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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 09 Dec 2013 08:01:04 -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/09/t1386594109f1oqkifk3dtcllt.htm/, Retrieved Fri, 29 Mar 2024 06:31:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231639, Retrieved Fri, 29 Mar 2024 06:31:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact75
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-09 13:01:04] [dedf484cd0157d286b516b811e22f230] [Current]
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Dataseries X:
6,11
6,13
6,15
6,15
6,16
6,18
6,21
6,22
6,23
6,26
6,28
6,28
6,29
6,32
6,36
6,37
6,38
6,38
6,4
6,41
6,42
6,43
6,44
6,47
6,47
6,48
6,51
6,54
6,56
6,57
6,6
6,62
6,65
6,71
6,76
6,78
6,8
6,83
6,86
6,86
6,87
6,88
6,9
6,92
6,93
6,94
6,96
6,98
6,99
7,01
7,06
7,07
7,08
7,08
7,1
7,11
7,22
7,24
7,25
7,26
7,27
7,3
7,32
7,34
7,35
7,36
7,39
7,41
7,43
7,46
7,47
7,5
7,51
7,52
7,58
7,59
7,63
7,64
7,64
7,66
7,67
7,68
7,69
7,7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 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 & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231639&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]9 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=231639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231639&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 time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
16.11NANA0.999089NA
26.13NANA0.999378NA
36.15NANA1.00201NA
46.15NANA1.00108NA
56.16NANA1.0006NA
66.18NANA0.998722NA
76.216.196936.204170.9988331.00211
86.226.208296.219580.9981841.00189
96.236.235246.236250.9998380.999159
106.266.259486.254171.000851.00008
116.286.277926.27251.000861.00033
126.286.293456.291.000550.997863
136.296.30056.306250.9990890.998333
146.326.318156.322080.9993781.00029
156.366.350656.337921.002011.00147
166.376.359786.352921.001081.00161
176.386.370516.366671.00061.00149
186.386.373096.381250.9987221.00108
196.46.38926.396670.9988331.00169
206.416.399196.410830.9981841.00169
216.426.422716.423750.9998380.999578
226.436.442566.437081.000850.998051
236.446.457246.451671.000860.997331
246.476.470636.467081.000550.999902
256.476.477426.483330.9990890.998854
266.486.496376.500420.9993780.99748
276.516.531856.518751.002010.996655
286.546.547076.541.001080.998921
296.566.568966.5651.00060.998636
306.576.582826.591250.9987220.998052
316.66.61026.617920.9988330.998458
326.626.634186.646250.9981840.997862
336.656.674346.675420.9998380.996353
346.716.709036.703331.000851.00014
356.766.735396.729581.000861.00365
366.786.759126.755421.000551.00309
376.86.774656.780830.9990891.00374
386.836.80166.805830.9993781.00418
396.866.843736.831.002011.00238
406.866.858656.851251.001081.0002
416.876.873316.869171.00060.999518
426.886.877036.885830.9987221.00043
436.96.894036.902080.9988331.00087
