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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 19 Dec 2010 15:16:53 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t12927717467uek8mf6vbrxn59.htm/, Retrieved Sun, 05 May 2024 04:52:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112485, Retrieved Sun, 05 May 2024 04:52:51 +0000

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109

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-  MPD  [Classical Decomposition] [] [2010-11-27 15:01:19] [39e83c7b0ac936e906a817a1bb402750]
-   PD      [Classical Decomposition] [] [2010-12-19 15:16:53] [558c060a42ec367ec2c020fab85c25c7] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112485&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112485&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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	0.3415	NA	NA	-0.0547102430555556	NA
2	0.3554	NA	NA	-0.0480581597222223	NA
3	0.4035	NA	NA	-0.0296592013888889	NA
4	0.435	NA	NA	-0.000607118055555573	NA
5	0.4105	NA	NA	0.0201553819444444	NA
6	0.4559	NA	NA	0.0420762152777778	NA
7	0.4755	0.500062673611111	0.449829166666667	0.0502335069444445	-0.0245626736111111
8	0.4918	0.491686631944445	0.459983333333333	0.0317032986111112	0.000113368055555507
9	0.5175	0.492266840277778	0.4681125	0.0241543402777778	0.0252331597222222
10	0.5191	0.486279340277778	0.475233333333333	0.0110460069444444	0.0328206597222223
11	0.4754	0.477877256944444	0.4835125	-0.0056352430555555	-0.00247725694444445
12	0.4531	0.449722048611111	0.490420833333333	-0.0406987847222222	0.00337795138888891
13	0.469	0.440214756944444	0.494925	-0.0547102430555556	0.0287852430555556
14	0.4716	0.450500173611111	0.498558333333333	-0.0480581597222223	0.0210998263888890
15	0.4824	0.469078298611111	0.4987375	-0.0296592013888889	0.0133217013888889
16	0.527	0.494517881944444	0.495125	-0.000607118055555573	0.0324821180555556
17	0.5172	0.512405381944444	0.49225	0.0201553819444444	0.00479461805555559
18	0.515	0.533742881944444	0.491666666666667	0.0420762152777778	-0.0187428819444443
19	0.5245	0.540021006944444	0.4897875	0.0502335069444445	-0.0155210069444445
20	0.53	0.518061631944445	0.486358333333333	0.0317032986111112	0.0119383680555555
21	0.4836	0.507837673611111	0.483683333333333	0.0241543402777778	-0.0242376736111111
22	0.4663	0.491316840277778	0.480270833333333	0.0110460069444444	-0.0250168402777778
23	0.4592	0.470789756944445	0.476425	-0.0056352430555555	-0.0115897569444445
24	0.4553	0.433238715277778	0.4739375	-0.0406987847222222	0.0220612847222222
25	0.4217	0.417656423611111	0.472366666666667	-0.0547102430555556	0.00404357638888897
26	0.4366	0.422241840277778	0.4703	-0.0480581597222223	0.0143581597222222
27	0.4532	0.440878298611111	0.4705375	-0.0296592013888889	0.0123217013888889
28	0.4743	0.474547048611111	0.475154166666667	-0.000607118055555573	-0.000247048611111078
29	0.4776	0.504534548611111	0.484379166666667	0.0201553819444444	-0.0269345486111111
30	0.4949	0.538326215277778	0.49625	0.0420762152777778	-0.0434262152777777
31	0.5069	0.558596006944444	0.5083625	0.0502335069444445	-0.0516960069444444
32	0.498	0.552944965277778	0.521241666666667	0.0317032986111112	-0.0549449652777778
33	0.5213	0.559946006944444	0.535791666666667	0.0241543402777778	-0.0386460069444445
