## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 17:26:34 -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/t1386887229213m6666xh9e2ca.htm/, Retrieved Tue, 07 Dec 2021 12:22:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232282, Retrieved Tue, 07 Dec 2021 12:22:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 22:26:34] [f3e37d24265d1c1b6ba14664c97da4c0] [Current]
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Dataseries X:
1.31
1.32
1.32
1.33
1.33
1.33
1.34
1.33
1.32
1.31
1.31
1.33
1.34
1.33
1.33
1.34
1.34
1.34
1.35
1.35
1.35
1.34
1.35
1.36
1.35
1.36
1.36
1.36
1.37
1.39
1.39
1.38
1.37
1.39
1.38
1.4
1.41
1.4
1.42
1.43
1.44
1.44
1.44
1.46
1.46
1.49
1.49
1.48
1.49
1.5
1.5
1.5
1.47
1.49
1.49
1.5
1.52
1.52
1.52
1.52
1.53
1.54
1.51
1.49
1.49
1.49
1.48
1.49
1.49
1.47
1.49
1.49

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 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 & 7 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232282&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]7 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=232282&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232282&T=0

As an alternative you can also use a QR Code:

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

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 seconds R Server 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.31 NA NA 1.00411 NA 2 1.32 NA NA 1.00355 NA 3 1.32 NA NA 1.00045 NA 4 1.33 NA NA 0.998715 NA 5 1.33 NA NA 0.995523 NA 6 1.33 NA NA 0.999091 NA 7 1.34 1.3269 1.32458 1.00175 1.00988 8 1.33 1.32663 1.32625 1.00029 1.00254 9 1.32 1.32389 1.32708 0.997592 0.997063 10 1.31 1.32726 1.32792 0.999507 0.986994 11 1.31 1.32565 1.32875 0.997663 0.988198 12 1.33 1.33193 1.32958 1.00176 0.998554 13 1.34 1.33589 1.33042 1.00411 1.00308 14 1.33 1.3364 1.33167 1.00355 0.995212 15 1.33 1.33435 1.33375 1.00045 0.996744 16 1.34 1.33453 1.33625 0.998715 1.0041 17 1.34 1.33317 1.33917 0.995523 1.00512 18 1.34 1.34086 1.34208 0.999091 0.999356 19 1.35 1.3461 1.34375 1.00175 1.0029 20 1.35 1.34581 1.34542 1.00029 1.00312 21 1.35 1.34467 1.34792 0.997592 1.00396 22 1.34 1.34933 1.35 0.999507 0.993082 23 1.35 1.34892 1.35208 0.997663 1.0008 24 1.36 1.3578 1.35542 1.00176 1.00162 25 1.35 1.36475 1.35917 1.00411 0.989189 26 1.36 1.36692 1.36208 1.00355 0.994935 27 1.36 1.36478 1.36417 1.00045 0.996501 28 1.36 1.36533 1.36708 0.998715 0.996099 29 1.37 1.36428 1.37042 0.995523 1.00419 30 1.39 1.37209 1.37333 0.999091 1.01306 31 1.39 1.37991 1.3775 1.00175 1.00732 32 1.38 1.38207 1.38167 1.00029 0.998504 33 1.37 1.3825 1.38583 0.997592 0.990961 34 1.39 1.39056 