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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 01 May 2013 06:35:56 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/01/t1367404622oyezf3s16osdq0g.htm/, Retrieved Mon, 29 Apr 2024 14:42:06 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208631, Retrieved Mon, 29 Apr 2024 14:42:06 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

160

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [standard deviatio...] [2013-05-01 10:35:56] [32dc2c4b4a2dbace6e4aec9df691cbdd] [Current]

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Dataseries X:

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2,27
2,35
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,54
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,66
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
2,93
3,07
3,07
3,07
3,07
3,07
3,07
3,07
3,07
3,07
3,07

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' @ 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208631&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' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208631&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208631&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' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.27	NA	NA	-0.0464444444444444	NA
2	2.35	NA	NA	0.0227222222222223	NA
3	2.54	NA	NA	0.0418888888888889	NA
4	2.54	NA	NA	0.0330555555555555	NA
5	2.54	NA	NA	0.0242222222222222	NA
6	2.54	NA	NA	0.0153888888888888	NA
7	2.54	2.52138888888889	2.51291666666667	0.00847222222222213	0.0186111111111114
8	2.54	2.53022222222222	2.53208333333333	-0.00186111111111114	0.00977777777777833
9	2.54	2.52888888888889	2.54	-0.0111111111111111	0.0111111111111115
10	2.54	2.52005555555556	2.54	-0.0199444444444444	0.019944444444445
11	2.54	2.51122222222222	2.54	-0.0287777777777777	0.028777777777778
12	2.54	2.50238888888889	2.54	-0.037611111111111	0.0376111111111115
13	2.54	2.49355555555556	2.54	-0.0464444444444444	0.046444444444445
14	2.54	2.56272222222222	2.54	0.0227222222222223	-0.0227222222222219
15	2.54	2.58188888888889	2.54	0.0418888888888889	-0.0418888888888884
16	2.54	2.57305555555555	2.54	0.0330555555555555	-0.0330555555555549
17	2.54	2.56422222222222	2.54	0.0242222222222222	-0.0242222222222219
18	2.54	2.55538888888889	2.54	0.0153888888888888	-0.0153888888888885
19	2.54	2.54847222222222	2.54	0.00847222222222213	-0.00847222222222177
20	2.54	2.54313888888889	2.545	-0.00186111111111114	-0.00313888888888814
21	2.54	2.54388888888889	2.555	-0.0111111111111111	-0.00388888888888861
22	2.54	2.54505555555555	2.565	-0.0199444444444444	-0.00505555555555492
23	2.54	2.54622222222222	2.575	-0.0287777777777777	-0.00622222222222213
24	2.54	2.54738888888889	2.585	-0.037611111111111	-0.00738888888888845
25	2.54	2.54855555555556	2.595	-0.0464444444444444	-0.00855555555555521
26	2.66	2.62772222222222	2.605	0.0227222222222223	0.0322777777777783
27	2.66	2.65688888888889	2.615	0.0418888888888889	0.00311111111111151
28	2.66	2.65805555555555	2.625	0.0330555555555555	0.00194444444444519
29	2.66	2.65922222222222	2.635	0.0242222222222222	0.000777777777777988
30	2.66	2.66038888888889	2.645	0.0153888888888888	-0.000388888888888772
31	2.66	2.66347222222222	2.655	0.00847222222222213	-0.00347222222222232
