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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 23 Dec 2013 04:31:50 -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/23/t1387791475038jtqpgy1vscqh.htm/, Retrieved Thu, 18 Apr 2024 18:37:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232580, Retrieved Thu, 18 Apr 2024 18:37:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-23 09:31:50] [54713e3426a13268f2edfca2b563126c] [Current]
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Dataseries X:
0,43
0,45
0,44
0,44
0,44
0,48
0,47
0,47
0,47
0,49
0,49
0,46
0,45
0,44
0,42
0,43
0,43
0,47
0,47
0,47
0,47
0,48
0,48
0,48
0,49
0,49
0,47
0,5
0,51
0,5
0,49
0,5
0,51
0,51
0,5
0,53
0,5
0,49
0,46
0,46
0,47
0,49
0,5
0,5
0,51
0,5
0,52
0,5
0,48
0,47
0,43
0,42
0,45
0,5
0,52
0,52
0,51
0,52
0,52
0,51
0,51
0,51
0,48
0,49
0,47
0,51
0,5
0,51
0,51
0,52
0,51
0,52
0,48
0,49
0,47
0,44
0,44
0,47
0,51
0,51
0,52
0,52
0,52
0,52




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 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 & 8 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232580&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]8 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=232580&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232580&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 time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
10.43NANA0.000439815NA
20.45NANA-0.00344907NA
30.44NANA-0.0307407NA
40.44NANA-0.0296296NA
50.44NANA-0.0250463NA
60.48NANA0.00266204NA
70.470.4702310.4616670.00856481-0.000231481
80.470.4733560.4620830.0112731-0.00335648
90.470.4732870.4608330.0124537-0.00328704
100.490.4784950.4595830.0189120.0115046
110.490.4776620.458750.0189120.012338
120.460.4735650.4579170.0156481-0.0135648
130.450.457940.45750.000439815-0.00793981
140.440.4540510.4575-0.00344907-0.0140509
150.420.4267590.4575-0.0307407-0.00675926
160.430.4274540.457083-0.02962960.0025463
170.430.4312040.45625-0.0250463-0.0012037
180.470.4593290.4566670.002662040.0106713
190.470.4677310.4591670.008564810.00226852
200.470.474190.4629170.0112731-0.00418981
210.470.4795370.4670830.0124537-0.00953704
220.480.4909950.4720830.018912-0.0109954
230.480.4972450.4783330.018912-0.0172454
240.480.4985650.4829170.0156481-0.0185648
250.490.485440.4850.0004398150.00456019
260.490.4836340.487083-0.003449070.00636574
270.470.4592590.49-0.03074070.0107407
280.50.4632870.492917-0.02962960.036713
290.510.4699540.495-0.02504630.0400463
300.50.5005790.4979170.00266204-0.000578704
310.490.5089810.5004170.00856481-0.0189815
320.50.5121060.5008330.0112731-0.0121065
330.510.512870.5004170.0124537-0.00287037
340.510.5172450.4983330.018912-0.00724537
350.50.5139120.4950.018912-0.013912