446.926.904946.91750.9981841.00218
456.936.932216.933330.9998380.999681
466.946.956336.950421.000850.997653
476.966.973936.967921.000860.998002
486.986.988836.9851.000550.998736
496.996.995297.001670.9990890.999244
507.017.013557.017920.9993780.999494
517.067.052067.037921.002011.00113
527.077.070137.06251.001080.999982
537.087.091367.087081.00060.998398
547.087.101747.110830.9987220.996938
557.17.125847.134170.9988330.996373
567.117.144927.157920.9981840.995113
577.227.179677.180830.9998381.00562
587.247.209047.202921.000851.00429
597.257.231657.225421.000861.00254
607.267.252317.248331.000551.00106
617.277.265467.272080.9990891.00063
627.37.292137.296670.9993781.00108
637.327.332627.317921.002010.998279
647.347.343767.335831.001080.999488
657.357.358617.354171.00060.99883
667.367.363917.373330.9987220.999469
677.397.384717.393330.9988331.00072
687.417.399047.41250.9981841.00148
697.437.43137.43250.9998380.999825
707.467.460097.453751.000850.999988
717.477.482297.475831.000860.998358
727.57.503287.499171.000550.999563
737.517.51447.521250.9990890.999415
747.527.537397.542080.9993780.997692
757.587.57777.56251.002011.0003
767.597.589867.581671.001081.00002
777.637.604597.61.00061.00334
787.647.607767.61750.9987221.00424
797.64NANA0.998833NA
807.66NANA0.998184NA
817.67NANA0.999838NA
827.68NANA1.00085NA
837.69NANA1.00086NA
847.7NANA1.00055NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 6.11 & NA & NA & 0.999089 & NA \tabularnewline
2 & 6.13 & NA & NA & 0.999378 & NA \tabularnewline
3 & 6.15 & NA & NA & 1.00201 & NA \tabularnewline
4 & 6.15 & NA & NA & 1.00108 & NA \tabularnewline
5 & 6.16 & NA & NA & 1.0006 & NA \tabularnewline
6 & 6.18 & NA & NA & 0.998722 & NA \tabularnewline
7 & 6.21 & 6.19693 & 6.20417 & 0.998833 & 1.00211 \tabularnewline
8 & 6.22 & 6.20829 & 6.21958 & 0.998184 & 1.00189 \tabularnewline
9 & 6.23 & 6.23524 & 6.23625 & 0.999838 & 0.999159 \tabularnewline
10 & 6.26 & 6.25948 & 6.25417 & 1.00085 & 1.00008 \tabularnewline
11 & 6.28 & 6.27792 & 6.2725 & 1.00086 & 1.00033 \tabularnewline
12 & 6.28 & 6.29345 & 6.29 & 1.00055 & 0.997863 \tabularnewline
13 & 6.29 & 6.3005 & 6.30625 & 0.999089 & 0.998333 \tabularnewline
14 & 6.32 & 6.31815 & 6.32208 & 0.999378 & 1.00029 \tabularnewline
15 & 6.36 & 6.35065 & 6.33792 & 1.00201 & 1.00147 \tabularnewline
16 & 6.37 & 6.35978 & 6.35292 & 1.00108 & 1.00161 \tabularnewline
17 & 6.38 & 6.37051 & 6.36667 & 1.0006 & 1.00149 \tabularnewline
18 & 6.38 & 6.37309 & 6.38125 & 0.998722 & 1.00108 \tabularnewline
19 & 6.4 & 6.3892 & 6.39667 & 0.998833 & 1.00169 \tabularnewline
20 & 6.41 & 6.39919 & 6.41083 & 0.998184 & 1.00169 \tabularnewline
21 & 6.42 & 6.42271 & 6.42375 & 0.999838 & 0.999578 \tabularnewline
22 & 6.43 & 6.44256 & 6.43708 & 1.00085 & 0.998051 \tabularnewline
23 & 6.44 & 6.45724 & 6.45167 & 1.00086 & 0.997331 \tabularnewline
24 & 6.47 & 6.47063 & 6.46708 & 1.00055 & 0.999902 \tabularnewline