34	0.5394	0.563100173611111	0.552054166666667	0.0110460069444444	-0.0237001736111111
35	0.6075	0.566160590277778	0.571795833333333	-0.0056352430555555	0.0413394097222224
36	0.5919	0.554926215277778	0.595625	-0.0406987847222222	0.0369737847222223
37	0.5758	0.564718923611111	0.619429166666667	-0.0547102430555556	0.0110810763888888
38	0.5916	0.591362673611111	0.639420833333333	-0.0480581597222223	0.000237326388888848
39	0.6474	0.624319965277778	0.653979166666667	-0.0296592013888889	0.0230800347222222
40	0.6704	0.662434548611111	0.663041666666667	-0.000607118055555573	0.00796545138888882
41	0.7553	0.682659548611111	0.662504166666667	0.0201553819444444	0.0726404513888889
42	0.7891	0.694084548611111	0.652008333333333	0.0420762152777778	0.0950154513888888
43	0.784	0.687837673611111	0.637604166666667	0.0502335069444445	0.0961623263888889
44	0.7007	0.653424131944444	0.621720833333333	0.0317032986111112	0.0472758680555556
45	0.668	0.625966840277778	0.6018125	0.0241543402777778	0.0420331597222223
46	0.6102	0.589921006944444	0.578875	0.0110460069444444	0.0202789930555555
47	0.5238	0.546689756944444	0.552325	-0.0056352430555555	-0.0228897569444444
48	0.4237	0.481730381944445	0.522429166666667	-0.0406987847222222	-0.0580303819444445
49	0.3983	0.437827256944444	0.4925375	-0.0547102430555556	-0.0395272569444445
50	0.3879	0.419212673611111	0.467270833333333	-0.0480581597222223	-0.031312673611111
51	0.3733	0.417640798611111	0.4473	-0.0296592013888889	-0.0443407986111111
52	0.394	0.429817881944444	0.430425	-0.000607118055555573	-0.0358178819444444
53	0.3945	0.440617881944444	0.4204625	0.0201553819444444	-0.0461178819444444
54	0.4324	0.460863715277778	0.4187875	0.0420762152777778	-0.0284637152777777
55	0.4233	NA	NA	0.0502335069444445	NA
56	0.455	NA	NA	0.0317032986111112	NA
57	0.4344	NA	NA	0.0241543402777778	NA
58	0.4388	NA	NA	0.0110460069444444	NA
59	0.4561	NA	NA	-0.0056352430555555	NA
60	0.4512	NA	NA	-0.0406987847222222	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.3415 & NA & NA & -0.0547102430555556 & NA \tabularnewline
2 & 0.3554 & NA & NA & -0.0480581597222223 & NA \tabularnewline
3 & 0.4035 & NA & NA & -0.0296592013888889 & NA \tabularnewline
4 & 0.435 & NA & NA & -0.000607118055555573 & NA \tabularnewline
5 & 0.4105 & NA & NA & 0.0201553819444444 & NA \tabularnewline
6 & 0.4559 & NA & NA & 0.0420762152777778 & NA \tabularnewline
7 & 0.4755 & 0.500062673611111 & 0.449829166666667 & 0.0502335069444445 & -0.0245626736111111 \tabularnewline
8 & 0.4918 & 0.491686631944445 & 0.459983333333333 & 0.0317032986111112 & 0.000113368055555507 \tabularnewline
9 & 0.5175 & 0.492266840277778 & 0.4681125 & 0.0241543402777778 & 0.0252331597222222 \tabularnewline
10 & 0.5191 & 0.486279340277778 & 0.475233333333333 & 0.0110460069444444 & 0.0328206597222223 \tabularnewline
11 & 0.4754 & 0.477877256944444 & 0.4835125 & -0.0056352430555555 & -0.00247725694444445 \tabularnewline
12 & 0.4531 & 0.449722048611111 & 0.490420833333333 & -0.0406987847222222 & 0.00337795138888891 \tabularnewline
13 & 0.469 & 0.440214756944444 & 0.494925 & -0.0547102430555556 & 0.0287852430555556 \tabularnewline
14 & 0.4716 & 0.450500173611111 & 0.498558333333333 & -0.0480581597222223 & 0.0210998263888890 \tabularnewline
15 & 0.4824 & 0.469078298611111 & 0.4987375 & -0.0296592013888889 & 0.0133217013888889 \tabularnewline