360.530.5085650.4929170.01564810.0214352
370.50.4933560.4929170.0004398150.00664352
380.490.4898840.493333-0.003449070.000115741
390.460.4625930.493333-0.0307407-0.00259259
400.460.4632870.492917-0.0296296-0.00328704
410.470.4682870.493333-0.02504630.00171296
420.490.4955790.4929170.00266204-0.0055787
430.50.4993980.4908330.008564810.000601852
440.50.500440.4891670.0112731-0.000439815
450.510.4995370.4870830.01245370.010463
460.50.5030790.4841670.018912-0.0030787
470.520.5005790.4816670.0189120.0194213
480.50.4968980.481250.01564810.00310185
490.480.482940.48250.000439815-0.00293981
500.470.4807180.484167-0.00344907-0.0107176
510.430.4542590.485-0.0307407-0.0242593
520.420.4562040.485833-0.0296296-0.0362037
530.450.461620.486667-0.0250463-0.0116204
540.50.4897450.4870830.002662040.0102546
550.520.4973150.488750.008564810.0226852
560.520.502940.4916670.01127310.0170602
570.510.507870.4954170.01245370.00212963
580.520.5193290.5004170.0189120.000671296
590.520.5230790.5041670.018912-0.0030787
600.510.5210650.5054170.0156481-0.0110648
610.510.505440.5050.0004398150.00456019
620.510.5003010.50375-0.003449070.00969907
630.480.4725930.503333-0.03074070.00740741
640.490.4737040.503333-0.02962960.0162963
650.470.477870.502917-0.0250463-0.00787037
660.510.5055790.5029170.002662040.0044213
670.50.5106480.5020830.00856481-0.0106481
680.510.5112730.50.0112731-0.00127315
690.510.5112040.498750.0124537-0.0012037
700.520.5151620.496250.0189120.00483796
710.510.5118290.4929170.018912-0.0018287
720.520.5056480.490.01564810.0143519
730.480.489190.488750.000439815-0.00918981
740.490.4857180.489167-0.003449070.00428241
750.470.4588430.489583-0.03074070.0111574
760.440.460370.49-0.0296296-0.0203704
770.440.465370.490417-0.0250463-0.0253704
780.470.4934950.4908330.00266204-0.0234954
790.51NANA0.00856481NA
800.51NANA0.0112731NA
810.52NANA0.0124537NA
820.52NANA0.018912NA
830.52NANA0.018912NA
840.52NANA0.0156481NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.43 & NA & NA & 0.000439815 & NA \tabularnewline
2 & 0.45 & NA & NA & -0.00344907 & NA \tabularnewline
3 & 0.44 & NA & NA & -0.0307407 & NA \tabularnewline
4 & 0.44 & NA & NA & -0.0296296 & NA \tabularnewline
5 & 0.44 & NA & NA & -0.0250463 & NA \tabularnewline
6 & 0.48 & NA & NA & 0.00266204 & NA \tabularnewline
7 & 0.47 & 0.470231 & 0.461667 & 0.00856481 & -0.000231481 \tabularnewline
8 & 0.47 & 0.473356 & 0.462083 & 0.0112731 & -0.00335648 \tabularnewline
9 & 0.47 & 0.473287 & 0.460833 & 0.0124537 & -0.00328704 \tabularnewline
10 & 0.49 & 0.478495 & 0.459583 & 0.018912 & 0.0115046 \tabularnewline
11 & 0.49 & 0.477662 & 0.45875 & 0.018912 & 0.012338 \tabularnewline
12 & 0.46 & 0.473565 & 0.457917 & 0.0156481 & -0.0135648 \tabularnewline
13 & 0.45 & 0.45794 & 0.4575 & 0.000439815 & -0.00793981 \tabularnewline