1.39125 0.999507 0.999594 35 1.38 1.39382 1.39708 0.997663 0.990085 36 1.4 1.40455 1.40208 1.00176 0.996758 37 1.41 1.41203 1.40625 1.00411 0.998561 38 1.4 1.41668 1.41167 1.00355 0.988224 39 1.42 1.41938 1.41875 1.00045 1.00043 40 1.43 1.42483 1.42667 0.998715 1.00363 41 1.44 1.42899 1.43542 0.995523 1.0077 42 1.44 1.44202 1.44333 0.999091 0.998598 43 1.44 1.45253 1.45 1.00175 0.991373 44 1.46 1.45792 1.4575 1.00029 1.00142 45 1.46 1.46147 1.465 0.997592 0.998992 46 1.49 1.47052 1.47125 0.999507 1.01324 47 1.49 1.47197 1.47542 0.997663 1.01225 48 1.48 1.48135 1.47875 1.00176 0.999085 49 1.49 1.48901 1.48292 1.00411 1.00066 50 1.5 1.49195 1.48667 1.00355 1.0054 51 1.5 1.4915 1.49083 1.00045 1.0057 52 1.5 1.49266 1.49458 0.998715 1.00492 53 1.47 1.49038 1.49708 0.995523 0.986325 54 1.49 1.49864 1.5 0.999091 0.994237 55 1.49 1.50596 1.50333 1.00175 0.989403 56 1.5 1.5071 1.50667 1.00029 0.995286 57 1.52 1.50512 1.50875 0.997592 1.00989 58 1.52 1.50801 1.50875 0.999507 1.00795 59 1.52 1.50564 1.50917 0.997663 1.00954 60 1.52 1.51266 1.51 1.00176 1.00485 61 1.53 1.51579 1.50958 1.00411 1.00937 62 1.54 1.51411 1.50875 1.00355 1.0171 63 1.51 1.50776 1.50708 1.00045 1.00149 64 1.49 1.50182 1.50375 0.998715 0.992131 65 1.49 1.4937 1.50042 0.995523 0.997524 66 1.49 1.49656 1.49792 0.999091 0.99562 67 1.48 NA NA 1.00175 NA 68 1.49 NA NA 1.00029 NA 69 1.49 NA NA 0.997592 NA 70 1.47 NA NA 0.999507 NA 71 1.49 NA NA 0.997663 NA 72 1.49 NA NA 1.00176 NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.31 & NA & NA & 1.00411 & NA \tabularnewline
2 & 1.32 & NA & NA & 1.00355 & NA \tabularnewline
3 & 1.32 & NA & NA & 1.00045 & NA \tabularnewline
4 & 1.33 & NA & NA & 0.998715 & NA \tabularnewline
5 & 1.33 & NA & NA & 0.995523 & NA \tabularnewline
6 & 1.33 & NA & NA & 0.999091 & NA \tabularnewline
7 & 1.34 & 1.3269 & 1.32458 & 1.00175 & 1.00988 \tabularnewline
8 & 1.33 & 1.32663 & 1.32625 & 1.00029 & 1.00254 \tabularnewline
9 & 1.32 & 1.32389 & 1.32708 & 0.997592 & 0.997063 \tabularnewline
10 & 1.31 & 1.32726 & 1.32792 & 0.999507 & 0.986994 \tabularnewline
11 & 1.31 & 1.32565 & 1.32875 & 0.997663 & 0.988198 \tabularnewline
12 & 1.33 & 1.33193 & 1.32958 & 1.00176 & 0.998554 \tabularnewline
13 & 1.34 & 1.33589 & 1.33042 & 1.00411 & 1.00308 \tabularnewline
14 & 1.33 & 1.3364 & 1.33167 & 1.00355 & 0.995212 \tabularnewline
15 & 1.33 & 1.33435 & 1.33375 & 1.00045 & 0.996744 \tabularnewline
16 & 1.34 & 1.33453 & 1.33625 & 0.998715 & 1.0041 \tabularnewline
17 & 1.34 & 1.33317 & 1.33917 & 0.995523 & 1.00512 \tabularnewline
18 & 1.34 & 1.34086 & 1.34208 & 0.999091 & 0.999356 \tabularnewline
