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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 08:00:44 -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/Dec/04/t12599388902k23wnxquznn5kr.htm/, Retrieved Sat, 27 Apr 2024 19:00:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63700, Retrieved Sat, 27 Apr 2024 19:00:15 +0000

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No (this computation is public)

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Estimated Impact

105

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] [shw9] [2009-12-04 15:00:44] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
-             [Classical Decomposition] [workshop 9] [2009-12-04 18:58:48] [1433a524809eda02c3198b3ae6eebb69] 
-    D          [Classical Decomposition] [verbetering workshop] [2009-12-06 13:38:52] [1433a524809eda02c3198b3ae6eebb69] 

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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	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63700&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]1 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=63700&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63700&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	0.7461	NA	NA	1.00447820979037	NA
2	0.7775	NA	NA	0.987963294714205	NA
3	0.779	NA	NA	0.980072838319878	NA
4	0.7744	NA	NA	0.976032293476133	NA
5	0.7905	NA	NA	0.993203799768895	NA
6	0.7719	NA	NA	0.978112983912604	NA
7	0.7811	0.774374085534364	0.767441666666667	1.00903315413901	1.00868561408663
8	0.7557	0.783538502032904	0.765941666666667	1.02297411948199	0.964470792487317
9	0.7637	0.784150485167401	0.762445833333333	1.02846713941524	0.97392020338668
10	0.7595	0.787820559974768	0.759583333333333	1.03717462640672	0.964052017155181
11	0.7471	0.752316113535205	0.756429166666667	0.994562540271171	0.993066593362338
12	0.7615	0.74283727314509	0.751916666666667	0.987925000303789	1.02512357353299
13	0.7487	0.751814272095224	0.7484625	1.00447820979037	0.995857657654537
14	0.7389	0.738671339861715	0.747670833333333	0.987963294714205	1.00030955599053
15	0.7337	0.732261421150697	0.74715	0.980072838319878	1.00196457003981
16	0.751	0.728669109098275	0.7465625	0.976032293476133	1.03064613364681
17	0.7382	0.742395010232255	0.747475	0.993203799768895	0.994349355566193
18	0.7159	0.731200587536166	0.7475625	0.978112983912604	0.979074705632114
19	0.7542	0.754609648627666	0.747854166666666	1.00903315413901	0.999457138364967
20	0.7636	0.767874210828336	0.750629166666667	1.02297411948199	0.994433709625792
21	0.7433	0.776441266901534	0.75495	1.02846713941524	0.957316453524182
22	0.7658	0.786411731107233	0.758225	1.03717462640672	0.973790153056069
23	0.7627	0.757036141590909	0.761175	0.994562540271171	1.00748162220788
24	0.748	0.757783755128853	0.767045833333333	0.987925000303789	0.987088988035657
25	0.7692	0.777332203949773	0.773866666666667	1.00447820979037	0.9895383159112
26	0.785	0.77004329098262	0.779425	0.987963294714205	1.01942320541264