16 & 0.527 & 0.494517881944444 & 0.495125 & -0.000607118055555573 & 0.0324821180555556 \tabularnewline
17 & 0.5172 & 0.512405381944444 & 0.49225 & 0.0201553819444444 & 0.00479461805555559 \tabularnewline
18 & 0.515 & 0.533742881944444 & 0.491666666666667 & 0.0420762152777778 & -0.0187428819444443 \tabularnewline
19 & 0.5245 & 0.540021006944444 & 0.4897875 & 0.0502335069444445 & -0.0155210069444445 \tabularnewline
20 & 0.53 & 0.518061631944445 & 0.486358333333333 & 0.0317032986111112 & 0.0119383680555555 \tabularnewline
21 & 0.4836 & 0.507837673611111 & 0.483683333333333 & 0.0241543402777778 & -0.0242376736111111 \tabularnewline
22 & 0.4663 & 0.491316840277778 & 0.480270833333333 & 0.0110460069444444 & -0.0250168402777778 \tabularnewline
23 & 0.4592 & 0.470789756944445 & 0.476425 & -0.0056352430555555 & -0.0115897569444445 \tabularnewline
24 & 0.4553 & 0.433238715277778 & 0.4739375 & -0.0406987847222222 & 0.0220612847222222 \tabularnewline
25 & 0.4217 & 0.417656423611111 & 0.472366666666667 & -0.0547102430555556 & 0.00404357638888897 \tabularnewline
26 & 0.4366 & 0.422241840277778 & 0.4703 & -0.0480581597222223 & 0.0143581597222222 \tabularnewline
27 & 0.4532 & 0.440878298611111 & 0.4705375 & -0.0296592013888889 & 0.0123217013888889 \tabularnewline
28 & 0.4743 & 0.474547048611111 & 0.475154166666667 & -0.000607118055555573 & -0.000247048611111078 \tabularnewline
29 & 0.4776 & 0.504534548611111 & 0.484379166666667 & 0.0201553819444444 & -0.0269345486111111 \tabularnewline
30 & 0.4949 & 0.538326215277778 & 0.49625 & 0.0420762152777778 & -0.0434262152777777 \tabularnewline
31 & 0.5069 & 0.558596006944444 & 0.5083625 & 0.0502335069444445 & -0.0516960069444444 \tabularnewline
32 & 0.498 & 0.552944965277778 & 0.521241666666667 & 0.0317032986111112 & -0.0549449652777778 \tabularnewline
33 & 0.5213 & 0.559946006944444 & 0.535791666666667 & 0.0241543402777778 & -0.0386460069444445 \tabularnewline
34 & 0.5394 & 0.563100173611111 & 0.552054166666667 & 0.0110460069444444 & -0.0237001736111111 \tabularnewline
35 & 0.6075 & 0.566160590277778 & 0.571795833333333 & -0.0056352430555555 & 0.0413394097222224 \tabularnewline
36 & 0.5919 & 0.554926215277778 & 0.595625 & -0.0406987847222222 & 0.0369737847222223 \tabularnewline
37 & 0.5758 & 0.564718923611111 & 0.619429166666667 & -0.0547102430555556 & 0.0110810763888888 \tabularnewline
38 & 0.5916 & 0.591362673611111 & 0.639420833333333 & -0.0480581597222223 & 0.000237326388888848 \tabularnewline
39 & 0.6474 & 0.624319965277778 & 0.653979166666667 & -0.0296592013888889 & 0.0230800347222222 \tabularnewline
40 & 0.6704 & 0.662434548611111 & 0.663041666666667 & -0.000607118055555573 & 0.00796545138888882 \tabularnewline
41 & 0.7553 & 0.682659548611111 & 0.662504166666667 & 0.0201553819444444 & 0.0726404513888889 \tabularnewline
42 & 0.7891 & 0.694084548611111 & 0.652008333333333 & 0.0420762152777778 & 0.0950154513888888 \tabularnewline
43 & 0.784 & 0.687837673611111 & 0.637604166666667 & 0.0502335069444445 & 0.0961623263888889 \tabularnewline
44 & 0.7007 & 0.653424131944444 & 0.621720833333333 & 0.0317032986111112 & 0.0472758680555556 \tabularnewline
45 & 0.668 & 0.625966840277778 & 0.6018125 & 0.0241543402777778 & 0.0420331597222223 \tabularnewline
46 & 0.6102 & 0.589921006944444 & 0.578875 & 0.0110460069444444 & 0.0202789930555555 \tabularnewline