19 & 1.35 & 1.3461 & 1.34375 & 1.00175 & 1.0029 \tabularnewline
20 & 1.35 & 1.34581 & 1.34542 & 1.00029 & 1.00312 \tabularnewline
21 & 1.35 & 1.34467 & 1.34792 & 0.997592 & 1.00396 \tabularnewline
22 & 1.34 & 1.34933 & 1.35 & 0.999507 & 0.993082 \tabularnewline
23 & 1.35 & 1.34892 & 1.35208 & 0.997663 & 1.0008 \tabularnewline
24 & 1.36 & 1.3578 & 1.35542 & 1.00176 & 1.00162 \tabularnewline
25 & 1.35 & 1.36475 & 1.35917 & 1.00411 & 0.989189 \tabularnewline
26 & 1.36 & 1.36692 & 1.36208 & 1.00355 & 0.994935 \tabularnewline
27 & 1.36 & 1.36478 & 1.36417 & 1.00045 & 0.996501 \tabularnewline
28 & 1.36 & 1.36533 & 1.36708 & 0.998715 & 0.996099 \tabularnewline
29 & 1.37 & 1.36428 & 1.37042 & 0.995523 & 1.00419 \tabularnewline
30 & 1.39 & 1.37209 & 1.37333 & 0.999091 & 1.01306 \tabularnewline
31 & 1.39 & 1.37991 & 1.3775 & 1.00175 & 1.00732 \tabularnewline
32 & 1.38 & 1.38207 & 1.38167 & 1.00029 & 0.998504 \tabularnewline
33 & 1.37 & 1.3825 & 1.38583 & 0.997592 & 0.990961 \tabularnewline
34 & 1.39 & 1.39056 & 1.39125 & 0.999507 & 0.999594 \tabularnewline
35 & 1.38 & 1.39382 & 1.39708 & 0.997663 & 0.990085 \tabularnewline
36 & 1.4 & 1.40455 & 1.40208 & 1.00176 & 0.996758 \tabularnewline
37 & 1.41 & 1.41203 & 1.40625 & 1.00411 & 0.998561 \tabularnewline
38 & 1.4 & 1.41668 & 1.41167 & 1.00355 & 0.988224 \tabularnewline
39 & 1.42 & 1.41938 & 1.41875 & 1.00045 & 1.00043 \tabularnewline
40 & 1.43 & 1.42483 & 1.42667 & 0.998715 & 1.00363 \tabularnewline
41 & 1.44 & 1.42899 & 1.43542 & 0.995523 & 1.0077 \tabularnewline
42 & 1.44 & 1.44202 & 1.44333 & 0.999091 & 0.998598 \tabularnewline
43 & 1.44 & 1.45253 & 1.45 & 1.00175 & 0.991373 \tabularnewline
44 & 1.46 & 1.45792 & 1.4575 & 1.00029 & 1.00142 \tabularnewline
45 & 1.46 & 1.46147 & 1.465 & 0.997592 & 0.998992 \tabularnewline
46 & 1.49 & 1.47052 & 1.47125 & 0.999507 & 1.01324 \tabularnewline
47 & 1.49 & 1.47197 & 1.47542 & 0.997663 & 1.01225 \tabularnewline
48 & 1.48 & 1.48135 & 1.47875 & 1.00176 & 0.999085 \tabularnewline
49 & 1.49 & 1.48901 & 1.48292 & 1.00411 & 1.00066 \tabularnewline
50 & 1.5 & 1.49195 & 1.48667 & 1.00355 & 1.0054 \tabularnewline
51 & 1.5 & 1.4915 & 1.49083 & 1.00045 & 1.0057 \tabularnewline
52 & 1.5 & 1.49266 & 1.49458 & 0.998715 & 1.00492 \tabularnewline
53 & 1.47 & 1.49038 & 1.49708 & 0.995523 & 0.986325 \tabularnewline
54 & 1.49 & 1.49864 & 1.5 & 0.999091 & 0.994237 \tabularnewline
55 & 1.49 & 1.50596 & 1.50333 & 1.00175 & 0.989403 \tabularnewline
56 & 1.5 & 1.5071 & 1.50667 & 1.00029 & 0.995286 \tabularnewline
57 & 1.52 & 1.50512 & 1.50875 & 0.997592 & 1.00989 \tabularnewline
58 & 1.52 & 1.50801 & 1.50875 & 0.999507 & 1.00795 \tabularnewline