27	0.7913	0.770680276412836	0.78635	0.980072838319878	1.02675522420677
28	0.772	0.775506458781461	0.79455	0.976032293476133	0.995478491840067
29	0.788	0.795361741204097	0.800804166666667	0.993203799768895	0.99074415976691
30	0.807	0.791158913450008	0.8088625	0.978112983912604	1.02002263550431
31	0.8268	0.828239638746151	0.820825	1.00903315413901	0.998261808927268
32	0.8244	0.850504945329494	0.831404166666667	1.02297411948199	0.969306533168504
33	0.8487	0.863291031545404	0.839395833333333	1.02846713941524	0.983098363110197
34	0.8572	0.879532726314782	0.848008333333333	1.03717462640672	0.974608419167805
35	0.8214	0.854793351278396	0.859466666666667	0.994562540271171	0.960934006764964
36	0.8827	0.860186297764509	0.8707	0.987925000303789	1.02617305378382
37	0.9216	0.883719002344196	0.879779166666667	1.00447820979037	1.04286543296604
38	0.8865	0.879003292848412	0.8897125	0.987963294714205	1.00852864512861
39	0.8816	0.882004299935496	0.8999375	0.980072838319878	0.999541612285195
40	0.8884	0.886505731357034	0.908275	0.976032293476133	1.00213678104491
41	0.9466	0.907428236611354	0.9136375	0.993203799768895	1.04316789119868
42	0.918	0.891986060208333	0.911945833333333	0.978112983912604	1.02916406539536
43	0.9337	0.90602768632065	0.897916666666667	1.00903315413901	1.03054245923955
44	0.9559	0.89796241968913	0.877795833333333	1.02297411948199	1.06452116373748
45	0.9626	0.884867415074386	0.860375	1.02846713941524	1.08784658989740
46	0.9434	0.873629474066151	0.842316666666667	1.03717462640672	1.07986283430791
47	0.8639	0.815118593942745	0.819575	0.994562540271171	1.05984577755894
48	0.7996	0.787783744304745	0.7974125	0.987925000303789	1.01499936471231
49	0.668	NA	0.779166666666667	NA	NA
50	0.6572	NA	0.763670833333333	NA	NA
51	0.6928	NA	0.750508333333333	NA	NA
52	0.6438	NA	0.739404166666667	NA	NA
53	0.6454	NA	0.733575	NA	NA
54	0.6873	NA	NA	NA	NA
55	0.7265	NA	NA	NA	NA
56	0.7912	NA	NA	NA	NA
57	0.8114	NA	NA	NA	NA
58	0.8281	NA	NA	NA	NA
59	0.8393	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 0.7461 & NA & NA & 1.00447820979037 & NA \tabularnewline
2 & 0.7775 & NA & NA & 0.987963294714205 & NA \tabularnewline
3 & 0.779 & NA & NA & 0.980072838319878 & NA \tabularnewline
4 & 0.7744 & NA & NA & 0.976032293476133 & NA \tabularnewline
5 & 0.7905 & NA & NA & 0.993203799768895 & NA \tabularnewline
6 & 0.7719 & NA & NA & 0.978112983912604 & NA \tabularnewline
7 & 0.7811 & 0.774374085534364 & 0.767441666666667 & 1.00903315413901 & 1.00868561408663 \tabularnewline
8 & 0.7557 & 0.783538502032904 & 0.765941666666667 & 1.02297411948199 & 0.964470792487317 \tabularnewline
9 & 0.7637 & 0.784150485167401 & 0.762445833333333 & 1.02846713941524 & 0.97392020338668 \tabularnewline
10 & 0.7595 & 0.787820559974768 & 0.759583333333333 & 1.03717462640672 & 0.964052017155181 \tabularnewline
11 & 0.7471 & 0.752316113535205 & 0.756429166666667 & 0.994562540271171 & 0.993066593362338 \tabularnewline
12 & 0.7615 & 0.74283727314509 & 0.751916666666667 & 0.987925000303789 & 1.02512357353299 \tabularnewline