32	2.66	2.65813888888889	2.66	-0.00186111111111114	0.00186111111111131
33	2.66	2.64888888888889	2.66	-0.0111111111111111	0.0111111111111111
34	2.66	2.64005555555556	2.66	-0.0199444444444444	0.0199444444444445
35	2.66	2.63122222222222	2.66	-0.0287777777777777	0.0287777777777776
36	2.66	2.62238888888889	2.66	-0.037611111111111	0.037611111111111
37	2.66	2.61355555555556	2.66	-0.0464444444444444	0.0464444444444445
38	2.66	2.68272222222222	2.66	0.0227222222222223	-0.0227222222222223
39	2.66	2.70188888888889	2.66	0.0418888888888889	-0.0418888888888889
40	2.66	2.69305555555556	2.66	0.0330555555555555	-0.0330555555555554
41	2.66	2.68422222222222	2.66	0.0242222222222222	-0.0242222222222224
42	2.66	2.67538888888889	2.66	0.0153888888888888	-0.0153888888888889
43	2.66	2.66847222222222	2.66	0.00847222222222213	-0.00847222222222221
44	2.66	2.66938888888889	2.67125	-0.00186111111111114	-0.00938888888888867
45	2.66	2.68263888888889	2.69375	-0.0111111111111111	-0.0226388888888889
46	2.66	2.69630555555556	2.71625	-0.0199444444444444	-0.0363055555555554
47	2.66	2.70997222222222	2.73875	-0.0287777777777777	-0.0499722222222223
48	2.66	2.72363888888889	2.76125	-0.037611111111111	-0.0636388888888888
49	2.66	2.73730555555556	2.78375	-0.0464444444444444	-0.0773055555555553
50	2.93	2.82897222222222	2.80625	0.0227222222222223	0.101027777777778
51	2.93	2.87063888888889	2.82875	0.0418888888888889	0.0593611111111114
52	2.93	2.88430555555556	2.85125	0.0330555555555555	0.0456944444444445
53	2.93	2.89797222222222	2.87375	0.0242222222222222	0.0320277777777775
54	2.93	2.91163888888889	2.89625	0.0153888888888888	0.0183611111111111
55	2.93	2.92722222222222	2.91875	0.00847222222222213	0.00277777777777777
56	2.93	2.92813888888889	2.93	-0.00186111111111114	0.00186111111111131
57	2.93	2.92472222222222	2.93583333333333	-0.0111111111111111	0.00527777777777816
58	2.93	2.92755555555556	2.9475	-0.0199444444444444	0.00244444444444492
59	2.93	2.93038888888889	2.95916666666667	-0.0287777777777777	-0.000388888888888772
60	2.93	2.93322222222222	2.97083333333333	-0.037611111111111	-0.00322222222222202
61	2.93	2.93605555555556	2.9825	-0.0464444444444444	-0.00605555555555526
62	2.93	3.01688888888889	2.99416666666667	0.0227222222222223	-0.0868888888888888
63	3.07	3.04772222222222	3.00583333333333	0.0418888888888889	0.0222777777777776
64	3.07	3.05055555555556	3.0175	0.0330555555555555	0.0194444444444444
65	3.07	3.05338888888889	3.02916666666667	0.0242222222222222	0.0166111111111111
66	3.07	3.05622222222222	3.04083333333333	0.0153888888888888	0.0137777777777779
67	3.07	NA	NA	0.00847222222222213	NA
68	3.07	NA	NA	-0.00186111111111114	NA
69	3.07	NA	NA	-0.0111111111111111	NA
70	3.07	NA	NA	-0.0199444444444444	NA
71	3.07	NA	NA	-0.0287777777777777	NA
72	3.07	NA	NA	-0.037611111111111	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.27 & NA & NA & -0.0464444444444444 & NA \tabularnewline
2 & 2.35 & NA & NA & 0.0227222222222223 & NA \tabularnewline
3 & 2.54 & NA & NA & 0.0418888888888889 & NA \tabularnewline
4 & 2.54 & NA & NA & 0.0330555555555555 & NA \tabularnewline
5 & 2.54 & NA & NA & 0.0242222222222222 & NA \tabularnewline
6 & 2.54 & NA & NA & 0.0153888888888888 & NA \tabularnewline