14 & 0.44 & 0.454051 & 0.4575 & -0.00344907 & -0.0140509 \tabularnewline
15 & 0.42 & 0.426759 & 0.4575 & -0.0307407 & -0.00675926 \tabularnewline
16 & 0.43 & 0.427454 & 0.457083 & -0.0296296 & 0.0025463 \tabularnewline
17 & 0.43 & 0.431204 & 0.45625 & -0.0250463 & -0.0012037 \tabularnewline
18 & 0.47 & 0.459329 & 0.456667 & 0.00266204 & 0.0106713 \tabularnewline
19 & 0.47 & 0.467731 & 0.459167 & 0.00856481 & 0.00226852 \tabularnewline
20 & 0.47 & 0.47419 & 0.462917 & 0.0112731 & -0.00418981 \tabularnewline
21 & 0.47 & 0.479537 & 0.467083 & 0.0124537 & -0.00953704 \tabularnewline
22 & 0.48 & 0.490995 & 0.472083 & 0.018912 & -0.0109954 \tabularnewline
23 & 0.48 & 0.497245 & 0.478333 & 0.018912 & -0.0172454 \tabularnewline
24 & 0.48 & 0.498565 & 0.482917 & 0.0156481 & -0.0185648 \tabularnewline
25 & 0.49 & 0.48544 & 0.485 & 0.000439815 & 0.00456019 \tabularnewline
26 & 0.49 & 0.483634 & 0.487083 & -0.00344907 & 0.00636574 \tabularnewline
27 & 0.47 & 0.459259 & 0.49 & -0.0307407 & 0.0107407 \tabularnewline
28 & 0.5 & 0.463287 & 0.492917 & -0.0296296 & 0.036713 \tabularnewline
29 & 0.51 & 0.469954 & 0.495 & -0.0250463 & 0.0400463 \tabularnewline
30 & 0.5 & 0.500579 & 0.497917 & 0.00266204 & -0.000578704 \tabularnewline
31 & 0.49 & 0.508981 & 0.500417 & 0.00856481 & -0.0189815 \tabularnewline
32 & 0.5 & 0.512106 & 0.500833 & 0.0112731 & -0.0121065 \tabularnewline
33 & 0.51 & 0.51287 & 0.500417 & 0.0124537 & -0.00287037 \tabularnewline
34 & 0.51 & 0.517245 & 0.498333 & 0.018912 & -0.00724537 \tabularnewline
35 & 0.5 & 0.513912 & 0.495 & 0.018912 & -0.013912 \tabularnewline
36 & 0.53 & 0.508565 & 0.492917 & 0.0156481 & 0.0214352 \tabularnewline
37 & 0.5 & 0.493356 & 0.492917 & 0.000439815 & 0.00664352 \tabularnewline
38 & 0.49 & 0.489884 & 0.493333 & -0.00344907 & 0.000115741 \tabularnewline
39 & 0.46 & 0.462593 & 0.493333 & -0.0307407 & -0.00259259 \tabularnewline
40 & 0.46 & 0.463287 & 0.492917 & -0.0296296 & -0.00328704 \tabularnewline
41 & 0.47 & 0.468287 & 0.493333 & -0.0250463 & 0.00171296 \tabularnewline
42 & 0.49 & 0.495579 & 0.492917 & 0.00266204 & -0.0055787 \tabularnewline
43 & 0.5 & 0.499398 & 0.490833 & 0.00856481 & 0.000601852 \tabularnewline
44 & 0.5 & 0.50044 & 0.489167 & 0.0112731 & -0.000439815 \tabularnewline
45 & 0.51 & 0.499537 & 0.487083 & 0.0124537 & 0.010463 \tabularnewline
46 & 0.5 & 0.503079 & 0.484167 & 0.018912 & -0.0030787 \tabularnewline
47 & 0.52 & 0.500579 & 0.481667 & 0.018912 & 0.0194213 \tabularnewline
48 & 0.5 & 0.496898 & 0.48125 & 0.0156481 & 0.00310185 \tabularnewline
49 & 0.48 & 0.48294 & 0.4825 & 0.000439815 & -0.00293981 \tabularnewline
50 & 0.47 & 0.480718 & 0.484167 & -0.00344907 & -0.0107176 \tabularnewline
