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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 29 Nov 2009 06:41:35 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/29/t1259502133cak2eqea4d0xny6.htm/, Retrieved Sat, 20 Apr 2024 04:43:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61595, Retrieved Sat, 20 Apr 2024 04:43:16 +0000

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Estimated Impact

169

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-    D      [Classical Decomposition] [ws 9 classical] [2009-11-29 13:41:35] [2e4ef2c1b76db9b31c0a03b96e94ad77] [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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61595&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61595&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61595&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	103.63	NA	NA	1.00055541275226	NA
2	103.64	NA	NA	1.00028715838792	NA
3	103.66	NA	NA	1.00037376459922	NA
4	103.77	NA	NA	1.00019650002369	NA
5	103.88	NA	NA	0.999670231989992	NA
6	103.91	NA	NA	0.99931323068568	NA
7	103.91	103.851834036343	103.9625	0.998935520368816	1.00056008605141
8	103.92	103.854535605669	104.02	0.998409302111791	1.00063034699399
9	104.05	104.017831576674	104.08625	0.9993426756817	1.00030925873803
10	104.23	104.246596397299	104.16	1.00083137862231	0.99984079674663
11	104.3	104.348868191934	104.232083333333	1.00112043101189	0.999531684504293
12	104.31	104.403088680647	104.3025	1.00096439376474	0.999108372349674
13	104.31	104.430469817485	104.3725	1.00055541275226	0.99884641122753
14	104.34	104.47249153993	104.4425	1.00028715838792	0.998731804535557
15	104.55	104.553647184686	104.514583333333	1.00037376459922	0.99996511661923
16	104.65	104.616386417061	104.595833333333	1.00019650002369	1.00032130323069
17	104.73	104.650478235872	104.685	0.999670231989992	1.0007598796056
18	104.75	104.704709267143	104.776666666667	0.99931323068568	1.00043255678922
19	104.75	104.758368021078	104.87	0.998935520368816	0.99992012073846
20	104.76	104.794704365157	104.961666666667	0.998409302111791	0.99966883474344
21	104.94	104.978033330892	105.047083333333	0.9993426756817	0.999637702005981
22	105.29	105.218236860712	105.130833333333	1.00083137862231	1.00068204088406
23	105.38	105.333303282429	105.215416666667	1.00112043101189	1.00044332339456
24	105.43	105.399465320940	105.297916666667	1.00096439376474	1.00028970430701
25	105.43	105.438946293922	105.380416666667	1.00055541275226	0.999915151903199
26	105.42	105.492784441486	105.4625	1.00028715838792	0.999310052892518
27	105.52	105.584865807027	105.545416666667	1.00037376459922	0.999385652417788
28	105.69	105.644921817919	105.624166666667	1.00019650002369	1.00042669520982
29	105.72	105.665976579869	105.700833333333	0.999670231989992	1.00051126599006
30	105.74	105.707353541931	105.78	0.99931323068568	1.00030883809853
31	105.74	105.745649293709	105.858333333333	0.998935520368816	0.999946576584978
32	105.74	105.768153434716	105.936666666667	0.998409302111791	0.999733819360536
33	105.95	105.944480976832	106.014166666667	0.9993426756817	1.00005209354104
34	106.17	106.165690565808	106.0775	1.00083137862231	1.00004059159008