7 & 2.54 & 2.52138888888889 & 2.51291666666667 & 0.00847222222222213 & 0.0186111111111114 \tabularnewline
8 & 2.54 & 2.53022222222222 & 2.53208333333333 & -0.00186111111111114 & 0.00977777777777833 \tabularnewline
9 & 2.54 & 2.52888888888889 & 2.54 & -0.0111111111111111 & 0.0111111111111115 \tabularnewline
10 & 2.54 & 2.52005555555556 & 2.54 & -0.0199444444444444 & 0.019944444444445 \tabularnewline
11 & 2.54 & 2.51122222222222 & 2.54 & -0.0287777777777777 & 0.028777777777778 \tabularnewline
12 & 2.54 & 2.50238888888889 & 2.54 & -0.037611111111111 & 0.0376111111111115 \tabularnewline
13 & 2.54 & 2.49355555555556 & 2.54 & -0.0464444444444444 & 0.046444444444445 \tabularnewline
14 & 2.54 & 2.56272222222222 & 2.54 & 0.0227222222222223 & -0.0227222222222219 \tabularnewline
15 & 2.54 & 2.58188888888889 & 2.54 & 0.0418888888888889 & -0.0418888888888884 \tabularnewline
16 & 2.54 & 2.57305555555555 & 2.54 & 0.0330555555555555 & -0.0330555555555549 \tabularnewline
17 & 2.54 & 2.56422222222222 & 2.54 & 0.0242222222222222 & -0.0242222222222219 \tabularnewline
18 & 2.54 & 2.55538888888889 & 2.54 & 0.0153888888888888 & -0.0153888888888885 \tabularnewline
19 & 2.54 & 2.54847222222222 & 2.54 & 0.00847222222222213 & -0.00847222222222177 \tabularnewline
20 & 2.54 & 2.54313888888889 & 2.545 & -0.00186111111111114 & -0.00313888888888814 \tabularnewline
21 & 2.54 & 2.54388888888889 & 2.555 & -0.0111111111111111 & -0.00388888888888861 \tabularnewline
22 & 2.54 & 2.54505555555555 & 2.565 & -0.0199444444444444 & -0.00505555555555492 \tabularnewline
23 & 2.54 & 2.54622222222222 & 2.575 & -0.0287777777777777 & -0.00622222222222213 \tabularnewline
24 & 2.54 & 2.54738888888889 & 2.585 & -0.037611111111111 & -0.00738888888888845 \tabularnewline
25 & 2.54 & 2.54855555555556 & 2.595 & -0.0464444444444444 & -0.00855555555555521 \tabularnewline
26 & 2.66 & 2.62772222222222 & 2.605 & 0.0227222222222223 & 0.0322777777777783 \tabularnewline
27 & 2.66 & 2.65688888888889 & 2.615 & 0.0418888888888889 & 0.00311111111111151 \tabularnewline
28 & 2.66 & 2.65805555555555 & 2.625 & 0.0330555555555555 & 0.00194444444444519 \tabularnewline
29 & 2.66 & 2.65922222222222 & 2.635 & 0.0242222222222222 & 0.000777777777777988 \tabularnewline
30 & 2.66 & 2.66038888888889 & 2.645 & 0.0153888888888888 & -0.000388888888888772 \tabularnewline
31 & 2.66 & 2.66347222222222 & 2.655 & 0.00847222222222213 & -0.00347222222222232 \tabularnewline
32 & 2.66 & 2.65813888888889 & 2.66 & -0.00186111111111114 & 0.00186111111111131 \tabularnewline
33 & 2.66 & 2.64888888888889 & 2.66 & -0.0111111111111111 & 0.0111111111111111 \tabularnewline
34 & 2.66 & 2.64005555555556 & 2.66 & -0.0199444444444444 & 0.0199444444444445 \tabularnewline
35 & 2.66 & 2.63122222222222 & 2.66 & -0.0287777777777777 & 0.0287777777777776 \tabularnewline
36 & 2.66 & 2.62238888888889 & 2.66 & -0.037611111111111 & 0.037611111111111 \tabularnewline
37 & 2.66 & 2.61355555555556 & 2.66 & -0.0464444444444444 & 0.0464444444444445 \tabularnewline
38 & 2.66 & 2.68272222222222 & 2.66 & 0.0227222222222223 & -0.0227222222222223 \tabularnewline
39 & 2.66 & 2.70188888888889 & 2.66 & 0.0418888888888889 & -0.0418888888888889 \tabularnewline
40 & 2.66 & 2.69305555555556 & 2.66 & 0.0330555555555555 & -0.0330555555555554 \tabularnewline