51 & 0.43 & 0.454259 & 0.485 & -0.0307407 & -0.0242593 \tabularnewline
52 & 0.42 & 0.456204 & 0.485833 & -0.0296296 & -0.0362037 \tabularnewline
53 & 0.45 & 0.46162 & 0.486667 & -0.0250463 & -0.0116204 \tabularnewline
54 & 0.5 & 0.489745 & 0.487083 & 0.00266204 & 0.0102546 \tabularnewline
55 & 0.52 & 0.497315 & 0.48875 & 0.00856481 & 0.0226852 \tabularnewline
56 & 0.52 & 0.50294 & 0.491667 & 0.0112731 & 0.0170602 \tabularnewline
57 & 0.51 & 0.50787 & 0.495417 & 0.0124537 & 0.00212963 \tabularnewline
58 & 0.52 & 0.519329 & 0.500417 & 0.018912 & 0.000671296 \tabularnewline
59 & 0.52 & 0.523079 & 0.504167 & 0.018912 & -0.0030787 \tabularnewline
60 & 0.51 & 0.521065 & 0.505417 & 0.0156481 & -0.0110648 \tabularnewline
61 & 0.51 & 0.50544 & 0.505 & 0.000439815 & 0.00456019 \tabularnewline
62 & 0.51 & 0.500301 & 0.50375 & -0.00344907 & 0.00969907 \tabularnewline
63 & 0.48 & 0.472593 & 0.503333 & -0.0307407 & 0.00740741 \tabularnewline
64 & 0.49 & 0.473704 & 0.503333 & -0.0296296 & 0.0162963 \tabularnewline
65 & 0.47 & 0.47787 & 0.502917 & -0.0250463 & -0.00787037 \tabularnewline
66 & 0.51 & 0.505579 & 0.502917 & 0.00266204 & 0.0044213 \tabularnewline
67 & 0.5 & 0.510648 & 0.502083 & 0.00856481 & -0.0106481 \tabularnewline
68 & 0.51 & 0.511273 & 0.5 & 0.0112731 & -0.00127315 \tabularnewline
69 & 0.51 & 0.511204 & 0.49875 & 0.0124537 & -0.0012037 \tabularnewline
70 & 0.52 & 0.515162 & 0.49625 & 0.018912 & 0.00483796 \tabularnewline
71 & 0.51 & 0.511829 & 0.492917 & 0.018912 & -0.0018287 \tabularnewline
72 & 0.52 & 0.505648 & 0.49 & 0.0156481 & 0.0143519 \tabularnewline
73 & 0.48 & 0.48919 & 0.48875 & 0.000439815 & -0.00918981 \tabularnewline
74 & 0.49 & 0.485718 & 0.489167 & -0.00344907 & 0.00428241 \tabularnewline
75 & 0.47 & 0.458843 & 0.489583 & -0.0307407 & 0.0111574 \tabularnewline
76 & 0.44 & 0.46037 & 0.49 & -0.0296296 & -0.0203704 \tabularnewline
77 & 0.44 & 0.46537 & 0.490417 & -0.0250463 & -0.0253704 \tabularnewline
78 & 0.47 & 0.493495 & 0.490833 & 0.00266204 & -0.0234954 \tabularnewline
79 & 0.51 & NA & NA & 0.00856481 & NA \tabularnewline
80 & 0.51 & NA & NA & 0.0112731 & NA \tabularnewline
81 & 0.52 & NA & NA & 0.0124537 & NA \tabularnewline
82 & 0.52 & NA & NA & 0.018912 & NA \tabularnewline
83 & 0.52 & NA & NA & 0.018912 & NA \tabularnewline
84 & 0.52 & NA & NA & 0.0156481 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232580&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]0.43[/C][C]NA[/C][C]NA[/C][C]0.000439815[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.45[/C][C]NA[/C][C]NA[/C][C]-0.00344907[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.44[/C][C]NA[/C][C]NA[/C][C]-0.0307407[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.44[/C][C]NA[/C][C]NA[/C][C]-0.0296296[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.44[/C][C]NA[/C][C]NA[/C][C]-0.0250463[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.48[/C][C]NA[/C][C]NA[/C][C]0.00266204[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.47[/C][C]0.470231[/C][C]0.461667[/C][C]0.00856481[/C][C]-0.000231481[/C][/ROW]