59 & 1.52 & 1.50564 & 1.50917 & 0.997663 & 1.00954 \tabularnewline
60 & 1.52 & 1.51266 & 1.51 & 1.00176 & 1.00485 \tabularnewline
61 & 1.53 & 1.51579 & 1.50958 & 1.00411 & 1.00937 \tabularnewline
62 & 1.54 & 1.51411 & 1.50875 & 1.00355 & 1.0171 \tabularnewline
63 & 1.51 & 1.50776 & 1.50708 & 1.00045 & 1.00149 \tabularnewline
64 & 1.49 & 1.50182 & 1.50375 & 0.998715 & 0.992131 \tabularnewline
65 & 1.49 & 1.4937 & 1.50042 & 0.995523 & 0.997524 \tabularnewline
66 & 1.49 & 1.49656 & 1.49792 & 0.999091 & 0.99562 \tabularnewline
67 & 1.48 & NA & NA & 1.00175 & NA \tabularnewline
68 & 1.49 & NA & NA & 1.00029 & NA \tabularnewline
69 & 1.49 & NA & NA & 0.997592 & NA \tabularnewline
70 & 1.47 & NA & NA & 0.999507 & NA \tabularnewline
71 & 1.49 & NA & NA & 0.997663 & NA \tabularnewline
72 & 1.49 & NA & NA & 1.00176 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232282&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]1.31[/C][C]NA[/C][C]NA[/C][C]1.00411[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.32[/C][C]NA[/C][C]NA[/C][C]1.00355[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.32[/C][C]NA[/C][C]NA[/C][C]1.00045[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.33[/C][C]NA[/C][C]NA[/C][C]0.998715[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.33[/C][C]NA[/C][C]NA[/C][C]0.995523[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.33[/C][C]NA[/C][C]NA[/C][C]0.999091[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.34[/C][C]1.3269[/C][C]1.32458[/C][C]1.00175[/C][C]1.00988[/C][/ROW]
[ROW][C]8[/C][C]1.33[/C][C]1.32663[/C][C]1.32625[/C][C]1.00029[/C][C]1.00254[/C][/ROW]
[ROW][C]9[/C][C]1.32[/C][C]1.32389[/C][C]1.32708[/C][C]0.997592[/C][C]0.997063[/C][/ROW]
[ROW][C]10[/C][C]1.31[/C][C]1.32726[/C][C]1.32792[/C][C]0.999507[/C][C]0.986994[/C][/ROW]
[ROW][C]11[/C][C]1.31[/C][C]1.32565[/C][C]1.32875[/C][C]0.997663[/C][C]0.988198[/C][/ROW]
[ROW][C]12[/C][C]1.33[/C][C]1.33193[/C][C]1.32958[/C][C]1.00176[/C][C]0.998554[/C][/ROW]
[ROW][C]13[/C][C]1.34[/C][C]1.33589[/C][C]1.33042[/C][C]1.00411[/C][C]1.00308[/C][/ROW]
[ROW][C]14[/C][C]1.33[/C][C]1.3364[/C][C]1.33167[/C][C]1.00355[/C][C]0.995212[/C][/ROW]
[ROW][C]15[/C][C]1.33[/C][C]1.33435[/C][C]1.33375[/C][C]1.00045[/C][C]0.996744[/C][/ROW]
[ROW][C]16[/C][C]1.34[/C][C]1.33453[/C][C]1.33625[/C][C]0.998715[/C][C]1.0041[/C][/ROW]
[ROW][C]17[/C][C]1.34[/C][C]1.33317[/C][C]1.33917[/C][C]0.995523[/C][C]1.00512[/C][/ROW]
[ROW][C]18[/C][C]1.34[/C][C]1.34086[/C][C]1.34208[/C][C]0.999091[/C][C]0.999356[/C][/ROW]
[ROW][C]19[/C][C]1.35[/C][C]1.3461[/C][C]1.34375[/C][C]1.00175[/C][C]1.0029[/C][/ROW]
[ROW][C]20[/C][C]1.35[/C][C]1.34581[/C][C]1.34542[/C][C]1.00029[/C][C]1.00312[/C][/ROW]