41 & 2.66 & 2.68422222222222 & 2.66 & 0.0242222222222222 & -0.0242222222222224 \tabularnewline
42 & 2.66 & 2.67538888888889 & 2.66 & 0.0153888888888888 & -0.0153888888888889 \tabularnewline
43 & 2.66 & 2.66847222222222 & 2.66 & 0.00847222222222213 & -0.00847222222222221 \tabularnewline
44 & 2.66 & 2.66938888888889 & 2.67125 & -0.00186111111111114 & -0.00938888888888867 \tabularnewline
45 & 2.66 & 2.68263888888889 & 2.69375 & -0.0111111111111111 & -0.0226388888888889 \tabularnewline
46 & 2.66 & 2.69630555555556 & 2.71625 & -0.0199444444444444 & -0.0363055555555554 \tabularnewline
47 & 2.66 & 2.70997222222222 & 2.73875 & -0.0287777777777777 & -0.0499722222222223 \tabularnewline
48 & 2.66 & 2.72363888888889 & 2.76125 & -0.037611111111111 & -0.0636388888888888 \tabularnewline
49 & 2.66 & 2.73730555555556 & 2.78375 & -0.0464444444444444 & -0.0773055555555553 \tabularnewline
50 & 2.93 & 2.82897222222222 & 2.80625 & 0.0227222222222223 & 0.101027777777778 \tabularnewline
51 & 2.93 & 2.87063888888889 & 2.82875 & 0.0418888888888889 & 0.0593611111111114 \tabularnewline
52 & 2.93 & 2.88430555555556 & 2.85125 & 0.0330555555555555 & 0.0456944444444445 \tabularnewline
53 & 2.93 & 2.89797222222222 & 2.87375 & 0.0242222222222222 & 0.0320277777777775 \tabularnewline
54 & 2.93 & 2.91163888888889 & 2.89625 & 0.0153888888888888 & 0.0183611111111111 \tabularnewline
55 & 2.93 & 2.92722222222222 & 2.91875 & 0.00847222222222213 & 0.00277777777777777 \tabularnewline
56 & 2.93 & 2.92813888888889 & 2.93 & -0.00186111111111114 & 0.00186111111111131 \tabularnewline
57 & 2.93 & 2.92472222222222 & 2.93583333333333 & -0.0111111111111111 & 0.00527777777777816 \tabularnewline
58 & 2.93 & 2.92755555555556 & 2.9475 & -0.0199444444444444 & 0.00244444444444492 \tabularnewline
59 & 2.93 & 2.93038888888889 & 2.95916666666667 & -0.0287777777777777 & -0.000388888888888772 \tabularnewline
60 & 2.93 & 2.93322222222222 & 2.97083333333333 & -0.037611111111111 & -0.00322222222222202 \tabularnewline
61 & 2.93 & 2.93605555555556 & 2.9825 & -0.0464444444444444 & -0.00605555555555526 \tabularnewline
62 & 2.93 & 3.01688888888889 & 2.99416666666667 & 0.0227222222222223 & -0.0868888888888888 \tabularnewline
63 & 3.07 & 3.04772222222222 & 3.00583333333333 & 0.0418888888888889 & 0.0222777777777776 \tabularnewline
64 & 3.07 & 3.05055555555556 & 3.0175 & 0.0330555555555555 & 0.0194444444444444 \tabularnewline
65 & 3.07 & 3.05338888888889 & 3.02916666666667 & 0.0242222222222222 & 0.0166111111111111 \tabularnewline
66 & 3.07 & 3.05622222222222 & 3.04083333333333 & 0.0153888888888888 & 0.0137777777777779 \tabularnewline
67 & 3.07 & NA & NA & 0.00847222222222213 & NA \tabularnewline
68 & 3.07 & NA & NA & -0.00186111111111114 & NA \tabularnewline
69 & 3.07 & NA & NA & -0.0111111111111111 & NA \tabularnewline
70 & 3.07 & NA & NA & -0.0199444444444444 & NA \tabularnewline
71 & 3.07 & NA & NA & -0.0287777777777777 & NA \tabularnewline
