][C]16.9384[/C][C]16.9612[/C][C]-0.0228125[/C][C]-0.0484375[/C][/ROW]
[ROW][C]79[/C][C]16.89[/C][C]NA[/C][C]NA[/C][C]-0.0209375[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]16.9[/C][C]NA[/C][C]NA[/C][C]-0.0173264[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]16.89[/C][C]NA[/C][C]NA[/C][C]-0.0101042[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]16.96[/C][C]NA[/C][C]NA[/C][C]-0.0101042[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]16.97[/C][C]NA[/C][C]NA[/C][C]0.0208681[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]16.97[/C][C]NA[/C][C]NA[/C][C]0.0294097[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232247&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232247&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
tObservationsFitTrendSeasonalRandom
116.68NANA0.0253819NA
216.68NANA0.0147569NA
316.69NANA0.0159375NA
416.61NANA-0.00177083NA
516.58NANA-0.0232986NA
616.6NANA-0.0228125NA
716.616.609116.63-0.0209375-0.0090625
816.6216.610616.6279-0.01732640.00940972
916.6216.608616.6188-0.01010420.0113542
1016.616.591616.6017-0.01010420.0084375
1116.6316.603416.58250.02086810.0266319
1216.6616.591516.56210.02940970.0685069
1316.6616.566616.54120.02538190.0933681
1416.6516.535616.52080.01475690.11441
1516.516.515916.50.0159375-0.0159375
1616.3916.478216.48-0.00177083-0.0882292
1716.3416.437516.4608-0.0232986-0.0975347
1816.3516.417616.4404-0.0228125-0.0676042
1916.3516.398616.4196-0.0209375-0.0486458
2016.3816.381816.3992-0.0173264-0.00184028
2116.3616.37716.3871-0.0101042-0.0169792
2216.3816.375716.3858-0.01010420.00427083
2316.3916.411716.39080.0208681-0.0217014
2416.4116.429416.40.0294097-0.0194097
2516.4116.435416.410.0253819-0.0253819
2616.4116.434316.41960.0147569-0.0243403
2716.4516.447616.43170.01593750.00239583
2816.4116.447416.4492-0.00177083-0.0373958
2916.4416.448416.4717-0.0232986-0.00836806
3016.4716.474316.4971-0.0228125-0.00427083
3116.4716.50216.5229-0.0209375-0.0319792
3216.4916.53116.5483-0.0173264-0.0410069
3316.5416.569116.5792-0.0101042-0.0290625
3416.6216.609116.6192-0.01010420.0109375
3516.6916.681316.66040.02086810.00871528
3616.7216.728616.69920.0294097-0.00857639
3716.7216.762916.73750.0253819-0.0428819
3816.7116.789816.7750.0147569-0.0797569
3916.8916.826416.81040.01593750.0636458
4016.9316.838616.8404-0.001770830.0913542
4116.9116.840916.8642-0.02329860.0691319
4216.9316.861816.8846-0.02281250.0682292
4316.9316.882816.9037-0.02093750.0471875
4416.9316.90616.9233-0.01732640.0239931
4516.9516.924516.9346-0.01010420.0255208
4616.9316.924916.935-0.01010420.00510417
4716.9516.954616.93370.0208681-0.00461806
4816.9516.96416.93460.0294097-0.0139931
4916.9516.962516.93710.0253819-0.0124653
5016.9516.953916.93920.0147569-0.00392361
5116.9216.954716.93880.0159375-0.0346875
5216.9116.933216.935-0.00177083-0.0232292
5316.916.905916.9292-0.0232986-0.00586806
5416.9616.900116.9229-0.02281250.0598958
5516.9616.896116.9171-0.02093750.0638542
5616.9516.893116.9104-0.01732640.0569097
5716.9216.894916.905-0.01010420.0251042
5816.8716.89216.9021-0.0101042-0.0219792
5916.8716.920916.90.0208681-0.0508681
6016.8816.925216.89580.0294097-0.0452431
6116.8816.914516.88920.0253819-0.0345486
6216.8616.897316.88250.0147569-0.0372569
6316.8816.895116.87920.0159375-0.0151042
6416.8816.880316.8821-0.00177083-0.0003125
6516.8816.868416.8917-0.02329860.0116319
6616.8816.881416.9042-0.0228125-0.00135417
6716.8816.894916.9158-0.0209375-0.0148958
6816.8716.91116.9283-0.0173264-0.0410069
6916.9216.929516.9396-0.0101042-0.00947917
7016.9416.940316.9504-0.0101042-0.0003125
7117.0316.981716.96080.02086810.0482986
7217.0216.994816.96540.02940970.0251736
7317.0216.991616.96620.02538190.0283681
7417.0216.982716.96790.01475690.0373264
7516.9916.983916.96790.01593750.00614583
7617.0316.965716.9675-0.001770830.0642708
7716.9816.942516.9658-0.02329860.0374653
7816.8916.938416.9612-0.0228125-0.0484375
7916.89NANA-0.0209375NA
8016.9NANA-0.0173264NA
8116.89NANA-0.0101042NA
8216.96NANA-0.0101042NA
8316.97NANA0.0208681NA
8416.97NANA0.0294097NA



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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')