47 & 0.5238 & 0.546689756944444 & 0.552325 & -0.0056352430555555 & -0.0228897569444444 \tabularnewline
48 & 0.4237 & 0.481730381944445 & 0.522429166666667 & -0.0406987847222222 & -0.0580303819444445 \tabularnewline
49 & 0.3983 & 0.437827256944444 & 0.4925375 & -0.0547102430555556 & -0.0395272569444445 \tabularnewline
50 & 0.3879 & 0.419212673611111 & 0.467270833333333 & -0.0480581597222223 & -0.031312673611111 \tabularnewline
51 & 0.3733 & 0.417640798611111 & 0.4473 & -0.0296592013888889 & -0.0443407986111111 \tabularnewline
52 & 0.394 & 0.429817881944444 & 0.430425 & -0.000607118055555573 & -0.0358178819444444 \tabularnewline
53 & 0.3945 & 0.440617881944444 & 0.4204625 & 0.0201553819444444 & -0.0461178819444444 \tabularnewline
54 & 0.4324 & 0.460863715277778 & 0.4187875 & 0.0420762152777778 & -0.0284637152777777 \tabularnewline
55 & 0.4233 & NA & NA & 0.0502335069444445 & NA \tabularnewline
56 & 0.455 & NA & NA & 0.0317032986111112 & NA \tabularnewline
57 & 0.4344 & NA & NA & 0.0241543402777778 & NA \tabularnewline
58 & 0.4388 & NA & NA & 0.0110460069444444 & NA \tabularnewline
59 & 0.4561 & NA & NA & -0.0056352430555555 & NA \tabularnewline
60 & 0.4512 & NA & NA & -0.0406987847222222 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112485&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]0.3415[/C][C]NA[/C][C]NA[/C][C]-0.0547102430555556[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.3554[/C][C]NA[/C][C]NA[/C][C]-0.0480581597222223[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.4035[/C][C]NA[/C][C]NA[/C][C]-0.0296592013888889[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.435[/C][C]NA[/C][C]NA[/C][C]-0.000607118055555573[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.4105[/C][C]NA[/C][C]NA[/C][C]0.0201553819444444[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.4559[/C][C]NA[/C][C]NA[/C][C]0.0420762152777778[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.4755[/C][C]0.500062673611111[/C][C]0.449829166666667[/C][C]0.0502335069444445[/C][C]-0.0245626736111111[/C][/ROW]
[ROW][C]8[/C][C]0.4918[/C][C]0.491686631944445[/C][C]0.459983333333333[/C][C]0.0317032986111112[/C][C]0.000113368055555507[/C][/ROW]
[ROW][C]9[/C][C]0.5175[/C][C]0.492266840277778[/C][C]0.4681125[/C][C]0.0241543402777778[/C][C]0.0252331597222222[/C][/ROW]
[ROW][C]10[/C][C]0.5191[/C][C]0.486279340277778[/C][C]0.475233333333333[/C][C]0.0110460069444444[/C][C]0.0328206597222223[/C][/ROW]
[ROW][C]11[/C][C]0.4754[/C][C]0.477877256944444[/C][C]0.4835125[/C][C]-0.0056352430555555[/C][C]-0.00247725694444445[/C][/ROW]
[ROW][C]12[/C][C]0.4531[/C][C]0.449722048611111[/C][C]0.490420833333333[/C][C]-0.0406987847222222[/C][C]0.00337795138888891[/C][/ROW]
[ROW][C]13[/C][C]0.469[/C][C]0.440214756944444[/C][C]0.494925[/C][C]-0.0547102430555556[/C][C]0.0287852430555556[/C][/ROW]
[ROW][C]14[/C][C]0.4716[/C][C]0.450500173611111[/C][C]0.498558333333333[/C][C]-0.0480581597222223[/C][C]0.0210998263888890[/C][/ROW]
[ROW][C]15[/C][C]0.4824[/C][C]0.469078298611111[/C][C]0.4987375[/C][C]-0.0296592013888889[/C][C]0.0133217013888889[/C][/ROW]
[ROW][C]16[/C][C]0.527[/C][C]0.494517881944444[/C][C]0.495125[/C][C]-0.000607118055555573[/C][C]0.0324821180555556[/C][/ROW]
[ROW][C]17[/C][C]0.5172[/C][C]0.512405381944444[/C][C]0.49225[/C][C]0.0201553819444444[/C][C]0.00479461805555559[/C][/ROW]