35	106.34	106.242654340598	106.12375	1.00112043101189	1.00091625778748
36	106.37	106.267801932531	106.165416666667	1.00096439376474	1.00096170303338
37	106.37	106.265238305620	106.20625	1.00055541275226	1.00098585102759
38	106.36	106.277593074504	106.247083333333	1.00028715838792	1.00077539322365
39	106.44	106.323475103222	106.28375	1.00037376459922	1.00109594703018
40	106.29	106.332140163143	106.31125	1.00019650002369	0.999603693078324
41	106.23	106.291603533389	106.326666666667	0.999670231989992	0.999420428977066
42	106.23	106.262388765475	106.335416666667	0.99931323068568	0.999695200099952
43	106.23	106.232214136755	106.345416666667	0.998935520368816	0.999979157576887
44	106.23	106.190397368734	106.359583333333	0.998409302111791	1.00037293985376
45	106.34	106.29674927001	106.366666666667	0.9993426756817	1.00040688666669
46	106.44	106.456765691757	106.368333333333	1.00083137862231	0.999842511730956
47	106.44	106.491683047812	106.3725	1.00112043101189	0.999514675265402
48	106.48	106.475084975740	106.3725	1.00096439376474	1.00004616126168
49	106.5	106.429913050635	106.370833333333	1.00055541275226	1.00065852679342
50	106.57	106.400961824039	106.370416666667	1.00028715838792	1.00158869030001
51	106.4	106.404338649194	106.364583333333	1.00037376459922	0.999959224884537
52	106.37	106.364229800852	106.343333333333	1.00019650002369	1.0000542494329
53	106.25	106.280357243279	106.315416666667	0.999670231989992	0.999714366379012
54	106.21	106.213255864966	106.28625	0.99931323068568	0.99996934596403
55	106.21	NA	NA	0.998935520368816	NA
56	106.24	NA	NA	0.998409302111791	NA
57	106.19	NA	NA	0.9993426756817	NA
58	106.08	NA	NA	1.00083137862231	NA
59	106.13	NA	NA	1.00112043101189	NA
60	106.09	NA	NA	1.00096439376474	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.63 & NA & NA & 1.00055541275226 & NA \tabularnewline
2 & 103.64 & NA & NA & 1.00028715838792 & NA \tabularnewline
3 & 103.66 & NA & NA & 1.00037376459922 & NA \tabularnewline
4 & 103.77 & NA & NA & 1.00019650002369 & NA \tabularnewline
5 & 103.88 & NA & NA & 0.999670231989992 & NA \tabularnewline
6 & 103.91 & NA & NA & 0.99931323068568 & NA \tabularnewline
7 & 103.91 & 103.851834036343 & 103.9625 & 0.998935520368816 & 1.00056008605141 \tabularnewline
8 & 103.92 & 103.854535605669 & 104.02 & 0.998409302111791 & 1.00063034699399 \tabularnewline
9 & 104.05 & 104.017831576674 & 104.08625 & 0.9993426756817 & 1.00030925873803 \tabularnewline
10 & 104.23 & 104.246596397299 & 104.16 & 1.00083137862231 & 0.99984079674663 \tabularnewline
11 & 104.3 & 104.348868191934 & 104.232083333333 & 1.00112043101189 & 0.999531684504293 \tabularnewline
12 & 104.31 & 104.403088680647 & 104.3025 & 1.00096439376474 & 0.999108372349674 \tabularnewline
13 & 104.31 & 104.430469817485 & 104.3725 & 1.00055541275226 & 0.99884641122753 \tabularnewline
14 & 104.34 & 104.47249153993 & 104.4425 & 1.00028715838792 & 0.998731804535557 \tabularnewline
15 & 104.55 & 104.553647184686 & 104.514583333333 & 1.00037376459922 & 0.99996511661923 \tabularnewline
16 & 104.65 & 104.616386417061 & 104.595833333333 & 1.00019650002369 & 1.00032130323069 \tabularnewline