13 & 0.7487 & 0.751814272095224 & 0.7484625 & 1.00447820979037 & 0.995857657654537 \tabularnewline
14 & 0.7389 & 0.738671339861715 & 0.747670833333333 & 0.987963294714205 & 1.00030955599053 \tabularnewline
15 & 0.7337 & 0.732261421150697 & 0.74715 & 0.980072838319878 & 1.00196457003981 \tabularnewline
16 & 0.751 & 0.728669109098275 & 0.7465625 & 0.976032293476133 & 1.03064613364681 \tabularnewline
17 & 0.7382 & 0.742395010232255 & 0.747475 & 0.993203799768895 & 0.994349355566193 \tabularnewline
18 & 0.7159 & 0.731200587536166 & 0.7475625 & 0.978112983912604 & 0.979074705632114 \tabularnewline
19 & 0.7542 & 0.754609648627666 & 0.747854166666666 & 1.00903315413901 & 0.999457138364967 \tabularnewline
20 & 0.7636 & 0.767874210828336 & 0.750629166666667 & 1.02297411948199 & 0.994433709625792 \tabularnewline
21 & 0.7433 & 0.776441266901534 & 0.75495 & 1.02846713941524 & 0.957316453524182 \tabularnewline
22 & 0.7658 & 0.786411731107233 & 0.758225 & 1.03717462640672 & 0.973790153056069 \tabularnewline
23 & 0.7627 & 0.757036141590909 & 0.761175 & 0.994562540271171 & 1.00748162220788 \tabularnewline
24 & 0.748 & 0.757783755128853 & 0.767045833333333 & 0.987925000303789 & 0.987088988035657 \tabularnewline
25 & 0.7692 & 0.777332203949773 & 0.773866666666667 & 1.00447820979037 & 0.9895383159112 \tabularnewline
26 & 0.785 & 0.77004329098262 & 0.779425 & 0.987963294714205 & 1.01942320541264 \tabularnewline
27 & 0.7913 & 0.770680276412836 & 0.78635 & 0.980072838319878 & 1.02675522420677 \tabularnewline
28 & 0.772 & 0.775506458781461 & 0.79455 & 0.976032293476133 & 0.995478491840067 \tabularnewline
29 & 0.788 & 0.795361741204097 & 0.800804166666667 & 0.993203799768895 & 0.99074415976691 \tabularnewline
30 & 0.807 & 0.791158913450008 & 0.8088625 & 0.978112983912604 & 1.02002263550431 \tabularnewline
31 & 0.8268 & 0.828239638746151 & 0.820825 & 1.00903315413901 & 0.998261808927268 \tabularnewline
32 & 0.8244 & 0.850504945329494 & 0.831404166666667 & 1.02297411948199 & 0.969306533168504 \tabularnewline
33 & 0.8487 & 0.863291031545404 & 0.839395833333333 & 1.02846713941524 & 0.983098363110197 \tabularnewline
34 & 0.8572 & 0.879532726314782 & 0.848008333333333 & 1.03717462640672 & 0.974608419167805 \tabularnewline
35 & 0.8214 & 0.854793351278396 & 0.859466666666667 & 0.994562540271171 & 0.960934006764964 \tabularnewline
36 & 0.8827 & 0.860186297764509 & 0.8707 & 0.987925000303789 & 1.02617305378382 \tabularnewline
37 & 0.9216 & 0.883719002344196 & 0.879779166666667 & 1.00447820979037 & 1.04286543296604 \tabularnewline
38 & 0.8865 & 0.879003292848412 & 0.8897125 & 0.987963294714205 & 1.00852864512861 \tabularnewline
39 & 0.8816 & 0.882004299935496 & 0.8999375 & 0.980072838319878 & 0.999541612285195 \tabularnewline
40 & 0.8884 & 0.886505731357034 & 0.908275 & 0.976032293476133 & 1.00213678104491 \tabularnewline
41 & 0.9466 & 0.907428236611354 & 0.9136375 & 0.993203799768895 & 1.04316789119868 \tabularnewline
42 & 0.918 & 0.891986060208333 & 0.911945833333333 & 0.978112983912604 & 1.02916406539536 \tabularnewline