72 & 3.07 & NA & NA & -0.037611111111111 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208631&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]2.27[/C][C]NA[/C][C]NA[/C][C]-0.0464444444444444[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.35[/C][C]NA[/C][C]NA[/C][C]0.0227222222222223[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.54[/C][C]NA[/C][C]NA[/C][C]0.0418888888888889[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.54[/C][C]NA[/C][C]NA[/C][C]0.0330555555555555[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.54[/C][C]NA[/C][C]NA[/C][C]0.0242222222222222[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.54[/C][C]NA[/C][C]NA[/C][C]0.0153888888888888[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.54[/C][C]2.52138888888889[/C][C]2.51291666666667[/C][C]0.00847222222222213[/C][C]0.0186111111111114[/C][/ROW]
[ROW][C]8[/C][C]2.54[/C][C]2.53022222222222[/C][C]2.53208333333333[/C][C]-0.00186111111111114[/C][C]0.00977777777777833[/C][/ROW]
[ROW][C]9[/C][C]2.54[/C][C]2.52888888888889[/C][C]2.54[/C][C]-0.0111111111111111[/C][C]0.0111111111111115[/C][/ROW]
[ROW][C]10[/C][C]2.54[/C][C]2.52005555555556[/C][C]2.54[/C][C]-0.0199444444444444[/C][C]0.019944444444445[/C][/ROW]
[ROW][C]11[/C][C]2.54[/C][C]2.51122222222222[/C][C]2.54[/C][C]-0.0287777777777777[/C][C]0.028777777777778[/C][/ROW]
[ROW][C]12[/C][C]2.54[/C][C]2.50238888888889[/C][C]2.54[/C][C]-0.037611111111111[/C][C]0.0376111111111115[/C][/ROW]
[ROW][C]13[/C][C]2.54[/C][C]2.49355555555556[/C][C]2.54[/C][C]-0.0464444444444444[/C][C]0.046444444444445[/C][/ROW]
[ROW][C]14[/C][C]2.54[/C][C]2.56272222222222[/C][C]2.54[/C][C]0.0227222222222223[/C][C]-0.0227222222222219[/C][/ROW]
[ROW][C]15[/C][C]2.54[/C][C]2.58188888888889[/C][C]2.54[/C][C]0.0418888888888889[/C][C]-0.0418888888888884[/C][/ROW]
[ROW][C]16[/C][C]2.54[/C][C]2.57305555555555[/C][C]2.54[/C][C]0.0330555555555555[/C][C]-0.0330555555555549[/C][/ROW]
[ROW][C]17[/C][C]2.54[/C][C]2.56422222222222[/C][C]2.54[/C][C]0.0242222222222222[/C][C]-0.0242222222222219[/C][/ROW]
[ROW][C]18[/C][C]2.54[/C][C]2.55538888888889[/C][C]2.54[/C][C]0.0153888888888888[/C][C]-0.0153888888888885[/C][/ROW]
[ROW][C]19[/C][C]2.54[/C][C]2.54847222222222[/C][C]2.54[/C][C]0.00847222222222213[/C][C]-0.00847222222222177[/C][/ROW]
[ROW][C]20[/C][C]2.54[/C][C]2.54313888888889[/C][C]2.545[/C][C]-0.00186111111111114[/C][C]-0.00313888888888814[/C][/ROW]
[ROW][C]21[/C][C]2.54[/C][C]2.54388888888889[/C][C]2.555[/C][C]-0.0111111111111111[/C][C]-0.00388888888888861[/C][/ROW]
[ROW][C]22[/C][C]2.54[/C][C]2.54505555555555[/C][C]2.565[/C][C]-0.0199444444444444[/C][C]-0.00505555555555492[/C][/ROW]
[ROW][C]23[/C][C]2.54[/C][C]2.54622222222222[/C][C]2.575[/C][C]-0.0287777777777777[/C][C]-0.00622222222222213[/C][/ROW]
[ROW][C]24[/C][C]2.54[/C][C]2.54738888888889[/C][C]2.585[/C][C]-0.037611111111111[/C][C]-0.00738888888888845[/C][/ROW]
[ROW][C]25[/C][C]2.54[/C][C]2.54855555555556[/C][C]2.595[/C][C]-0.0464444444444444[/C][C]-0.00855555555555521[/C][/ROW]
[ROW][C]26[/C][C]2.66[/C][C]2.62772222222222[/C][C]2.605[/C][C]0.0227222222222223[/C][C]0.0322777777777783[/C][/ROW]
[ROW][C]27[/C][C]2.66[/C][C]2.65688888888889[/C][C]2.615[/C][C]0.0418888888888889[/C][C]0.00311111111111151[/C][/ROW]
[ROW][C]28[/C][C]2.66[/C][C]2.65805555555555[/C][C]2.625[/C][C]0.0330555555555555[/C][C]0.00194444444444519[/C][/ROW]
[ROW][C]29[/C][C]2.66[/C][C]2.65922222222222[/C][C]2.635[/C][C]0.0242222222222222[/C][C]0.000777777777777988[/C][/ROW]
[ROW][C]30[/C][C]2.66[/C][C]2.66038888888889[/C][C]2.645[/C][C]0.0153888888888888[/C][C]-0.000388888888888772[/C][/ROW]