17 & 104.73 & 104.650478235872 & 104.685 & 0.999670231989992 & 1.0007598796056 \tabularnewline
18 & 104.75 & 104.704709267143 & 104.776666666667 & 0.99931323068568 & 1.00043255678922 \tabularnewline
19 & 104.75 & 104.758368021078 & 104.87 & 0.998935520368816 & 0.99992012073846 \tabularnewline
20 & 104.76 & 104.794704365157 & 104.961666666667 & 0.998409302111791 & 0.99966883474344 \tabularnewline
21 & 104.94 & 104.978033330892 & 105.047083333333 & 0.9993426756817 & 0.999637702005981 \tabularnewline
22 & 105.29 & 105.218236860712 & 105.130833333333 & 1.00083137862231 & 1.00068204088406 \tabularnewline
23 & 105.38 & 105.333303282429 & 105.215416666667 & 1.00112043101189 & 1.00044332339456 \tabularnewline
24 & 105.43 & 105.399465320940 & 105.297916666667 & 1.00096439376474 & 1.00028970430701 \tabularnewline
25 & 105.43 & 105.438946293922 & 105.380416666667 & 1.00055541275226 & 0.999915151903199 \tabularnewline
26 & 105.42 & 105.492784441486 & 105.4625 & 1.00028715838792 & 0.999310052892518 \tabularnewline
27 & 105.52 & 105.584865807027 & 105.545416666667 & 1.00037376459922 & 0.999385652417788 \tabularnewline
28 & 105.69 & 105.644921817919 & 105.624166666667 & 1.00019650002369 & 1.00042669520982 \tabularnewline
29 & 105.72 & 105.665976579869 & 105.700833333333 & 0.999670231989992 & 1.00051126599006 \tabularnewline
30 & 105.74 & 105.707353541931 & 105.78 & 0.99931323068568 & 1.00030883809853 \tabularnewline
31 & 105.74 & 105.745649293709 & 105.858333333333 & 0.998935520368816 & 0.999946576584978 \tabularnewline
32 & 105.74 & 105.768153434716 & 105.936666666667 & 0.998409302111791 & 0.999733819360536 \tabularnewline
33 & 105.95 & 105.944480976832 & 106.014166666667 & 0.9993426756817 & 1.00005209354104 \tabularnewline
34 & 106.17 & 106.165690565808 & 106.0775 & 1.00083137862231 & 1.00004059159008 \tabularnewline
35 & 106.34 & 106.242654340598 & 106.12375 & 1.00112043101189 & 1.00091625778748 \tabularnewline
36 & 106.37 & 106.267801932531 & 106.165416666667 & 1.00096439376474 & 1.00096170303338 \tabularnewline
37 & 106.37 & 106.265238305620 & 106.20625 & 1.00055541275226 & 1.00098585102759 \tabularnewline
38 & 106.36 & 106.277593074504 & 106.247083333333 & 1.00028715838792 & 1.00077539322365 \tabularnewline
39 & 106.44 & 106.323475103222 & 106.28375 & 1.00037376459922 & 1.00109594703018 \tabularnewline
40 & 106.29 & 106.332140163143 & 106.31125 & 1.00019650002369 & 0.999603693078324 \tabularnewline
41 & 106.23 & 106.291603533389 & 106.326666666667 & 0.999670231989992 & 0.999420428977066 \tabularnewline
42 & 106.23 & 106.262388765475 & 106.335416666667 & 0.99931323068568 & 0.999695200099952 \tabularnewline
43 & 106.23 & 106.232214136755 & 106.345416666667 & 0.998935520368816 & 0.999979157576887 \tabularnewline
44 & 106.23 & 106.190397368734 & 106.359583333333 & 0.998409302111791 & 1.00037293985376 \tabularnewline
45 & 106.34 & 106.29674927001 & 106.366666666667 & 0.9993426756817 & 1.00040688666669 \tabularnewline
46 & 106.44 & 106.456765691757 & 106.368333333333 & 1.00083137862231 & 0.999842511730956 \tabularnewline
47 & 106.44 & 106.491683047812 & 106.3725 & 1.00112043101189 & 0.999514675265402 \tabularnewline