43 & 0.9337 & 0.90602768632065 & 0.897916666666667 & 1.00903315413901 & 1.03054245923955 \tabularnewline
44 & 0.9559 & 0.89796241968913 & 0.877795833333333 & 1.02297411948199 & 1.06452116373748 \tabularnewline
45 & 0.9626 & 0.884867415074386 & 0.860375 & 1.02846713941524 & 1.08784658989740 \tabularnewline
46 & 0.9434 & 0.873629474066151 & 0.842316666666667 & 1.03717462640672 & 1.07986283430791 \tabularnewline
47 & 0.8639 & 0.815118593942745 & 0.819575 & 0.994562540271171 & 1.05984577755894 \tabularnewline
48 & 0.7996 & 0.787783744304745 & 0.7974125 & 0.987925000303789 & 1.01499936471231 \tabularnewline
49 & 0.668 & NA & 0.779166666666667 & NA & NA \tabularnewline
50 & 0.6572 & NA & 0.763670833333333 & NA & NA \tabularnewline
51 & 0.6928 & NA & 0.750508333333333 & NA & NA \tabularnewline
52 & 0.6438 & NA & 0.739404166666667 & NA & NA \tabularnewline
53 & 0.6454 & NA & 0.733575 & NA & NA \tabularnewline
54 & 0.6873 & NA & NA & NA & NA \tabularnewline
55 & 0.7265 & NA & NA & NA & NA \tabularnewline
56 & 0.7912 & NA & NA & NA & NA \tabularnewline
57 & 0.8114 & NA & NA & NA & NA \tabularnewline
58 & 0.8281 & NA & NA & NA & NA \tabularnewline
59 & 0.8393 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63700&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]0.7461[/C][C]NA[/C][C]NA[/C][C]1.00447820979037[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]0.7775[/C][C]NA[/C][C]NA[/C][C]0.987963294714205[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]0.779[/C][C]NA[/C][C]NA[/C][C]0.980072838319878[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]0.7744[/C][C]NA[/C][C]NA[/C][C]0.976032293476133[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]0.7905[/C][C]NA[/C][C]NA[/C][C]0.993203799768895[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]0.7719[/C][C]NA[/C][C]NA[/C][C]0.978112983912604[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]0.7811[/C][C]0.774374085534364[/C][C]0.767441666666667[/C][C]1.00903315413901[/C][C]1.00868561408663[/C][/ROW]
[ROW][C]8[/C][C]0.7557[/C][C]0.783538502032904[/C][C]0.765941666666667[/C][C]1.02297411948199[/C][C]0.964470792487317[/C][/ROW]
[ROW][C]9[/C][C]0.7637[/C][C]0.784150485167401[/C][C]0.762445833333333[/C][C]1.02846713941524[/C][C]0.97392020338668[/C][/ROW]
[ROW][C]10[/C][C]0.7595[/C][C]0.787820559974768[/C][C]0.759583333333333[/C][C]1.03717462640672[/C][C]0.964052017155181[/C][/ROW]
[ROW][C]11[/C][C]0.7471[/C][C]0.752316113535205[/C][C]0.756429166666667[/C][C]0.994562540271171[/C][C]0.993066593362338[/C][/ROW]
[ROW][C]12[/C][C]0.7615[/C][C]0.74283727314509[/C][C]0.751916666666667[/C][C]0.987925000303789[/C][C]1.02512357353299[/C][/ROW]
[ROW][C]13[/C][C]0.7487[/C][C]0.751814272095224[/C][C]0.7484625[/C][C]1.00447820979037[/C][C]0.995857657654537[/C][/ROW]
[ROW][C]14[/C][C]0.7389[/C][C]0.738671339861715[/C][C]0.747670833333333[/C][C]0.987963294714205[/C][C]1.00030955599053[/C][/ROW]
[ROW][C]15[/C][C]0.7337[/C][C]0.732261421150697[/C][C]0.74715[/C][C]0.980072838319878[/C][C]1.00196457003981[/C][/ROW]