25 & 6.47 & 6.47742 & 6.48333 & 0.999089 & 0.998854 \tabularnewline
26 & 6.48 & 6.49637 & 6.50042 & 0.999378 & 0.99748 \tabularnewline
27 & 6.51 & 6.53185 & 6.51875 & 1.00201 & 0.996655 \tabularnewline
28 & 6.54 & 6.54707 & 6.54 & 1.00108 & 0.998921 \tabularnewline
29 & 6.56 & 6.56896 & 6.565 & 1.0006 & 0.998636 \tabularnewline
30 & 6.57 & 6.58282 & 6.59125 & 0.998722 & 0.998052 \tabularnewline
31 & 6.6 & 6.6102 & 6.61792 & 0.998833 & 0.998458 \tabularnewline
32 & 6.62 & 6.63418 & 6.64625 & 0.998184 & 0.997862 \tabularnewline
33 & 6.65 & 6.67434 & 6.67542 & 0.999838 & 0.996353 \tabularnewline
34 & 6.71 & 6.70903 & 6.70333 & 1.00085 & 1.00014 \tabularnewline
35 & 6.76 & 6.73539 & 6.72958 & 1.00086 & 1.00365 \tabularnewline
36 & 6.78 & 6.75912 & 6.75542 & 1.00055 & 1.00309 \tabularnewline
37 & 6.8 & 6.77465 & 6.78083 & 0.999089 & 1.00374 \tabularnewline
38 & 6.83 & 6.8016 & 6.80583 & 0.999378 & 1.00418 \tabularnewline
39 & 6.86 & 6.84373 & 6.83 & 1.00201 & 1.00238 \tabularnewline
40 & 6.86 & 6.85865 & 6.85125 & 1.00108 & 1.0002 \tabularnewline
41 & 6.87 & 6.87331 & 6.86917 & 1.0006 & 0.999518 \tabularnewline
42 & 6.88 & 6.87703 & 6.88583 & 0.998722 & 1.00043 \tabularnewline
43 & 6.9 & 6.89403 & 6.90208 & 0.998833 & 1.00087 \tabularnewline
44 & 6.92 & 6.90494 & 6.9175 & 0.998184 & 1.00218 \tabularnewline
45 & 6.93 & 6.93221 & 6.93333 & 0.999838 & 0.999681 \tabularnewline
46 & 6.94 & 6.95633 & 6.95042 & 1.00085 & 0.997653 \tabularnewline
47 & 6.96 & 6.97393 & 6.96792 & 1.00086 & 0.998002 \tabularnewline
48 & 6.98 & 6.98883 & 6.985 & 1.00055 & 0.998736 \tabularnewline
49 & 6.99 & 6.99529 & 7.00167 & 0.999089 & 0.999244 \tabularnewline
50 & 7.01 & 7.01355 & 7.01792 & 0.999378 & 0.999494 \tabularnewline
51 & 7.06 & 7.05206 & 7.03792 & 1.00201 & 1.00113 \tabularnewline
52 & 7.07 & 7.07013 & 7.0625 & 1.00108 & 0.999982 \tabularnewline
53 & 7.08 & 7.09136 & 7.08708 & 1.0006 & 0.998398 \tabularnewline
54 & 7.08 & 7.10174 & 7.11083 & 0.998722 & 0.996938 \tabularnewline
55 & 7.1 & 7.12584 & 7.13417 & 0.998833 & 0.996373 \tabularnewline
56 & 7.11 & 7.14492 & 7.15792 & 0.998184 & 0.995113 \tabularnewline
57 & 7.22 & 7.17967 & 7.18083 & 0.999838 & 1.00562 \tabularnewline
58 & 7.24 & 7.20904 & 7.20292 & 1.00085 & 1.00429 \tabularnewline
59 & 7.25 & 7.23165 & 7.22542 & 1.00086 & 1.00254 \tabularnewline
60 & 7.26 & 7.25231 & 7.24833 & 1.00055 & 1.00106 \tabularnewline
61 & 7.27 & 7.26546 & 7.27208 & 0.999089 & 1.00063 \tabularnewline
62 & 7.3 & 7.29213 & 7.29667 & 0.999378 & 1.00108 \tabularnewline
63 & 7.32 & 7.33262 & 7.31792 & 1.00201 & 0.998279 \tabularnewline
64 & 7.34 & 7.34376 & 7.33583 & 1.00108 & 0.999488 \tabularnewline
65 & 7.35 & 7.35861 & 7.35417 & 1.0006 & 0.99883 \tabularnewline
66 & 7.36 & 7.36391 & 7.37333 & 0.998722 & 0.999469 \tabularnewline
67 & 7.39 & 7.38471 & 7.39333 & 0.998833 & 1.00072 \tabularnewline