48 & 106.48 & 106.475084975740 & 106.3725 & 1.00096439376474 & 1.00004616126168 \tabularnewline
49 & 106.5 & 106.429913050635 & 106.370833333333 & 1.00055541275226 & 1.00065852679342 \tabularnewline
50 & 106.57 & 106.400961824039 & 106.370416666667 & 1.00028715838792 & 1.00158869030001 \tabularnewline
51 & 106.4 & 106.404338649194 & 106.364583333333 & 1.00037376459922 & 0.999959224884537 \tabularnewline
52 & 106.37 & 106.364229800852 & 106.343333333333 & 1.00019650002369 & 1.0000542494329 \tabularnewline
53 & 106.25 & 106.280357243279 & 106.315416666667 & 0.999670231989992 & 0.999714366379012 \tabularnewline
54 & 106.21 & 106.213255864966 & 106.28625 & 0.99931323068568 & 0.99996934596403 \tabularnewline
55 & 106.21 & NA & NA & 0.998935520368816 & NA \tabularnewline
56 & 106.24 & NA & NA & 0.998409302111791 & NA \tabularnewline
57 & 106.19 & NA & NA & 0.9993426756817 & NA \tabularnewline
58 & 106.08 & NA & NA & 1.00083137862231 & NA \tabularnewline
59 & 106.13 & NA & NA & 1.00112043101189 & NA \tabularnewline
60 & 106.09 & NA & NA & 1.00096439376474 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61595&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]103.63[/C][C]NA[/C][C]NA[/C][C]1.00055541275226[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.64[/C][C]NA[/C][C]NA[/C][C]1.00028715838792[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]103.66[/C][C]NA[/C][C]NA[/C][C]1.00037376459922[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]103.77[/C][C]NA[/C][C]NA[/C][C]1.00019650002369[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]103.88[/C][C]NA[/C][C]NA[/C][C]0.999670231989992[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]103.91[/C][C]NA[/C][C]NA[/C][C]0.99931323068568[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]103.91[/C][C]103.851834036343[/C][C]103.9625[/C][C]0.998935520368816[/C][C]1.00056008605141[/C][/ROW]
[ROW][C]8[/C][C]103.92[/C][C]103.854535605669[/C][C]104.02[/C][C]0.998409302111791[/C][C]1.00063034699399[/C][/ROW]
[ROW][C]9[/C][C]104.05[/C][C]104.017831576674[/C][C]104.08625[/C][C]0.9993426756817[/C][C]1.00030925873803[/C][/ROW]
[ROW][C]10[/C][C]104.23[/C][C]104.246596397299[/C][C]104.16[/C][C]1.00083137862231[/C][C]0.99984079674663[/C][/ROW]
[ROW][C]11[/C][C]104.3[/C][C]104.348868191934[/C][C]104.232083333333[/C][C]1.00112043101189[/C][C]0.999531684504293[/C][/ROW]
[ROW][C]12[/C][C]104.31[/C][C]104.403088680647[/C][C]104.3025[/C][C]1.00096439376474[/C][C]0.999108372349674[/C][/ROW]
[ROW][C]13[/C][C]104.31[/C][C]104.430469817485[/C][C]104.3725[/C][C]1.00055541275226[/C][C]0.99884641122753[/C][/ROW]
[ROW][C]14[/C][C]104.34[/C][C]104.47249153993[/C][C]104.4425[/C][C]1.00028715838792[/C][C]0.998731804535557[/C][/ROW]
[ROW][C]15[/C][C]104.55[/C][C]104.553647184686[/C][C]104.514583333333[/C][C]1.00037376459922[/C][C]0.99996511661923[/C][/ROW]
[ROW][C]16[/C][C]104.65[/C][C]104.616386417061[/C][C]104.595833333333[/C][C]1.00019650002369[/C][C]1.00032130323069[/C][/ROW]
[ROW][C]17[/C][C]104.73[/C][C]104.650478235872[/C][C]104.685[/C][C]0.999670231989992[/C][C]1.0007598796056[/C][/ROW]
[ROW][C]18[/C][C]104.75[/C][C]104.704709267143[/C][C]104.776666666667[/C][C]0.99931323068568[/C][C]1.00043255678922[/C][/ROW]