[ROW][C]18[/C][C]0.515[/C][C]0.533742881944444[/C][C]0.491666666666667[/C][C]0.0420762152777778[/C][C]-0.0187428819444443[/C][/ROW]
[ROW][C]19[/C][C]0.5245[/C][C]0.540021006944444[/C][C]0.4897875[/C][C]0.0502335069444445[/C][C]-0.0155210069444445[/C][/ROW]
[ROW][C]20[/C][C]0.53[/C][C]0.518061631944445[/C][C]0.486358333333333[/C][C]0.0317032986111112[/C][C]0.0119383680555555[/C][/ROW]
[ROW][C]21[/C][C]0.4836[/C][C]0.507837673611111[/C][C]0.483683333333333[/C][C]0.0241543402777778[/C][C]-0.0242376736111111[/C][/ROW]
[ROW][C]22[/C][C]0.4663[/C][C]0.491316840277778[/C][C]0.480270833333333[/C][C]0.0110460069444444[/C][C]-0.0250168402777778[/C][/ROW]
[ROW][C]23[/C][C]0.4592[/C][C]0.470789756944445[/C][C]0.476425[/C][C]-0.0056352430555555[/C][C]-0.0115897569444445[/C][/ROW]
[ROW][C]24[/C][C]0.4553[/C][C]0.433238715277778[/C][C]0.4739375[/C][C]-0.0406987847222222[/C][C]0.0220612847222222[/C][/ROW]
[ROW][C]25[/C][C]0.4217[/C][C]0.417656423611111[/C][C]0.472366666666667[/C][C]-0.0547102430555556[/C][C]0.00404357638888897[/C][/ROW]
[ROW][C]26[/C][C]0.4366[/C][C]0.422241840277778[/C][C]0.4703[/C][C]-0.0480581597222223[/C][C]0.0143581597222222[/C][/ROW]
[ROW][C]27[/C][C]0.4532[/C][C]0.440878298611111[/C][C]0.4705375[/C][C]-0.0296592013888889[/C][C]0.0123217013888889[/C][/ROW]
[ROW][C]28[/C][C]0.4743[/C][C]0.474547048611111[/C][C]0.475154166666667[/C][C]-0.000607118055555573[/C][C]-0.000247048611111078[/C][/ROW]
[ROW][C]29[/C][C]0.4776[/C][C]0.504534548611111[/C][C]0.484379166666667[/C][C]0.0201553819444444[/C][C]-0.0269345486111111[/C][/ROW]
[ROW][C]30[/C][C]0.4949[/C][C]0.538326215277778[/C][C]0.49625[/C][C]0.0420762152777778[/C][C]-0.0434262152777777[/C][/ROW]
[ROW][C]31[/C][C]0.5069[/C][C]0.558596006944444[/C][C]0.5083625[/C][C]0.0502335069444445[/C][C]-0.0516960069444444[/C][/ROW]
[ROW][C]32[/C][C]0.498[/C][C]0.552944965277778[/C][C]0.521241666666667[/C][C]0.0317032986111112[/C][C]-0.0549449652777778[/C][/ROW]
[ROW][C]33[/C][C]0.5213[/C][C]0.559946006944444[/C][C]0.535791666666667[/C][C]0.0241543402777778[/C][C]-0.0386460069444445[/C][/ROW]
[ROW][C]34[/C][C]0.5394[/C][C]0.563100173611111[/C][C]0.552054166666667[/C][C]0.0110460069444444[/C][C]-0.0237001736111111[/C][/ROW]
[ROW][C]35[/C][C]0.6075[/C][C]0.566160590277778[/C][C]0.571795833333333[/C][C]-0.0056352430555555[/C][C]0.0413394097222224[/C][/ROW]
[ROW][C]36[/C][C]0.5919[/C][C]0.554926215277778[/C][C]0.595625[/C][C]-0.0406987847222222[/C][C]0.0369737847222223[/C][/ROW]
[ROW][C]37[/C][C]0.5758[/C][C]0.564718923611111[/C][C]0.619429166666667[/C][C]-0.0547102430555556[/C][C]0.0110810763888888[/C][/ROW]
[ROW][C]38[/C][C]0.5916[/C][C]0.591362673611111[/C][C]0.639420833333333[/C][C]-0.0480581597222223[/C][C]0.000237326388888848[/C][/ROW]
[ROW][C]39[/C][C]0.6474[/C][C]0.624319965277778[/C][C]0.653979166666667[/C][C]-0.0296592013888889[/C][C]0.0230800347222222[/C][/ROW]
[ROW][C]40[/C][C]0.6704[/C][C]0.662434548611111[/C][C]0.663041666666667[/C][C]-0.000607118055555573[/C][C]0.00796545138888882[/C][/ROW]
[ROW][C]41[/C][C]0.7553[/C][C]0.682659548611111[/C][C]0.662504166666667[/C][C]0.0201553819444444[/C][C]0.0726404513888889[/C][/ROW]
[ROW][C]42[/C][C]0.7891[/C][C]0.694084548611111[/C][C]0.652008333333333[/C][C]0.0420762152777778[/C][C]0.0950154513888888[/C][/ROW]