[ROW][C]8[/C][C]0.47[/C][C]0.473356[/C][C]0.462083[/C][C]0.0112731[/C][C]-0.00335648[/C][/ROW]
[ROW][C]9[/C][C]0.47[/C][C]0.473287[/C][C]0.460833[/C][C]0.0124537[/C][C]-0.00328704[/C][/ROW]
[ROW][C]10[/C][C]0.49[/C][C]0.478495[/C][C]0.459583[/C][C]0.018912[/C][C]0.0115046[/C][/ROW]
[ROW][C]11[/C][C]0.49[/C][C]0.477662[/C][C]0.45875[/C][C]0.018912[/C][C]0.012338[/C][/ROW]
[ROW][C]12[/C][C]0.46[/C][C]0.473565[/C][C]0.457917[/C][C]0.0156481[/C][C]-0.0135648[/C][/ROW]
[ROW][C]13[/C][C]0.45[/C][C]0.45794[/C][C]0.4575[/C][C]0.000439815[/C][C]-0.00793981[/C][/ROW]
[ROW][C]14[/C][C]0.44[/C][C]0.454051[/C][C]0.4575[/C][C]-0.00344907[/C][C]-0.0140509[/C][/ROW]
[ROW][C]15[/C][C]0.42[/C][C]0.426759[/C][C]0.4575[/C][C]-0.0307407[/C][C]-0.00675926[/C][/ROW]
[ROW][C]16[/C][C]0.43[/C][C]0.427454[/C][C]0.457083[/C][C]-0.0296296[/C][C]0.0025463[/C][/ROW]
[ROW][C]17[/C][C]0.43[/C][C]0.431204[/C][C]0.45625[/C][C]-0.0250463[/C][C]-0.0012037[/C][/ROW]
[ROW][C]18[/C][C]0.47[/C][C]0.459329[/C][C]0.456667[/C][C]0.00266204[/C][C]0.0106713[/C][/ROW]
[ROW][C]19[/C][C]0.47[/C][C]0.467731[/C][C]0.459167[/C][C]0.00856481[/C][C]0.00226852[/C][/ROW]
[ROW][C]20[/C][C]0.47[/C][C]0.47419[/C][C]0.462917[/C][C]0.0112731[/C][C]-0.00418981[/C][/ROW]
[ROW][C]21[/C][C]0.47[/C][C]0.479537[/C][C]0.467083[/C][C]0.0124537[/C][C]-0.00953704[/C][/ROW]
[ROW][C]22[/C][C]0.48[/C][C]0.490995[/C][C]0.472083[/C][C]0.018912[/C][C]-0.0109954[/C][/ROW]
[ROW][C]23[/C][C]0.48[/C][C]0.497245[/C][C]0.478333[/C][C]0.018912[/C][C]-0.0172454[/C][/ROW]
[ROW][C]24[/C][C]0.48[/C][C]0.498565[/C][C]0.482917[/C][C]0.0156481[/C][C]-0.0185648[/C][/ROW]
[ROW][C]25[/C][C]0.49[/C][C]0.48544[/C][C]0.485[/C][C]0.000439815[/C][C]0.00456019[/C][/ROW]
[ROW][C]26[/C][C]0.49[/C][C]0.483634[/C][C]0.487083[/C][C]-0.00344907[/C][C]0.00636574[/C][/ROW]
[ROW][C]27[/C][C]0.47[/C][C]0.459259[/C][C]0.49[/C][C]-0.0307407[/C][C]0.0107407[/C][/ROW]
[ROW][C]28[/C][C]0.5[/C][C]0.463287[/C][C]0.492917[/C][C]-0.0296296[/C][C]0.036713[/C][/ROW]
[ROW][C]29[/C][C]0.51[/C][C]0.469954[/C][C]0.495[/C][C]-0.0250463[/C][C]0.0400463[/C][/ROW]
[ROW][C]30[/C][C]0.5[/C][C]0.500579[/C][C]0.497917[/C][C]0.00266204[/C][C]-0.000578704[/C][/ROW]
[ROW][C]31[/C][C]0.49[/C][C]0.508981[/C][C]0.500417[/C][C]0.00856481[/C][C]-0.0189815[/C][/ROW]
[ROW][C]32[/C][C]0.5[/C][C]0.512106[/C][C]0.500833[/C][C]0.0112731[/C][C]-0.0121065[/C][/ROW]
[ROW][C]33[/C][C]0.51[/C][C]0.51287[/C][C]0.500417[/C][C]0.0124537[/C][C]-0.00287037[/C][/ROW]