[ROW][C]31[/C][C]2.66[/C][C]2.66347222222222[/C][C]2.655[/C][C]0.00847222222222213[/C][C]-0.00347222222222232[/C][/ROW]
[ROW][C]32[/C][C]2.66[/C][C]2.65813888888889[/C][C]2.66[/C][C]-0.00186111111111114[/C][C]0.00186111111111131[/C][/ROW]
[ROW][C]33[/C][C]2.66[/C][C]2.64888888888889[/C][C]2.66[/C][C]-0.0111111111111111[/C][C]0.0111111111111111[/C][/ROW]
[ROW][C]34[/C][C]2.66[/C][C]2.64005555555556[/C][C]2.66[/C][C]-0.0199444444444444[/C][C]0.0199444444444445[/C][/ROW]
[ROW][C]35[/C][C]2.66[/C][C]2.63122222222222[/C][C]2.66[/C][C]-0.0287777777777777[/C][C]0.0287777777777776[/C][/ROW]
[ROW][C]36[/C][C]2.66[/C][C]2.62238888888889[/C][C]2.66[/C][C]-0.037611111111111[/C][C]0.037611111111111[/C][/ROW]
[ROW][C]37[/C][C]2.66[/C][C]2.61355555555556[/C][C]2.66[/C][C]-0.0464444444444444[/C][C]0.0464444444444445[/C][/ROW]
[ROW][C]38[/C][C]2.66[/C][C]2.68272222222222[/C][C]2.66[/C][C]0.0227222222222223[/C][C]-0.0227222222222223[/C][/ROW]
[ROW][C]39[/C][C]2.66[/C][C]2.70188888888889[/C][C]2.66[/C][C]0.0418888888888889[/C][C]-0.0418888888888889[/C][/ROW]
[ROW][C]40[/C][C]2.66[/C][C]2.69305555555556[/C][C]2.66[/C][C]0.0330555555555555[/C][C]-0.0330555555555554[/C][/ROW]
[ROW][C]41[/C][C]2.66[/C][C]2.68422222222222[/C][C]2.66[/C][C]0.0242222222222222[/C][C]-0.0242222222222224[/C][/ROW]
[ROW][C]42[/C][C]2.66[/C][C]2.67538888888889[/C][C]2.66[/C][C]0.0153888888888888[/C][C]-0.0153888888888889[/C][/ROW]
[ROW][C]43[/C][C]2.66[/C][C]2.66847222222222[/C][C]2.66[/C][C]0.00847222222222213[/C][C]-0.00847222222222221[/C][/ROW]
[ROW][C]44[/C][C]2.66[/C][C]2.66938888888889[/C][C]2.67125[/C][C]-0.00186111111111114[/C][C]-0.00938888888888867[/C][/ROW]
[ROW][C]45[/C][C]2.66[/C][C]2.68263888888889[/C][C]2.69375[/C][C]-0.0111111111111111[/C][C]-0.0226388888888889[/C][/ROW]
[ROW][C]46[/C][C]2.66[/C][C]2.69630555555556[/C][C]2.71625[/C][C]-0.0199444444444444[/C][C]-0.0363055555555554[/C][/ROW]
[ROW][C]47[/C][C]2.66[/C][C]2.70997222222222[/C][C]2.73875[/C][C]-0.0287777777777777[/C][C]-0.0499722222222223[/C][/ROW]
[ROW][C]48[/C][C]2.66[/C][C]2.72363888888889[/C][C]2.76125[/C][C]-0.037611111111111[/C][C]-0.0636388888888888[/C][/ROW]
[ROW][C]49[/C][C]2.66[/C][C]2.73730555555556[/C][C]2.78375[/C][C]-0.0464444444444444[/C][C]-0.0773055555555553[/C][/ROW]
[ROW][C]50[/C][C]2.93[/C][C]2.82897222222222[/C][C]2.80625[/C][C]0.0227222222222223[/C][C]0.101027777777778[/C][/ROW]
[ROW][C]51[/C][C]2.93[/C][C]2.87063888888889[/C][C]2.82875[/C][C]0.0418888888888889[/C][C]0.0593611111111114[/C][/ROW]
[ROW][C]52[/C][C]2.93[/C][C]2.88430555555556[/C][C]2.85125[/C][C]0.0330555555555555[/C][C]0.0456944444444445[/C][/ROW]
[ROW][C]53[/C][C]2.93[/C][C]2.89797222222222[/C][C]2.87375[/C][C]0.0242222222222222[/C][C]0.0320277777777775[/C][/ROW]
[ROW][C]54[/C][C]2.93[/C][C]2.91163888888889[/C][C]2.89625[/C][C]0.0153888888888888[/C][C]0.0183611111111111[/C][/ROW]
[ROW][C]55[/C][C]2.93[/C][C]2.92722222222222[/C][C]2.91875[/C][C]0.00847222222222213[/C][C]0.00277777777777777[/C][/ROW]
[ROW][C]56[/C][C]2.93[/C][C]2.92813888888889[/C][C]2.93[/C][C]-0.00186111111111114[/C][C]0.00186111111111131[/C][/ROW]
[ROW][C]57[/C][C]2.93[/C][C]2.92472222222222[/C][C]2.93583333333333[/C][C]-0.0111111111111111[/C][C]0.00527777777777816[/C][/ROW]
[ROW][C]58[/C][C]2.93[/C][C]2.92755555555556[/C][C]2.9475[/C][C]-0.0199444444444444[/C][C]0.00244444444444492[/C][/ROW]