[ROW][C]43[/C][C]0.784[/C][C]0.687837673611111[/C][C]0.637604166666667[/C][C]0.0502335069444445[/C][C]0.0961623263888889[/C][/ROW]
[ROW][C]44[/C][C]0.7007[/C][C]0.653424131944444[/C][C]0.621720833333333[/C][C]0.0317032986111112[/C][C]0.0472758680555556[/C][/ROW]
[ROW][C]45[/C][C]0.668[/C][C]0.625966840277778[/C][C]0.6018125[/C][C]0.0241543402777778[/C][C]0.0420331597222223[/C][/ROW]
[ROW][C]46[/C][C]0.6102[/C][C]0.589921006944444[/C][C]0.578875[/C][C]0.0110460069444444[/C][C]0.0202789930555555[/C][/ROW]
[ROW][C]47[/C][C]0.5238[/C][C]0.546689756944444[/C][C]0.552325[/C][C]-0.0056352430555555[/C][C]-0.0228897569444444[/C][/ROW]
[ROW][C]48[/C][C]0.4237[/C][C]0.481730381944445[/C][C]0.522429166666667[/C][C]-0.0406987847222222[/C][C]-0.0580303819444445[/C][/ROW]
[ROW][C]49[/C][C]0.3983[/C][C]0.437827256944444[/C][C]0.4925375[/C][C]-0.0547102430555556[/C][C]-0.0395272569444445[/C][/ROW]
[ROW][C]50[/C][C]0.3879[/C][C]0.419212673611111[/C][C]0.467270833333333[/C][C]-0.0480581597222223[/C][C]-0.031312673611111[/C][/ROW]
[ROW][C]51[/C][C]0.3733[/C][C]0.417640798611111[/C][C]0.4473[/C][C]-0.0296592013888889[/C][C]-0.0443407986111111[/C][/ROW]
[ROW][C]52[/C][C]0.394[/C][C]0.429817881944444[/C][C]0.430425[/C][C]-0.000607118055555573[/C][C]-0.0358178819444444[/C][/ROW]
[ROW][C]53[/C][C]0.3945[/C][C]0.440617881944444[/C][C]0.4204625[/C][C]0.0201553819444444[/C][C]-0.0461178819444444[/C][/ROW]
[ROW][C]54[/C][C]0.4324[/C][C]0.460863715277778[/C][C]0.4187875[/C][C]0.0420762152777778[/C][C]-0.0284637152777777[/C][/ROW]
[ROW][C]55[/C][C]0.4233[/C][C]NA[/C][C]NA[/C][C]0.0502335069444445[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]0.455[/C][C]NA[/C][C]NA[/C][C]0.0317032986111112[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]0.4344[/C][C]NA[/C][C]NA[/C][C]0.0241543402777778[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]0.4388[/C][C]NA[/C][C]NA[/C][C]0.0110460069444444[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]0.4561[/C][C]NA[/C][C]NA[/C][C]-0.0056352430555555[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]0.4512[/C][C]NA[/C][C]NA[/C][C]-0.0406987847222222[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112485&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	0.3415	NA	NA	-0.0547102430555556	NA
2	0.3554	NA	NA	-0.0480581597222223	NA
3	0.4035	NA	NA	-0.0296592013888889	NA
4	0.435	NA	NA	-0.000607118055555573	NA
5	0.4105	NA	NA	0.0201553819444444	NA
6	0.4559	NA	NA	0.0420762152777778	NA
7	0.4755	0.500062673611111	0.449829166666667	0.0502335069444445	-0.0245626736111111
8	0.4918	0.491686631944445	0.459983333333333	0.0317032986111112	0.000113368055555507
9	0.5175	0.492266840277778	0.4681125	0.0241543402777778	0.0252331597222222
10	0.5191	0.486279340277778	0.475233333333333	0.0110460069444444	0.0328206597222223
11	0.4754	0.477877256944444	0.4835125	-0.0056352430555555	-0.00247725694444445
12	0.4531	0.449722048611111	0.490420833333333	-0.0406987847222222	0.00337795138888891
13	0.469	0.440214756944444	0.494925	-0.0547102430555556	0.0287852430555556
14	0.4716	0.450500173611111	0.498558333333333	-0.0480581597222223	0.0210998263888890
15	0.4824	0.469078298611111	0.4987375	-0.0296592013888889	0.0133217013888889
16	0.527	0.494517881944444	0.495125	-0.000607118055555573	0.0324821180555556
17	0.5172	0.512405381944444	0.49225	0.0201553819444444	0.00479461805555559