68 & 7.41 & 7.39904 & 7.4125 & 0.998184 & 1.00148 \tabularnewline
69 & 7.43 & 7.4313 & 7.4325 & 0.999838 & 0.999825 \tabularnewline
70 & 7.46 & 7.46009 & 7.45375 & 1.00085 & 0.999988 \tabularnewline
71 & 7.47 & 7.48229 & 7.47583 & 1.00086 & 0.998358 \tabularnewline
72 & 7.5 & 7.50328 & 7.49917 & 1.00055 & 0.999563 \tabularnewline
73 & 7.51 & 7.5144 & 7.52125 & 0.999089 & 0.999415 \tabularnewline
74 & 7.52 & 7.53739 & 7.54208 & 0.999378 & 0.997692 \tabularnewline
75 & 7.58 & 7.5777 & 7.5625 & 1.00201 & 1.0003 \tabularnewline
76 & 7.59 & 7.58986 & 7.58167 & 1.00108 & 1.00002 \tabularnewline
77 & 7.63 & 7.60459 & 7.6 & 1.0006 & 1.00334 \tabularnewline
78 & 7.64 & 7.60776 & 7.6175 & 0.998722 & 1.00424 \tabularnewline
79 & 7.64 & NA & NA & 0.998833 & NA \tabularnewline
80 & 7.66 & NA & NA & 0.998184 & NA \tabularnewline
81 & 7.67 & NA & NA & 0.999838 & NA \tabularnewline
82 & 7.68 & NA & NA & 1.00085 & NA \tabularnewline
83 & 7.69 & NA & NA & 1.00086 & NA \tabularnewline
84 & 7.7 & NA & NA & 1.00055 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231639&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]6.11[/C][C]NA[/C][C]NA[/C][C]0.999089[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]6.13[/C][C]NA[/C][C]NA[/C][C]0.999378[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]6.15[/C][C]NA[/C][C]NA[/C][C]1.00201[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]6.15[/C][C]NA[/C][C]NA[/C][C]1.00108[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]6.16[/C][C]NA[/C][C]NA[/C][C]1.0006[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]6.18[/C][C]NA[/C][C]NA[/C][C]0.998722[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]6.21[/C][C]6.19693[/C][C]6.20417[/C][C]0.998833[/C][C]1.00211[/C][/ROW]
[ROW][C]8[/C][C]6.22[/C][C]6.20829[/C][C]6.21958[/C][C]0.998184[/C][C]1.00189[/C][/ROW]
[ROW][C]9[/C][C]6.23[/C][C]6.23524[/C][C]6.23625[/C][C]0.999838[/C][C]0.999159[/C][/ROW]
[ROW][C]10[/C][C]6.26[/C][C]6.25948[/C][C]6.25417[/C][C]1.00085[/C][C]1.00008[/C][/ROW]
[ROW][C]11[/C][C]6.28[/C][C]6.27792[/C][C]6.2725[/C][C]1.00086[/C][C]1.00033[/C][/ROW]
[ROW][C]12[/C][C]6.28[/C][C]6.29345[/C][C]6.29[/C][C]1.00055[/C][C]0.997863[/C][/ROW]
[ROW][C]13[/C][C]6.29[/C][C]6.3005[/C][C]6.30625[/C][C]0.999089[/C][C]0.998333[/C][/ROW]
[ROW][C]14[/C][C]6.32[/C][C]6.31815[/C][C]6.32208[/C][C]0.999378[/C][C]1.00029[/C][/ROW]
[ROW][C]15[/C][C]6.36[/C][C]6.35065[/C][C]6.33792[/C][C]1.00201[/C][C]1.00147[/C][/ROW]
[ROW][C]16[/C][C]6.37[/C][C]6.35978[/C][C]6.35292[/C][C]1.00108[/C][C]1.00161[/C][/ROW]
[ROW][C]17[/C][C]6.38[/C][C]6.37051[/C][C]6.36667[/C][C]1.0006[/C][C]1.00149[/C][/ROW]
[ROW][C]18[/C][C]6.38[/C][C]6.37309[/C][C]6.38125[/C][C]0.998722[/C][C]1.00108[/C][/ROW]
[ROW][C]19[/C][C]6.4[/C][C]6.3892[/C][C]6.39667[/C][C]0.998833[/C][C]1.00169[/C][/ROW]
[ROW][C]20[/C][C]6.41[/C][C]6.39919[/C][C]6.41083[/C][C]0.998184[/C][C]1.00169[/C][/ROW]