[ROW][C]16[/C][C]0.751[/C][C]0.728669109098275[/C][C]0.7465625[/C][C]0.976032293476133[/C][C]1.03064613364681[/C][/ROW]
[ROW][C]17[/C][C]0.7382[/C][C]0.742395010232255[/C][C]0.747475[/C][C]0.993203799768895[/C][C]0.994349355566193[/C][/ROW]
[ROW][C]18[/C][C]0.7159[/C][C]0.731200587536166[/C][C]0.7475625[/C][C]0.978112983912604[/C][C]0.979074705632114[/C][/ROW]
[ROW][C]19[/C][C]0.7542[/C][C]0.754609648627666[/C][C]0.747854166666666[/C][C]1.00903315413901[/C][C]0.999457138364967[/C][/ROW]
[ROW][C]20[/C][C]0.7636[/C][C]0.767874210828336[/C][C]0.750629166666667[/C][C]1.02297411948199[/C][C]0.994433709625792[/C][/ROW]
[ROW][C]21[/C][C]0.7433[/C][C]0.776441266901534[/C][C]0.75495[/C][C]1.02846713941524[/C][C]0.957316453524182[/C][/ROW]
[ROW][C]22[/C][C]0.7658[/C][C]0.786411731107233[/C][C]0.758225[/C][C]1.03717462640672[/C][C]0.973790153056069[/C][/ROW]
[ROW][C]23[/C][C]0.7627[/C][C]0.757036141590909[/C][C]0.761175[/C][C]0.994562540271171[/C][C]1.00748162220788[/C][/ROW]
[ROW][C]24[/C][C]0.748[/C][C]0.757783755128853[/C][C]0.767045833333333[/C][C]0.987925000303789[/C][C]0.987088988035657[/C][/ROW]
[ROW][C]25[/C][C]0.7692[/C][C]0.777332203949773[/C][C]0.773866666666667[/C][C]1.00447820979037[/C][C]0.9895383159112[/C][/ROW]
[ROW][C]26[/C][C]0.785[/C][C]0.77004329098262[/C][C]0.779425[/C][C]0.987963294714205[/C][C]1.01942320541264[/C][/ROW]
[ROW][C]27[/C][C]0.7913[/C][C]0.770680276412836[/C][C]0.78635[/C][C]0.980072838319878[/C][C]1.02675522420677[/C][/ROW]
[ROW][C]28[/C][C]0.772[/C][C]0.775506458781461[/C][C]0.79455[/C][C]0.976032293476133[/C][C]0.995478491840067[/C][/ROW]
[ROW][C]29[/C][C]0.788[/C][C]0.795361741204097[/C][C]0.800804166666667[/C][C]0.993203799768895[/C][C]0.99074415976691[/C][/ROW]
[ROW][C]30[/C][C]0.807[/C][C]0.791158913450008[/C][C]0.8088625[/C][C]0.978112983912604[/C][C]1.02002263550431[/C][/ROW]
[ROW][C]31[/C][C]0.8268[/C][C]0.828239638746151[/C][C]0.820825[/C][C]1.00903315413901[/C][C]0.998261808927268[/C][/ROW]
[ROW][C]32[/C][C]0.8244[/C][C]0.850504945329494[/C][C]0.831404166666667[/C][C]1.02297411948199[/C][C]0.969306533168504[/C][/ROW]
[ROW][C]33[/C][C]0.8487[/C][C]0.863291031545404[/C][C]0.839395833333333[/C][C]1.02846713941524[/C][C]0.983098363110197[/C][/ROW]
[ROW][C]34[/C][C]0.8572[/C][C]0.879532726314782[/C][C]0.848008333333333[/C][C]1.03717462640672[/C][C]0.974608419167805[/C][/ROW]
[ROW][C]35[/C][C]0.8214[/C][C]0.854793351278396[/C][C]0.859466666666667[/C][C]0.994562540271171[/C][C]0.960934006764964[/C][/ROW]
[ROW][C]36[/C][C]0.8827[/C][C]0.860186297764509[/C][C]0.8707[/C][C]0.987925000303789[/C][C]1.02617305378382[/C][/ROW]
[ROW][C]37[/C][C]0.9216[/C][C]0.883719002344196[/C][C]0.879779166666667[/C][C]1.00447820979037[/C][C]1.04286543296604[/C][/ROW]
[ROW][C]38[/C][C]0.8865[/C][C]0.879003292848412[/C][C]0.8897125[/C][C]0.987963294714205[/C][C]1.00852864512861[/C][/ROW]
[ROW][C]39[/C][C]0.8816[/C][C]0.882004299935496[/C][C]0.8999375[/C][C]0.980072838319878[/C][C]0.999541612285195[/C][/ROW]