[ROW][C]19[/C][C]104.75[/C][C]104.758368021078[/C][C]104.87[/C][C]0.998935520368816[/C][C]0.99992012073846[/C][/ROW]
[ROW][C]20[/C][C]104.76[/C][C]104.794704365157[/C][C]104.961666666667[/C][C]0.998409302111791[/C][C]0.99966883474344[/C][/ROW]
[ROW][C]21[/C][C]104.94[/C][C]104.978033330892[/C][C]105.047083333333[/C][C]0.9993426756817[/C][C]0.999637702005981[/C][/ROW]
[ROW][C]22[/C][C]105.29[/C][C]105.218236860712[/C][C]105.130833333333[/C][C]1.00083137862231[/C][C]1.00068204088406[/C][/ROW]
[ROW][C]23[/C][C]105.38[/C][C]105.333303282429[/C][C]105.215416666667[/C][C]1.00112043101189[/C][C]1.00044332339456[/C][/ROW]
[ROW][C]24[/C][C]105.43[/C][C]105.399465320940[/C][C]105.297916666667[/C][C]1.00096439376474[/C][C]1.00028970430701[/C][/ROW]
[ROW][C]25[/C][C]105.43[/C][C]105.438946293922[/C][C]105.380416666667[/C][C]1.00055541275226[/C][C]0.999915151903199[/C][/ROW]
[ROW][C]26[/C][C]105.42[/C][C]105.492784441486[/C][C]105.4625[/C][C]1.00028715838792[/C][C]0.999310052892518[/C][/ROW]
[ROW][C]27[/C][C]105.52[/C][C]105.584865807027[/C][C]105.545416666667[/C][C]1.00037376459922[/C][C]0.999385652417788[/C][/ROW]
[ROW][C]28[/C][C]105.69[/C][C]105.644921817919[/C][C]105.624166666667[/C][C]1.00019650002369[/C][C]1.00042669520982[/C][/ROW]
[ROW][C]29[/C][C]105.72[/C][C]105.665976579869[/C][C]105.700833333333[/C][C]0.999670231989992[/C][C]1.00051126599006[/C][/ROW]
[ROW][C]30[/C][C]105.74[/C][C]105.707353541931[/C][C]105.78[/C][C]0.99931323068568[/C][C]1.00030883809853[/C][/ROW]
[ROW][C]31[/C][C]105.74[/C][C]105.745649293709[/C][C]105.858333333333[/C][C]0.998935520368816[/C][C]0.999946576584978[/C][/ROW]
[ROW][C]32[/C][C]105.74[/C][C]105.768153434716[/C][C]105.936666666667[/C][C]0.998409302111791[/C][C]0.999733819360536[/C][/ROW]
[ROW][C]33[/C][C]105.95[/C][C]105.944480976832[/C][C]106.014166666667[/C][C]0.9993426756817[/C][C]1.00005209354104[/C][/ROW]
[ROW][C]34[/C][C]106.17[/C][C]106.165690565808[/C][C]106.0775[/C][C]1.00083137862231[/C][C]1.00004059159008[/C][/ROW]
[ROW][C]35[/C][C]106.34[/C][C]106.242654340598[/C][C]106.12375[/C][C]1.00112043101189[/C][C]1.00091625778748[/C][/ROW]
[ROW][C]36[/C][C]106.37[/C][C]106.267801932531[/C][C]106.165416666667[/C][C]1.00096439376474[/C][C]1.00096170303338[/C][/ROW]
[ROW][C]37[/C][C]106.37[/C][C]106.265238305620[/C][C]106.20625[/C][C]1.00055541275226[/C][C]1.00098585102759[/C][/ROW]
[ROW][C]38[/C][C]106.36[/C][C]106.277593074504[/C][C]106.247083333333[/C][C]1.00028715838792[/C][C]1.00077539322365[/C][/ROW]
[ROW][C]39[/C][C]106.44[/C][C]106.323475103222[/C][C]106.28375[/C][C]1.00037376459922[/C][C]1.00109594703018[/C][/ROW]
[ROW][C]40[/C][C]106.29[/C][C]106.332140163143[/C][C]106.31125[/C][C]1.00019650002369[/C][C]0.999603693078324[/C][/ROW]
[ROW][C]41[/C][C]106.23[/C][C]106.291603533389[/C][C]106.326666666667[/C][C]0.999670231989992[/C][C]0.999420428977066[/C][/ROW]
[ROW][C]42[/C][C]106.23[/C][C]106.262388765475[/C][C]106.335416666667[/C][C]0.99931323068568[/C][C]0.999695200099952[/C][/ROW]
[ROW][C]43[/C][C]106.23[/C][C]106.232214136755[/C][C]106.345416666667[/C][C]0.998935520368816[/C][C]0.999979157576887[/C][/ROW]