[ROW][C]34[/C][C]0.51[/C][C]0.517245[/C][C]0.498333[/C][C]0.018912[/C][C]-0.00724537[/C][/ROW]
[ROW][C]35[/C][C]0.5[/C][C]0.513912[/C][C]0.495[/C][C]0.018912[/C][C]-0.013912[/C][/ROW]
[ROW][C]36[/C][C]0.53[/C][C]0.508565[/C][C]0.492917[/C][C]0.0156481[/C][C]0.0214352[/C][/ROW]
[ROW][C]37[/C][C]0.5[/C][C]0.493356[/C][C]0.492917[/C][C]0.000439815[/C][C]0.00664352[/C][/ROW]
[ROW][C]38[/C][C]0.49[/C][C]0.489884[/C][C]0.493333[/C][C]-0.00344907[/C][C]0.000115741[/C][/ROW]
[ROW][C]39[/C][C]0.46[/C][C]0.462593[/C][C]0.493333[/C][C]-0.0307407[/C][C]-0.00259259[/C][/ROW]
[ROW][C]40[/C][C]0.46[/C][C]0.463287[/C][C]0.492917[/C][C]-0.0296296[/C][C]-0.00328704[/C][/ROW]
[ROW][C]41[/C][C]0.47[/C][C]0.468287[/C][C]0.493333[/C][C]-0.0250463[/C][C]0.00171296[/C][/ROW]
[ROW][C]42[/C][C]0.49[/C][C]0.495579[/C][C]0.492917[/C][C]0.00266204[/C][C]-0.0055787[/C][/ROW]
[ROW][C]43[/C][C]0.5[/C][C]0.499398[/C][C]0.490833[/C][C]0.00856481[/C][C]0.000601852[/C][/ROW]
[ROW][C]44[/C][C]0.5[/C][C]0.50044[/C][C]0.489167[/C][C]0.0112731[/C][C]-0.000439815[/C][/ROW]
[ROW][C]45[/C][C]0.51[/C][C]0.499537[/C][C]0.487083[/C][C]0.0124537[/C][C]0.010463[/C][/ROW]
[ROW][C]46[/C][C]0.5[/C][C]0.503079[/C][C]0.484167[/C][C]0.018912[/C][C]-0.0030787[/C][/ROW]
[ROW][C]47[/C][C]0.52[/C][C]0.500579[/C][C]0.481667[/C][C]0.018912[/C][C]0.0194213[/C][/ROW]
[ROW][C]48[/C][C]0.5[/C][C]0.496898[/C][C]0.48125[/C][C]0.0156481[/C][C]0.00310185[/C][/ROW]
[ROW][C]49[/C][C]0.48[/C][C]0.48294[/C][C]0.4825[/C][C]0.000439815[/C][C]-0.00293981[/C][/ROW]
[ROW][C]50[/C][C]0.47[/C][C]0.480718[/C][C]0.484167[/C][C]-0.00344907[/C][C]-0.0107176[/C][/ROW]
[ROW][C]51[/C][C]0.43[/C][C]0.454259[/C][C]0.485[/C][C]-0.0307407[/C][C]-0.0242593[/C][/ROW]
[ROW][C]52[/C][C]0.42[/C][C]0.456204[/C][C]0.485833[/C][C]-0.0296296[/C][C]-0.0362037[/C][/ROW]
[ROW][C]53[/C][C]0.45[/C][C]0.46162[/C][C]0.486667[/C][C]-0.0250463[/C][C]-0.0116204[/C][/ROW]
[ROW][C]54[/C][C]0.5[/C][C]0.489745[/C][C]0.487083[/C][C]0.00266204[/C][C]0.0102546[/C][/ROW]
[ROW][C]55[/C][C]0.52[/C][C]0.497315[/C][C]0.48875[/C][C]0.00856481[/C][C]0.0226852[/C][/ROW]
[ROW][C]56[/C][C]0.52[/C][C]0.50294[/C][C]0.491667[/C][C]0.0112731[/C][C]0.0170602[/C][/ROW]
[ROW][C]57[/C][C]0.51[/C][C]0.50787[/C][C]0.495417[/C][C]0.0124537[/C][C]0.00212963[/C][/ROW]
[ROW][C]58[/C][C]0.52[/C][C]0.519329[/C][C]0.500417[/C][C]0.018912[/C][C]0.000671296[/C][/ROW]
[ROW][C]59[/C][C]0.52[/C][C]0.523079[/C][C]0.504167[/C][C]0.018912[/C][C]-0.0030787[/C][/ROW]
[ROW][C]60[/C][C]0.51[/C][C]0.521065[/C][C]0.505417[/C][C]0.0156481[/C][C]-0.0110648[/C][/ROW]
[ROW][C]61[/C][C]0.51[/C][C]0.50544[/C][C]0.505[/C][C]0.000439815[/C][C]0.00456019[/C][/ROW]
[ROW][C]62[/C][C]0.51[/C][C]0.500301[/C][C]0.50375[/C][C]-0.00344907[/C][C]0.00969907[/C][/ROW]