[ROW][C]21[/C][C]6.42[/C][C]6.42271[/C][C]6.42375[/C][C]0.999838[/C][C]0.999578[/C][/ROW]
[ROW][C]22[/C][C]6.43[/C][C]6.44256[/C][C]6.43708[/C][C]1.00085[/C][C]0.998051[/C][/ROW]
[ROW][C]23[/C][C]6.44[/C][C]6.45724[/C][C]6.45167[/C][C]1.00086[/C][C]0.997331[/C][/ROW]
[ROW][C]24[/C][C]6.47[/C][C]6.47063[/C][C]6.46708[/C][C]1.00055[/C][C]0.999902[/C][/ROW]
[ROW][C]25[/C][C]6.47[/C][C]6.47742[/C][C]6.48333[/C][C]0.999089[/C][C]0.998854[/C][/ROW]
[ROW][C]26[/C][C]6.48[/C][C]6.49637[/C][C]6.50042[/C][C]0.999378[/C][C]0.99748[/C][/ROW]
[ROW][C]27[/C][C]6.51[/C][C]6.53185[/C][C]6.51875[/C][C]1.00201[/C][C]0.996655[/C][/ROW]
[ROW][C]28[/C][C]6.54[/C][C]6.54707[/C][C]6.54[/C][C]1.00108[/C][C]0.998921[/C][/ROW]
[ROW][C]29[/C][C]6.56[/C][C]6.56896[/C][C]6.565[/C][C]1.0006[/C][C]0.998636[/C][/ROW]
[ROW][C]30[/C][C]6.57[/C][C]6.58282[/C][C]6.59125[/C][C]0.998722[/C][C]0.998052[/C][/ROW]
[ROW][C]31[/C][C]6.6[/C][C]6.6102[/C][C]6.61792[/C][C]0.998833[/C][C]0.998458[/C][/ROW]
[ROW][C]32[/C][C]6.62[/C][C]6.63418[/C][C]6.64625[/C][C]0.998184[/C][C]0.997862[/C][/ROW]
[ROW][C]33[/C][C]6.65[/C][C]6.67434[/C][C]6.67542[/C][C]0.999838[/C][C]0.996353[/C][/ROW]
[ROW][C]34[/C][C]6.71[/C][C]6.70903[/C][C]6.70333[/C][C]1.00085[/C][C]1.00014[/C][/ROW]
[ROW][C]35[/C][C]6.76[/C][C]6.73539[/C][C]6.72958[/C][C]1.00086[/C][C]1.00365[/C][/ROW]
[ROW][C]36[/C][C]6.78[/C][C]6.75912[/C][C]6.75542[/C][C]1.00055[/C][C]1.00309[/C][/ROW]
[ROW][C]37[/C][C]6.8[/C][C]6.77465[/C][C]6.78083[/C][C]0.999089[/C][C]1.00374[/C][/ROW]
[ROW][C]38[/C][C]6.83[/C][C]6.8016[/C][C]6.80583[/C][C]0.999378[/C][C]1.00418[/C][/ROW]
[ROW][C]39[/C][C]6.86[/C][C]6.84373[/C][C]6.83[/C][C]1.00201[/C][C]1.00238[/C][/ROW]
[ROW][C]40[/C][C]6.86[/C][C]6.85865[/C][C]6.85125[/C][C]1.00108[/C][C]1.0002[/C][/ROW]
[ROW][C]41[/C][C]6.87[/C][C]6.87331[/C][C]6.86917[/C][C]1.0006[/C][C]0.999518[/C][/ROW]
[ROW][C]42[/C][C]6.88[/C][C]6.87703[/C][C]6.88583[/C][C]0.998722[/C][C]1.00043[/C][/ROW]
[ROW][C]43[/C][C]6.9[/C][C]6.89403[/C][C]6.90208[/C][C]0.998833[/C][C]1.00087[/C][/ROW]
[ROW][C]44[/C][C]6.92[/C][C]6.90494[/C][C]6.9175[/C][C]0.998184[/C][C]1.00218[/C][/ROW]
[ROW][C]45[/C][C]6.93[/C][C]6.93221[/C][C]6.93333[/C][C]0.999838[/C][C]0.999681[/C][/ROW]
[ROW][C]46[/C][C]6.94[/C][C]6.95633[/C][C]6.95042[/C][C]1.00085[/C][C]0.997653[/C][/ROW]
[ROW][C]47[/C][C]6.96[/C][C]6.97393[/C][C]6.96792[/C][C]1.00086[/C][C]0.998002[/C][/ROW]
[ROW][C]48[/C][C]6.98[/C][C]6.98883[/C][C]6.985[/C][C]1.00055[/C][C]0.998736[/C][/ROW]
[ROW][C]49[/C][C]6.99[/C][C]6.99529[/C][C]7.00167[/C][C]0.999089[/C][C]0.999244[/C][/ROW]
[ROW][C]50[/C][C]7.01[/C][C]7.01355[/C][C]7.01792[/C][C]0.999378[/C][C]0.999494[/C][/ROW]
[ROW][C]51[/C][C]7.06[/C][C]7.05206[/C][C]7.03792[/C][C]1.00201[/C][C]1.00113[/C][/ROW]
[ROW][C]52[/C][C]7.07[/C][C]7.07013[/C][C]7.0625[/C][C]1.00108[/C][C]0.999982[/C][/ROW]
[ROW][C]53[/C][C]7.08[/C][C]7.09136[/C][C]7.08708[/C][C]1.0006[/C][C]0.998398[/C][/ROW]