[ROW][C]44[/C][C]106.23[/C][C]106.190397368734[/C][C]106.359583333333[/C][C]0.998409302111791[/C][C]1.00037293985376[/C][/ROW]
[ROW][C]45[/C][C]106.34[/C][C]106.29674927001[/C][C]106.366666666667[/C][C]0.9993426756817[/C][C]1.00040688666669[/C][/ROW]
[ROW][C]46[/C][C]106.44[/C][C]106.456765691757[/C][C]106.368333333333[/C][C]1.00083137862231[/C][C]0.999842511730956[/C][/ROW]
[ROW][C]47[/C][C]106.44[/C][C]106.491683047812[/C][C]106.3725[/C][C]1.00112043101189[/C][C]0.999514675265402[/C][/ROW]
[ROW][C]48[/C][C]106.48[/C][C]106.475084975740[/C][C]106.3725[/C][C]1.00096439376474[/C][C]1.00004616126168[/C][/ROW]
[ROW][C]49[/C][C]106.5[/C][C]106.429913050635[/C][C]106.370833333333[/C][C]1.00055541275226[/C][C]1.00065852679342[/C][/ROW]
[ROW][C]50[/C][C]106.57[/C][C]106.400961824039[/C][C]106.370416666667[/C][C]1.00028715838792[/C][C]1.00158869030001[/C][/ROW]
[ROW][C]51[/C][C]106.4[/C][C]106.404338649194[/C][C]106.364583333333[/C][C]1.00037376459922[/C][C]0.999959224884537[/C][/ROW]
[ROW][C]52[/C][C]106.37[/C][C]106.364229800852[/C][C]106.343333333333[/C][C]1.00019650002369[/C][C]1.0000542494329[/C][/ROW]
[ROW][C]53[/C][C]106.25[/C][C]106.280357243279[/C][C]106.315416666667[/C][C]0.999670231989992[/C][C]0.999714366379012[/C][/ROW]
[ROW][C]54[/C][C]106.21[/C][C]106.213255864966[/C][C]106.28625[/C][C]0.99931323068568[/C][C]0.99996934596403[/C][/ROW]
[ROW][C]55[/C][C]106.21[/C][C]NA[/C][C]NA[/C][C]0.998935520368816[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]106.24[/C][C]NA[/C][C]NA[/C][C]0.998409302111791[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]106.19[/C][C]NA[/C][C]NA[/C][C]0.9993426756817[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]106.08[/C][C]NA[/C][C]NA[/C][C]1.00083137862231[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]106.13[/C][C]NA[/C][C]NA[/C][C]1.00112043101189[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]106.09[/C][C]NA[/C][C]NA[/C][C]1.00096439376474[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61595&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61595&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	103.63	NA	NA	1.00055541275226	NA
2	103.64	NA	NA	1.00028715838792	NA
3	103.66	NA	NA	1.00037376459922	NA
4	103.77	NA	NA	1.00019650002369	NA
5	103.88	NA	NA	0.999670231989992	NA
6	103.91	NA	NA	0.99931323068568	NA
7	103.91	103.851834036343	103.9625	0.998935520368816	1.00056008605141
8	103.92	103.854535605669	104.02	0.998409302111791	1.00063034699399
9	104.05	104.017831576674	104.08625	0.9993426756817	1.00030925873803
10	104.23	104.246596397299	104.16	1.00083137862231	0.99984079674663
11	104.3	104.348868191934	104.232083333333	1.00112043101189	0.999531684504293
12	104.31	104.403088680647	104.3025	1.00096439376474	0.999108372349674
13	104.31	104.430469817485	104.3725	1.00055541275226	0.99884641122753
14	104.34	104.47249153993	104.4425	1.00028715838792	0.998731804535557
15	104.55	104.553647184686	104.514583333333	1.00037376459922	0.99996511661923
16	104.65	104.616386417061	104.595833333333	1.00019650002369	1.00032130323069
17	104.73	104.650478235872	104.685	0.999670231989992	1.0007598796056