[ROW][C]21[/C][C]1.35[/C][C]1.34467[/C][C]1.34792[/C][C]0.997592[/C][C]1.00396[/C][/ROW]
[ROW][C]22[/C][C]1.34[/C][C]1.34933[/C][C]1.35[/C][C]0.999507[/C][C]0.993082[/C][/ROW]
[ROW][C]23[/C][C]1.35[/C][C]1.34892[/C][C]1.35208[/C][C]0.997663[/C][C]1.0008[/C][/ROW]
[ROW][C]24[/C][C]1.36[/C][C]1.3578[/C][C]1.35542[/C][C]1.00176[/C][C]1.00162[/C][/ROW]
[ROW][C]25[/C][C]1.35[/C][C]1.36475[/C][C]1.35917[/C][C]1.00411[/C][C]0.989189[/C][/ROW]
[ROW][C]26[/C][C]1.36[/C][C]1.36692[/C][C]1.36208[/C][C]1.00355[/C][C]0.994935[/C][/ROW]
[ROW][C]27[/C][C]1.36[/C][C]1.36478[/C][C]1.36417[/C][C]1.00045[/C][C]0.996501[/C][/ROW]
[ROW][C]28[/C][C]1.36[/C][C]1.36533[/C][C]1.36708[/C][C]0.998715[/C][C]0.996099[/C][/ROW]
[ROW][C]29[/C][C]1.37[/C][C]1.36428[/C][C]1.37042[/C][C]0.995523[/C][C]1.00419[/C][/ROW]
[ROW][C]30[/C][C]1.39[/C][C]1.37209[/C][C]1.37333[/C][C]0.999091[/C][C]1.01306[/C][/ROW]
[ROW][C]31[/C][C]1.39[/C][C]1.37991[/C][C]1.3775[/C][C]1.00175[/C][C]1.00732[/C][/ROW]
[ROW][C]32[/C][C]1.38[/C][C]1.38207[/C][C]1.38167[/C][C]1.00029[/C][C]0.998504[/C][/ROW]
[ROW][C]33[/C][C]1.37[/C][C]1.3825[/C][C]1.38583[/C][C]0.997592[/C][C]0.990961[/C][/ROW]
[ROW][C]34[/C][C]1.39[/C][C]1.39056[/C][C]1.39125[/C][C]0.999507[/C][C]0.999594[/C][/ROW]
[ROW][C]35[/C][C]1.38[/C][C]1.39382[/C][C]1.39708[/C][C]0.997663[/C][C]0.990085[/C][/ROW]
[ROW][C]36[/C][C]1.4[/C][C]1.40455[/C][C]1.40208[/C][C]1.00176[/C][C]0.996758[/C][/ROW]
[ROW][C]37[/C][C]1.41[/C][C]1.41203[/C][C]1.40625[/C][C]1.00411[/C][C]0.998561[/C][/ROW]
[ROW][C]38[/C][C]1.4[/C][C]1.41668[/C][C]1.41167[/C][C]1.00355[/C][C]0.988224[/C][/ROW]
[ROW][C]39[/C][C]1.42[/C][C]1.41938[/C][C]1.41875[/C][C]1.00045[/C][C]1.00043[/C][/ROW]
[ROW][C]40[/C][C]1.43[/C][C]1.42483[/C][C]1.42667[/C][C]0.998715[/C][C]1.00363[/C][/ROW]
[ROW][C]41[/C][C]1.44[/C][C]1.42899[/C][C]1.43542[/C][C]0.995523[/C][C]1.0077[/C][/ROW]
[ROW][C]42[/C][C]1.44[/C][C]1.44202[/C][C]1.44333[/C][C]0.999091[/C][C]0.998598[/C][/ROW]
[ROW][C]43[/C][C]1.44[/C][C]1.45253[/C][C]1.45[/C][C]1.00175[/C][C]0.991373[/C][/ROW]
[ROW][C]44[/C][C]1.46[/C][C]1.45792[/C][C]1.4575[/C][C]1.00029[/C][C]1.00142[/C][/ROW]
[ROW][C]45[/C][C]1.46[/C][C]1.46147[/C][C]1.465[/C][C]0.997592[/C][C]0.998992[/C][/ROW]
[ROW][C]46[/C][C]1.49[/C][C]1.47052[/C][C]1.47125[/C][C]0.999507[/C][C]1.01324[/C][/ROW]
[ROW][C]47[/C][C]1.49[/C][C]1.47197[/C][C]1.47542[/C][C]0.997663[/C][C]1.01225[/C][/ROW]
[ROW][C]48[/C][C]1.48[/C][C]1.48135[/C][C]1.47875[/C][C]1.00176[/C][C]0.999085[/C][/ROW]
[ROW][C]49[/C][C]1.49[/C][C]1.48901[/C][C]1.48292[/C][C]1.00411[/C][C]1.00066[/C][/ROW]
[ROW][C]50[/C][C]1.5[/C][C]1.49195[/C][C]1.48667[/C][C]1.00355[/C][C]1.0054[/C][/ROW]