[ROW][C]63[/C][C]0.48[/C][C]0.472593[/C][C]0.503333[/C][C]-0.0307407[/C][C]0.00740741[/C][/ROW]
[ROW][C]64[/C][C]0.49[/C][C]0.473704[/C][C]0.503333[/C][C]-0.0296296[/C][C]0.0162963[/C][/ROW]
[ROW][C]65[/C][C]0.47[/C][C]0.47787[/C][C]0.502917[/C][C]-0.0250463[/C][C]-0.00787037[/C][/ROW]
[ROW][C]66[/C][C]0.51[/C][C]0.505579[/C][C]0.502917[/C][C]0.00266204[/C][C]0.0044213[/C][/ROW]
[ROW][C]67[/C][C]0.5[/C][C]0.510648[/C][C]0.502083[/C][C]0.00856481[/C][C]-0.0106481[/C][/ROW]
[ROW][C]68[/C][C]0.51[/C][C]0.511273[/C][C]0.5[/C][C]0.0112731[/C][C]-0.00127315[/C][/ROW]
[ROW][C]69[/C][C]0.51[/C][C]0.511204[/C][C]0.49875[/C][C]0.0124537[/C][C]-0.0012037[/C][/ROW]
[ROW][C]70[/C][C]0.52[/C][C]0.515162[/C][C]0.49625[/C][C]0.018912[/C][C]0.00483796[/C][/ROW]
[ROW][C]71[/C][C]0.51[/C][C]0.511829[/C][C]0.492917[/C][C]0.018912[/C][C]-0.0018287[/C][/ROW]
[ROW][C]72[/C][C]0.52[/C][C]0.505648[/C][C]0.49[/C][C]0.0156481[/C][C]0.0143519[/C][/ROW]
[ROW][C]73[/C][C]0.48[/C][C]0.48919[/C][C]0.48875[/C][C]0.000439815[/C][C]-0.00918981[/C][/ROW]
[ROW][C]74[/C][C]0.49[/C][C]0.485718[/C][C]0.489167[/C][C]-0.00344907[/C][C]0.00428241[/C][/ROW]
[ROW][C]75[/C][C]0.47[/C][C]0.458843[/C][C]0.489583[/C][C]-0.0307407[/C][C]0.0111574[/C][/ROW]
[ROW][C]76[/C][C]0.44[/C][C]0.46037[/C][C]0.49[/C][C]-0.0296296[/C][C]-0.0203704[/C][/ROW]
[ROW][C]77[/C][C]0.44[/C][C]0.46537[/C][C]0.490417[/C][C]-0.0250463[/C][C]-0.0253704[/C][/ROW]
[ROW][C]78[/C][C]0.47[/C][C]0.493495[/C][C]0.490833[/C][C]0.00266204[/C][C]-0.0234954[/C][/ROW]
[ROW][C]79[/C][C]0.51[/C][C]NA[/C][C]NA[/C][C]0.00856481[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]0.51[/C][C]NA[/C][C]NA[/C][C]0.0112731[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]0.52[/C][C]NA[/C][C]NA[/C][C]0.0124537[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]0.52[/C][C]NA[/C][C]NA[/C][C]0.018912[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]0.52[/C][C]NA[/C][C]NA[/C][C]0.018912[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]0.52[/C][C]NA[/C][C]NA[/C][C]0.0156481[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232580&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232580&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
10.43NANA0.000439815NA
20.45NANA-0.00344907NA
30.44NANA-0.0307407NA
40.44NANA-0.0296296NA
50.44NANA-0.0250463NA
60.48NANA0.00266204NA
70.470.4702310.4616670.00856481-0.000231481
80.470.4733560.4620830.0112731-0.00335648
90.470.4732870.4608330.0124537-0.00328704
100.490.4784950.4595830.0189120.0115046
110.490.4776620.458750.0189120.012338
120.460.4735650.4579170.0156481-0.0135648
130.450.457940.45750.000439815-0.00793981
140.440.4540510.4575-0.00344907-0.0140509
150.420.4267590.4575-0.0307407-0.00675926
160.430.4274540.457083-0.02962960.0025463