18	104.75	104.704709267143	104.776666666667	0.99931323068568	1.00043255678922
19	104.75	104.758368021078	104.87	0.998935520368816	0.99992012073846
20	104.76	104.794704365157	104.961666666667	0.998409302111791	0.99966883474344
21	104.94	104.978033330892	105.047083333333	0.9993426756817	0.999637702005981
22	105.29	105.218236860712	105.130833333333	1.00083137862231	1.00068204088406
23	105.38	105.333303282429	105.215416666667	1.00112043101189	1.00044332339456
24	105.43	105.399465320940	105.297916666667	1.00096439376474	1.00028970430701
25	105.43	105.438946293922	105.380416666667	1.00055541275226	0.999915151903199
26	105.42	105.492784441486	105.4625	1.00028715838792	0.999310052892518
27	105.52	105.584865807027	105.545416666667	1.00037376459922	0.999385652417788
28	105.69	105.644921817919	105.624166666667	1.00019650002369	1.00042669520982
29	105.72	105.665976579869	105.700833333333	0.999670231989992	1.00051126599006
30	105.74	105.707353541931	105.78	0.99931323068568	1.00030883809853
31	105.74	105.745649293709	105.858333333333	0.998935520368816	0.999946576584978
32	105.74	105.768153434716	105.936666666667	0.998409302111791	0.999733819360536
33	105.95	105.944480976832	106.014166666667	0.9993426756817	1.00005209354104
34	106.17	106.165690565808	106.0775	1.00083137862231	1.00004059159008
35	106.34	106.242654340598	106.12375	1.00112043101189	1.00091625778748
36	106.37	106.267801932531	106.165416666667	1.00096439376474	1.00096170303338
37	106.37	106.265238305620	106.20625	1.00055541275226	1.00098585102759
38	106.36	106.277593074504	106.247083333333	1.00028715838792	1.00077539322365
39	106.44	106.323475103222	106.28375	1.00037376459922	1.00109594703018
40	106.29	106.332140163143	106.31125	1.00019650002369	0.999603693078324
41	106.23	106.291603533389	106.326666666667	0.999670231989992	0.999420428977066
42	106.23	106.262388765475	106.335416666667	0.99931323068568	0.999695200099952
43	106.23	106.232214136755	106.345416666667	0.998935520368816	0.999979157576887
44	106.23	106.190397368734	106.359583333333	0.998409302111791	1.00037293985376
45	106.34	106.29674927001	106.366666666667	0.9993426756817	1.00040688666669
46	106.44	106.456765691757	106.368333333333	1.00083137862231	0.999842511730956
47	106.44	106.491683047812	106.3725	1.00112043101189	0.999514675265402
48	106.48	106.475084975740	106.3725	1.00096439376474	1.00004616126168
49	106.5	106.429913050635	106.370833333333	1.00055541275226	1.00065852679342
50	106.57	106.400961824039	106.370416666667	1.00028715838792	1.00158869030001
51	106.4	106.404338649194	106.364583333333	1.00037376459922	0.999959224884537
52	106.37	106.364229800852	106.343333333333	1.00019650002369	1.0000542494329
53	106.25	106.280357243279	106.315416666667	0.999670231989992	0.999714366379012
54	106.21	106.213255864966	106.28625	0.99931323068568	0.99996934596403
55	106.21	NA	NA	0.998935520368816	NA
56	106.24	NA	NA	0.998409302111791	NA
57	106.19	NA	NA	0.9993426756817	NA
58	106.08	NA	NA	1.00083137862231	NA
59	106.13	NA	NA	1.00112043101189	NA
60	106.09	NA	NA	1.00096439376474	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 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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