[ROW][C]51[/C][C]1.5[/C][C]1.4915[/C][C]1.49083[/C][C]1.00045[/C][C]1.0057[/C][/ROW]
[ROW][C]52[/C][C]1.5[/C][C]1.49266[/C][C]1.49458[/C][C]0.998715[/C][C]1.00492[/C][/ROW]
[ROW][C]53[/C][C]1.47[/C][C]1.49038[/C][C]1.49708[/C][C]0.995523[/C][C]0.986325[/C][/ROW]
[ROW][C]54[/C][C]1.49[/C][C]1.49864[/C][C]1.5[/C][C]0.999091[/C][C]0.994237[/C][/ROW]
[ROW][C]55[/C][C]1.49[/C][C]1.50596[/C][C]1.50333[/C][C]1.00175[/C][C]0.989403[/C][/ROW]
[ROW][C]56[/C][C]1.5[/C][C]1.5071[/C][C]1.50667[/C][C]1.00029[/C][C]0.995286[/C][/ROW]
[ROW][C]57[/C][C]1.52[/C][C]1.50512[/C][C]1.50875[/C][C]0.997592[/C][C]1.00989[/C][/ROW]
[ROW][C]58[/C][C]1.52[/C][C]1.50801[/C][C]1.50875[/C][C]0.999507[/C][C]1.00795[/C][/ROW]
[ROW][C]59[/C][C]1.52[/C][C]1.50564[/C][C]1.50917[/C][C]0.997663[/C][C]1.00954[/C][/ROW]
[ROW][C]60[/C][C]1.52[/C][C]1.51266[/C][C]1.51[/C][C]1.00176[/C][C]1.00485[/C][/ROW]
[ROW][C]61[/C][C]1.53[/C][C]1.51579[/C][C]1.50958[/C][C]1.00411[/C][C]1.00937[/C][/ROW]
[ROW][C]62[/C][C]1.54[/C][C]1.51411[/C][C]1.50875[/C][C]1.00355[/C][C]1.0171[/C][/ROW]
[ROW][C]63[/C][C]1.51[/C][C]1.50776[/C][C]1.50708[/C][C]1.00045[/C][C]1.00149[/C][/ROW]
[ROW][C]64[/C][C]1.49[/C][C]1.50182[/C][C]1.50375[/C][C]0.998715[/C][C]0.992131[/C][/ROW]
[ROW][C]65[/C][C]1.49[/C][C]1.4937[/C][C]1.50042[/C][C]0.995523[/C][C]0.997524[/C][/ROW]
[ROW][C]66[/C][C]1.49[/C][C]1.49656[/C][C]1.49792[/C][C]0.999091[/C][C]0.99562[/C][/ROW]
[ROW][C]67[/C][C]1.48[/C][C]NA[/C][C]NA[/C][C]1.00175[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.49[/C][C]NA[/C][C]NA[/C][C]1.00029[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.49[/C][C]NA[/C][C]NA[/C][C]0.997592[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.47[/C][C]NA[/C][C]NA[/C][C]0.999507[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.49[/C][C]NA[/C][C]NA[/C][C]0.997663[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.49[/C][C]NA[/C][C]NA[/C][C]1.00176[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232282&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232282&T=1

As an alternative you can also use a QR Code:

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

 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.31 NA NA 1.00411 NA 2 1.32 NA NA 1.00355 NA 3 1.32 NA NA 1.00045 NA 4 1.33 NA NA 0.998715 NA 5 1.33 NA NA 0.995523 NA 6 1.33 NA NA 0.999091 NA 7 1.34 1.3269 1.32458 1.00175 1.00988 8 1.33 1.32663 1.32625 1.00029 1.00254 9 1.32 1.32389 1.32708 0.997592 0.997063 10 1.31 1.32726 1.32792 0.999507 0.986994 11 1.31 1.32565 1.32875 0.997663 0.988198 12 1.33 1.33193 1.32958 1.00176 0.998554 13 1.34 1.33589 1.33042 1.00411 