170.430.4312040.45625-0.0250463-0.0012037
180.470.4593290.4566670.002662040.0106713
190.470.4677310.4591670.008564810.00226852
200.470.474190.4629170.0112731-0.00418981
210.470.4795370.4670830.0124537-0.00953704
220.480.4909950.4720830.018912-0.0109954
230.480.4972450.4783330.018912-0.0172454
240.480.4985650.4829170.0156481-0.0185648
250.490.485440.4850.0004398150.00456019
260.490.4836340.487083-0.003449070.00636574
270.470.4592590.49-0.03074070.0107407
280.50.4632870.492917-0.02962960.036713
290.510.4699540.495-0.02504630.0400463
300.50.5005790.4979170.00266204-0.000578704
310.490.5089810.5004170.00856481-0.0189815
320.50.5121060.5008330.0112731-0.0121065
330.510.512870.5004170.0124537-0.00287037
340.510.5172450.4983330.018912-0.00724537
350.50.5139120.4950.018912-0.013912
360.530.5085650.4929170.01564810.0214352
370.50.4933560.4929170.0004398150.00664352
380.490.4898840.493333-0.003449070.000115741
390.460.4625930.493333-0.0307407-0.00259259
400.460.4632870.492917-0.0296296-0.00328704
410.470.4682870.493333-0.02504630.00171296
420.490.4955790.4929170.00266204-0.0055787
430.50.4993980.4908330.008564810.000601852
440.50.500440.4891670.0112731-0.000439815
450.510.4995370.4870830.01245370.010463
460.50.5030790.4841670.018912-0.0030787
470.520.5005790.4816670.0189120.0194213
480.50.4968980.481250.01564810.00310185
490.480.482940.48250.000439815-0.00293981
500.470.4807180.484167-0.00344907-0.0107176
510.430.4542590.485-0.0307407-0.0242593
520.420.4562040.485833-0.0296296-0.0362037
530.450.461620.486667-0.0250463-0.0116204
540.50.4897450.4870830.002662040.0102546
550.520.4973150.488750.008564810.0226852
560.520.502940.4916670.01127310.0170602
570.510.507870.4954170.01245370.00212963
580.520.5193290.5004170.0189120.000671296
590.520.5230790.5041670.018912-0.0030787
600.510.5210650.5054170.0156481-0.0110648
610.510.505440.5050.0004398150.00456019
620.510.5003010.50375-0.003449070.00969907
630.480.4725930.503333-0.03074070.00740741
640.490.4737040.503333-0.02962960.0162963
650.470.477870.502917-0.0250463-0.00787037
660.510.5055790.5029170.002662040.0044213
670.50.5106480.5020830.00856481-0.0106481
680.510.5112730.50.0112731-0.00127315
690.510.5112040.498750.0124537-0.0012037
700.520.5151620.496250.0189120.00483796
710.510.5118290.4929170.018912-0.0018287
720.520.5056480.490.01564810.0143519
730.480.489190.488750.000439815-0.00918981
740.490.4857180.489167-0.003449070.00428241
750.470.4588430.489583-0.03074070.0111574
760.440.460370.49-0.0296296-0.0203704
770.440.465370.490417-0.0250463-0.0253704
780.470.4934950.4908330.00266204-0.0234954
790.51NANA0.00856481NA
800.51NANA0.0112731NA
810.52NANA0.0124537NA
820.52NANA0.018912NA
830.52NANA0.018912NA
840.52NANA0.0156481NA



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')