[ROW][C]54[/C][C]7.08[/C][C]7.10174[/C][C]7.11083[/C][C]0.998722[/C][C]0.996938[/C][/ROW]
[ROW][C]55[/C][C]7.1[/C][C]7.12584[/C][C]7.13417[/C][C]0.998833[/C][C]0.996373[/C][/ROW]
[ROW][C]56[/C][C]7.11[/C][C]7.14492[/C][C]7.15792[/C][C]0.998184[/C][C]0.995113[/C][/ROW]
[ROW][C]57[/C][C]7.22[/C][C]7.17967[/C][C]7.18083[/C][C]0.999838[/C][C]1.00562[/C][/ROW]
[ROW][C]58[/C][C]7.24[/C][C]7.20904[/C][C]7.20292[/C][C]1.00085[/C][C]1.00429[/C][/ROW]
[ROW][C]59[/C][C]7.25[/C][C]7.23165[/C][C]7.22542[/C][C]1.00086[/C][C]1.00254[/C][/ROW]
[ROW][C]60[/C][C]7.26[/C][C]7.25231[/C][C]7.24833[/C][C]1.00055[/C][C]1.00106[/C][/ROW]
[ROW][C]61[/C][C]7.27[/C][C]7.26546[/C][C]7.27208[/C][C]0.999089[/C][C]1.00063[/C][/ROW]
[ROW][C]62[/C][C]7.3[/C][C]7.29213[/C][C]7.29667[/C][C]0.999378[/C][C]1.00108[/C][/ROW]
[ROW][C]63[/C][C]7.32[/C][C]7.33262[/C][C]7.31792[/C][C]1.00201[/C][C]0.998279[/C][/ROW]
[ROW][C]64[/C][C]7.34[/C][C]7.34376[/C][C]7.33583[/C][C]1.00108[/C][C]0.999488[/C][/ROW]
[ROW][C]65[/C][C]7.35[/C][C]7.35861[/C][C]7.35417[/C][C]1.0006[/C][C]0.99883[/C][/ROW]
[ROW][C]66[/C][C]7.36[/C][C]7.36391[/C][C]7.37333[/C][C]0.998722[/C][C]0.999469[/C][/ROW]
[ROW][C]67[/C][C]7.39[/C][C]7.38471[/C][C]7.39333[/C][C]0.998833[/C][C]1.00072[/C][/ROW]
[ROW][C]68[/C][C]7.41[/C][C]7.39904[/C][C]7.4125[/C][C]0.998184[/C][C]1.00148[/C][/ROW]
[ROW][C]69[/C][C]7.43[/C][C]7.4313[/C][C]7.4325[/C][C]0.999838[/C][C]0.999825[/C][/ROW]
[ROW][C]70[/C][C]7.46[/C][C]7.46009[/C][C]7.45375[/C][C]1.00085[/C][C]0.999988[/C][/ROW]
[ROW][C]71[/C][C]7.47[/C][C]7.48229[/C][C]7.47583[/C][C]1.00086[/C][C]0.998358[/C][/ROW]
[ROW][C]72[/C][C]7.5[/C][C]7.50328[/C][C]7.49917[/C][C]1.00055[/C][C]0.999563[/C][/ROW]
[ROW][C]73[/C][C]7.51[/C][C]7.5144[/C][C]7.52125[/C][C]0.999089[/C][C]0.999415[/C][/ROW]
[ROW][C]74[/C][C]7.52[/C][C]7.53739[/C][C]7.54208[/C][C]0.999378[/C][C]0.997692[/C][/ROW]
[ROW][C]75[/C][C]7.58[/C][C]7.5777[/C][C]7.5625[/C][C]1.00201[/C][C]1.0003[/C][/ROW]
[ROW][C]76[/C][C]7.59[/C][C]7.58986[/C][C]7.58167[/C][C]1.00108[/C][C]1.00002[/C][/ROW]
[ROW][C]77[/C][C]7.63[/C][C]7.60459[/C][C]7.6[/C][C]1.0006[/C][C]1.00334[/C][/ROW]
[ROW][C]78[/C][C]7.64[/C][C]7.60776[/C][C]7.6175[/C][C]0.998722[/C][C]1.00424[/C][/ROW]
[ROW][C]79[/C][C]7.64[/C][C]NA[/C][C]NA[/C][C]0.998833[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]7.66[/C][C]NA[/C][C]NA[/C][C]0.998184[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]7.67[/C][C]NA[/C][C]NA[/C][C]0.999838[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]7.68[/C][C]NA[/C][C]NA[/C][C]1.00085[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]7.69[/C][C]NA[/C][C]NA[/C][C]1.00086[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]NA[/C][C]NA[/C][C]1.00055[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231639&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
16.11NANA0.999089NA
26.13NANA0.999378NA
36.15NANA1.00201NA