18	0.515	0.533742881944444	0.491666666666667	0.0420762152777778	-0.0187428819444443
19	0.5245	0.540021006944444	0.4897875	0.0502335069444445	-0.0155210069444445
20	0.53	0.518061631944445	0.486358333333333	0.0317032986111112	0.0119383680555555
21	0.4836	0.507837673611111	0.483683333333333	0.0241543402777778	-0.0242376736111111
22	0.4663	0.491316840277778	0.480270833333333	0.0110460069444444	-0.0250168402777778
23	0.4592	0.470789756944445	0.476425	-0.0056352430555555	-0.0115897569444445
24	0.4553	0.433238715277778	0.4739375	-0.0406987847222222	0.0220612847222222
25	0.4217	0.417656423611111	0.472366666666667	-0.0547102430555556	0.00404357638888897
26	0.4366	0.422241840277778	0.4703	-0.0480581597222223	0.0143581597222222
27	0.4532	0.440878298611111	0.4705375	-0.0296592013888889	0.0123217013888889
28	0.4743	0.474547048611111	0.475154166666667	-0.000607118055555573	-0.000247048611111078
29	0.4776	0.504534548611111	0.484379166666667	0.0201553819444444	-0.0269345486111111
30	0.4949	0.538326215277778	0.49625	0.0420762152777778	-0.0434262152777777
31	0.5069	0.558596006944444	0.5083625	0.0502335069444445	-0.0516960069444444
32	0.498	0.552944965277778	0.521241666666667	0.0317032986111112	-0.0549449652777778
33	0.5213	0.559946006944444	0.535791666666667	0.0241543402777778	-0.0386460069444445
34	0.5394	0.563100173611111	0.552054166666667	0.0110460069444444	-0.0237001736111111
35	0.6075	0.566160590277778	0.571795833333333	-0.0056352430555555	0.0413394097222224
36	0.5919	0.554926215277778	0.595625	-0.0406987847222222	0.0369737847222223
37	0.5758	0.564718923611111	0.619429166666667	-0.0547102430555556	0.0110810763888888
38	0.5916	0.591362673611111	0.639420833333333	-0.0480581597222223	0.000237326388888848
39	0.6474	0.624319965277778	0.653979166666667	-0.0296592013888889	0.0230800347222222
40	0.6704	0.662434548611111	0.663041666666667	-0.000607118055555573	0.00796545138888882
41	0.7553	0.682659548611111	0.662504166666667	0.0201553819444444	0.0726404513888889
42	0.7891	0.694084548611111	0.652008333333333	0.0420762152777778	0.0950154513888888
43	0.784	0.687837673611111	0.637604166666667	0.0502335069444445	0.0961623263888889
44	0.7007	0.653424131944444	0.621720833333333	0.0317032986111112	0.0472758680555556
45	0.668	0.625966840277778	0.6018125	0.0241543402777778	0.0420331597222223
46	0.6102	0.589921006944444	0.578875	0.0110460069444444	0.0202789930555555
47	0.5238	0.546689756944444	0.552325	-0.0056352430555555	-0.0228897569444444
48	0.4237	0.481730381944445	0.522429166666667	-0.0406987847222222	-0.0580303819444445
49	0.3983	0.437827256944444	0.4925375	-0.0547102430555556	-0.0395272569444445
50	0.3879	0.419212673611111	0.467270833333333	-0.0480581597222223	-0.031312673611111
51	0.3733	0.417640798611111	0.4473	-0.0296592013888889	-0.0443407986111111
52	0.394	0.429817881944444	0.430425	-0.000607118055555573	-0.0358178819444444
53	0.3945	0.440617881944444	0.4204625	0.0201553819444444	-0.0461178819444444
54	0.4324	0.460863715277778	0.4187875	0.0420762152777778	-0.0284637152777777
55	0.4233	NA	NA	0.0502335069444445	NA
56	0.455	NA	NA	0.0317032986111112	NA
57	0.4344	NA	NA	0.0241543402777778	NA
58	0.4388	NA	NA	0.0110460069444444	NA
59	0.4561	NA	NA	-0.0056352430555555	NA
60	0.4512	NA	NA	-0.0406987847222222	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code