[ROW][C]59[/C][C]2.93[/C][C]2.93038888888889[/C][C]2.95916666666667[/C][C]-0.0287777777777777[/C][C]-0.000388888888888772[/C][/ROW]
[ROW][C]60[/C][C]2.93[/C][C]2.93322222222222[/C][C]2.97083333333333[/C][C]-0.037611111111111[/C][C]-0.00322222222222202[/C][/ROW]
[ROW][C]61[/C][C]2.93[/C][C]2.93605555555556[/C][C]2.9825[/C][C]-0.0464444444444444[/C][C]-0.00605555555555526[/C][/ROW]
[ROW][C]62[/C][C]2.93[/C][C]3.01688888888889[/C][C]2.99416666666667[/C][C]0.0227222222222223[/C][C]-0.0868888888888888[/C][/ROW]
[ROW][C]63[/C][C]3.07[/C][C]3.04772222222222[/C][C]3.00583333333333[/C][C]0.0418888888888889[/C][C]0.0222777777777776[/C][/ROW]
[ROW][C]64[/C][C]3.07[/C][C]3.05055555555556[/C][C]3.0175[/C][C]0.0330555555555555[/C][C]0.0194444444444444[/C][/ROW]
[ROW][C]65[/C][C]3.07[/C][C]3.05338888888889[/C][C]3.02916666666667[/C][C]0.0242222222222222[/C][C]0.0166111111111111[/C][/ROW]
[ROW][C]66[/C][C]3.07[/C][C]3.05622222222222[/C][C]3.04083333333333[/C][C]0.0153888888888888[/C][C]0.0137777777777779[/C][/ROW]
[ROW][C]67[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]0.00847222222222213[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]-0.00186111111111114[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]-0.0111111111111111[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]-0.0199444444444444[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]-0.0287777777777777[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]-0.037611111111111[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208631&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208631&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	2.27	NA	NA	-0.0464444444444444	NA
2	2.35	NA	NA	0.0227222222222223	NA
3	2.54	NA	NA	0.0418888888888889	NA
4	2.54	NA	NA	0.0330555555555555	NA
5	2.54	NA	NA	0.0242222222222222	NA
6	2.54	NA	NA	0.0153888888888888	NA
7	2.54	2.52138888888889	2.51291666666667	0.00847222222222213	0.0186111111111114
8	2.54	2.53022222222222	2.53208333333333	-0.00186111111111114	0.00977777777777833
9	2.54	2.52888888888889	2.54	-0.0111111111111111	0.0111111111111115
10	2.54	2.52005555555556	2.54	-0.0199444444444444	0.019944444444445
11	2.54	2.51122222222222	2.54	-0.0287777777777777	0.028777777777778
12	2.54	2.50238888888889	2.54	-0.037611111111111	0.0376111111111115
13	2.54	2.49355555555556	2.54	-0.0464444444444444	0.046444444444445
14	2.54	2.56272222222222	2.54	0.0227222222222223	-0.0227222222222219
15	2.54	2.58188888888889	2.54	0.0418888888888889	-0.0418888888888884
16	2.54	2.57305555555555	2.54	0.0330555555555555	-0.0330555555555549
17	2.54	2.56422222222222	2.54	0.0242222222222222	-0.0242222222222219
18	2.54	2.55538888888889	2.54	0.0153888888888888	-0.0153888888888885
19	2.54	2.54847222222222	2.54	0.00847222222222213	-0.00847222222222177
20	2.54	2.54313888888889	2.545	-0.00186111111111114	-0.00313888888888814
21	2.54	2.54388888888889	2.555	-0.0111111111111111	-0.00388888888888861
22	2.54	2.54505555555555	2.565	-0.0199444444444444	-0.00505555555555492
23	2.54	2.54622222222222	2.575	-0.0287777777777777	-0.00622222222222213
24	2.54	2.54738888888889	2.585	-0.037611111111111	-0.00738888888888845
25	2.54	2.54855555555556	2.595	-0.0464444444444444	-0.00855555555555521
26	2.66	2.62772222222222	2.605	0.0227222222222223	0.0322777777777783