46.15NANA1.00108NA
56.16NANA1.0006NA
66.18NANA0.998722NA
76.216.196936.204170.9988331.00211
86.226.208296.219580.9981841.00189
96.236.235246.236250.9998380.999159
106.266.259486.254171.000851.00008
116.286.277926.27251.000861.00033
126.286.293456.291.000550.997863
136.296.30056.306250.9990890.998333
146.326.318156.322080.9993781.00029
156.366.350656.337921.002011.00147
166.376.359786.352921.001081.00161
176.386.370516.366671.00061.00149
186.386.373096.381250.9987221.00108
196.46.38926.396670.9988331.00169
206.416.399196.410830.9981841.00169
216.426.422716.423750.9998380.999578
226.436.442566.437081.000850.998051
236.446.457246.451671.000860.997331
246.476.470636.467081.000550.999902
256.476.477426.483330.9990890.998854
266.486.496376.500420.9993780.99748
276.516.531856.518751.002010.996655
286.546.547076.541.001080.998921
296.566.568966.5651.00060.998636
306.576.582826.591250.9987220.998052
316.66.61026.617920.9988330.998458
326.626.634186.646250.9981840.997862
336.656.674346.675420.9998380.996353
346.716.709036.703331.000851.00014
356.766.735396.729581.000861.00365
366.786.759126.755421.000551.00309
376.86.774656.780830.9990891.00374
386.836.80166.805830.9993781.00418
396.866.843736.831.002011.00238
406.866.858656.851251.001081.0002
416.876.873316.869171.00060.999518
426.886.877036.885830.9987221.00043
436.96.894036.902080.9988331.00087
446.926.904946.91750.9981841.00218
456.936.932216.933330.9998380.999681
466.946.956336.950421.000850.997653
476.966.973936.967921.000860.998002
486.986.988836.9851.000550.998736
496.996.995297.001670.9990890.999244
507.017.013557.017920.9993780.999494
517.067.052067.037921.002011.00113
527.077.070137.06251.001080.999982
537.087.091367.087081.00060.998398
547.087.101747.110830.9987220.996938
557.17.125847.134170.9988330.996373
567.117.144927.157920.9981840.995113
577.227.179677.180830.9998381.00562
587.247.209047.202921.000851.00429
597.257.231657.225421.000861.00254
607.267.252317.248331.000551.00106
617.277.265467.272080.9990891.00063
627.37.292137.296670.9993781.00108
637.327.332627.317921.002010.998279
647.347.343767.335831.001080.999488
657.357.358617.354171.00060.99883
667.367.363917.373330.9987220.999469
677.397.384717.393330.9988331.00072
687.417.399047.41250.9981841.00148
697.437.43137.43250.9998380.999825
707.467.460097.453751.000850.999988
717.477.482297.475831.000860.998358
727.57.503287.499171.000550.999563
737.517.51447.521250.9990890.999415
747.527.537397.542080.9993780.997692
757.587.57777.56251.002011.0003
767.597.589867.581671.001081.00002
777.637.604597.61.00061.00334
787.647.607767.61750.9987221.00424
797.64NANA0.998833NA
807.66NANA0.998184NA
817.67NANA0.999838NA
827.68NANA1.00085NA
837.69NANA1.00086NA
847.7NANA1.00055NA



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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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')