1.00308 14 1.33 1.3364 1.33167 1.00355 0.995212 15 1.33 1.33435 1.33375 1.00045 0.996744 16 1.34 1.33453 1.33625 0.998715 1.0041 17 1.34 1.33317 1.33917 0.995523 1.00512 18 1.34 1.34086 1.34208 0.999091 0.999356 19 1.35 1.3461 1.34375 1.00175 1.0029 20 1.35 1.34581 1.34542 1.00029 1.00312 21 1.35 1.34467 1.34792 0.997592 1.00396 22 1.34 1.34933 1.35 0.999507 0.993082 23 1.35 1.34892 1.35208 0.997663 1.0008 24 1.36 1.3578 1.35542 1.00176 1.00162 25 1.35 1.36475 1.35917 1.00411 0.989189 26 1.36 1.36692 1.36208 1.00355 0.994935 27 1.36 1.36478 1.36417 1.00045 0.996501 28 1.36 1.36533 1.36708 0.998715 0.996099 29 1.37 1.36428 1.37042 0.995523 1.00419 30 1.39 1.37209 1.37333 0.999091 1.01306 31 1.39 1.37991 1.3775 1.00175 1.00732 32 1.38 1.38207 1.38167 1.00029 0.998504 33 1.37 1.3825 1.38583 0.997592 0.990961 34 1.39 1.39056 1.39125 0.999507 0.999594 35 1.38 1.39382 1.39708 0.997663 0.990085 36 1.4 1.40455 1.40208 1.00176 0.996758 37 1.41 1.41203 1.40625 1.00411 0.998561 38 1.4 1.41668 1.41167 1.00355 0.988224 39 1.42 1.41938 1.41875 1.00045 1.00043 40 1.43 1.42483 1.42667 0.998715 1.00363 41 1.44 1.42899 1.43542 0.995523 1.0077 42 1.44 1.44202 1.44333 0.999091 0.998598 43 1.44 1.45253 1.45 1.00175 0.991373 44 1.46 1.45792 1.4575 1.00029 1.00142 45 1.46 1.46147 1.465 0.997592 0.998992 46 1.49 1.47052 1.47125 0.999507 1.01324 47 1.49 1.47197 1.47542 0.997663 1.01225 48 1.48 1.48135 1.47875 1.00176 0.999085 49 1.49 1.48901 1.48292 1.00411 1.00066 50 1.5 1.49195 1.48667 1.00355 1.0054 51 1.5 1.4915 1.49083 1.00045 1.0057 52 1.5 1.49266 1.49458 0.998715 1.00492 53 1.47 1.49038 1.49708 0.995523 0.986325 54 1.49 1.49864 1.5 0.999091 0.994237 55 1.49 1.50596 1.50333 1.00175 0.989403 56 1.5 1.5071 1.50667 1.00029 0.995286 57 1.52 1.50512 1.50875 0.997592 1.00989 58 1.52 1.50801 1.50875 0.999507 1.00795 59 1.52 1.50564 1.50917 0.997663 1.00954 60 1.52 1.51266 1.51 1.00176 1.00485 61 1.53 1.51579 1.50958 1.00411 1.00937 62 1.54 1.51411 1.50875 1.00355 1.0171 63 1.51 1.50776 1.50708 1.00045 1.00149 64 1.49 1.50182 1.50375 0.998715 0.992131 65 1.49 1.4937 1.50042 0.995523 0.997524 66 1.49 1.49656 1.49792 0.999091 0.99562 67 1.48 NA NA 1.00175 NA 68 1.49 NA NA 1.00029 NA 69 1.49 NA NA 0.997592 NA 70 1.47 NA NA 0.999507 NA 71 1.49 NA NA 0.997663 NA 72 1.49 NA NA 1.00176 NA

par2 <- '12'par1 <- 'additive'par2 <- as.numeric(par2)x <- ts(x,freq=par2)m <- decompose(x,type=par1)m$figurebitmap(file='test1.png')plot(m)dev.off()mylagmax <- length(x)/2bitmap(file='test2.png')op <- par(mfrow = c(2,2))acf(as.numeric(x),lag.max = mylagmax,main='Observed')acf(as.numeric(m$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')