27	2.66	2.65688888888889	2.615	0.0418888888888889	0.00311111111111151
28	2.66	2.65805555555555	2.625	0.0330555555555555	0.00194444444444519
29	2.66	2.65922222222222	2.635	0.0242222222222222	0.000777777777777988
30	2.66	2.66038888888889	2.645	0.0153888888888888	-0.000388888888888772
31	2.66	2.66347222222222	2.655	0.00847222222222213	-0.00347222222222232
32	2.66	2.65813888888889	2.66	-0.00186111111111114	0.00186111111111131
33	2.66	2.64888888888889	2.66	-0.0111111111111111	0.0111111111111111
34	2.66	2.64005555555556	2.66	-0.0199444444444444	0.0199444444444445
35	2.66	2.63122222222222	2.66	-0.0287777777777777	0.0287777777777776
36	2.66	2.62238888888889	2.66	-0.037611111111111	0.037611111111111
37	2.66	2.61355555555556	2.66	-0.0464444444444444	0.0464444444444445
38	2.66	2.68272222222222	2.66	0.0227222222222223	-0.0227222222222223
39	2.66	2.70188888888889	2.66	0.0418888888888889	-0.0418888888888889
40	2.66	2.69305555555556	2.66	0.0330555555555555	-0.0330555555555554
41	2.66	2.68422222222222	2.66	0.0242222222222222	-0.0242222222222224
42	2.66	2.67538888888889	2.66	0.0153888888888888	-0.0153888888888889
43	2.66	2.66847222222222	2.66	0.00847222222222213	-0.00847222222222221
44	2.66	2.66938888888889	2.67125	-0.00186111111111114	-0.00938888888888867
45	2.66	2.68263888888889	2.69375	-0.0111111111111111	-0.0226388888888889
46	2.66	2.69630555555556	2.71625	-0.0199444444444444	-0.0363055555555554
47	2.66	2.70997222222222	2.73875	-0.0287777777777777	-0.0499722222222223
48	2.66	2.72363888888889	2.76125	-0.037611111111111	-0.0636388888888888
49	2.66	2.73730555555556	2.78375	-0.0464444444444444	-0.0773055555555553
50	2.93	2.82897222222222	2.80625	0.0227222222222223	0.101027777777778
51	2.93	2.87063888888889	2.82875	0.0418888888888889	0.0593611111111114
52	2.93	2.88430555555556	2.85125	0.0330555555555555	0.0456944444444445
53	2.93	2.89797222222222	2.87375	0.0242222222222222	0.0320277777777775
54	2.93	2.91163888888889	2.89625	0.0153888888888888	0.0183611111111111
55	2.93	2.92722222222222	2.91875	0.00847222222222213	0.00277777777777777
56	2.93	2.92813888888889	2.93	-0.00186111111111114	0.00186111111111131
57	2.93	2.92472222222222	2.93583333333333	-0.0111111111111111	0.00527777777777816
58	2.93	2.92755555555556	2.9475	-0.0199444444444444	0.00244444444444492
59	2.93	2.93038888888889	2.95916666666667	-0.0287777777777777	-0.000388888888888772
60	2.93	2.93322222222222	2.97083333333333	-0.037611111111111	-0.00322222222222202
61	2.93	2.93605555555556	2.9825	-0.0464444444444444	-0.00605555555555526
62	2.93	3.01688888888889	2.99416666666667	0.0227222222222223	-0.0868888888888888
63	3.07	3.04772222222222	3.00583333333333	0.0418888888888889	0.0222777777777776
64	3.07	3.05055555555556	3.0175	0.0330555555555555	0.0194444444444444
65	3.07	3.05338888888889	3.02916666666667	0.0242222222222222	0.0166111111111111
66	3.07	3.05622222222222	3.04083333333333	0.0153888888888888	0.0137777777777779
67	3.07	NA	NA	0.00847222222222213	NA
68	3.07	NA	NA	-0.00186111111111114	NA
69	3.07	NA	NA	-0.0111111111111111	NA
70	3.07	NA	NA	-0.0199444444444444	NA
71	3.07	NA	NA	-0.0287777777777777	NA
72	3.07	NA	NA	-0.037611111111111	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$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