[ROW][C]40[/C][C]0.8884[/C][C]0.886505731357034[/C][C]0.908275[/C][C]0.976032293476133[/C][C]1.00213678104491[/C][/ROW]
[ROW][C]41[/C][C]0.9466[/C][C]0.907428236611354[/C][C]0.9136375[/C][C]0.993203799768895[/C][C]1.04316789119868[/C][/ROW]
[ROW][C]42[/C][C]0.918[/C][C]0.891986060208333[/C][C]0.911945833333333[/C][C]0.978112983912604[/C][C]1.02916406539536[/C][/ROW]
[ROW][C]43[/C][C]0.9337[/C][C]0.90602768632065[/C][C]0.897916666666667[/C][C]1.00903315413901[/C][C]1.03054245923955[/C][/ROW]
[ROW][C]44[/C][C]0.9559[/C][C]0.89796241968913[/C][C]0.877795833333333[/C][C]1.02297411948199[/C][C]1.06452116373748[/C][/ROW]
[ROW][C]45[/C][C]0.9626[/C][C]0.884867415074386[/C][C]0.860375[/C][C]1.02846713941524[/C][C]1.08784658989740[/C][/ROW]
[ROW][C]46[/C][C]0.9434[/C][C]0.873629474066151[/C][C]0.842316666666667[/C][C]1.03717462640672[/C][C]1.07986283430791[/C][/ROW]
[ROW][C]47[/C][C]0.8639[/C][C]0.815118593942745[/C][C]0.819575[/C][C]0.994562540271171[/C][C]1.05984577755894[/C][/ROW]
[ROW][C]48[/C][C]0.7996[/C][C]0.787783744304745[/C][C]0.7974125[/C][C]0.987925000303789[/C][C]1.01499936471231[/C][/ROW]
[ROW][C]49[/C][C]0.668[/C][C]NA[/C][C]0.779166666666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]0.6572[/C][C]NA[/C][C]0.763670833333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]0.6928[/C][C]NA[/C][C]0.750508333333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]0.6438[/C][C]NA[/C][C]0.739404166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]0.6454[/C][C]NA[/C][C]0.733575[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]0.6873[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]0.7265[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]0.7912[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]0.8114[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]0.8281[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]0.8393[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63700&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63700&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	0.7461	NA	NA	1.00447820979037	NA
2	0.7775	NA	NA	0.987963294714205	NA
3	0.779	NA	NA	0.980072838319878	NA
4	0.7744	NA	NA	0.976032293476133	NA
5	0.7905	NA	NA	0.993203799768895	NA
6	0.7719	NA	NA	0.978112983912604	NA
7	0.7811	0.774374085534364	0.767441666666667	1.00903315413901	1.00868561408663
8	0.7557	0.783538502032904	0.765941666666667	1.02297411948199	0.964470792487317
9	0.7637	0.784150485167401	0.762445833333333	1.02846713941524	0.97392020338668
10	0.7595	0.787820559974768	0.759583333333333	1.03717462640672	0.964052017155181
11	0.7471	0.752316113535205	0.756429166666667	0.994562540271171	0.993066593362338
12	0.7615	0.74283727314509	0.751916666666667	0.987925000303789	1.02512357353299
13	0.7487	0.751814272095224	0.7484625	1.00447820979037	0.995857657654537
14	0.7389	0.738671339861715	0.747670833333333	0.987963294714205	1.00030955599053
15	0.7337	0.732261421150697	0.74715	0.980072838319878	1.00196457003981
16	0.751	0.728669109098275	0.7465625	0.976032293476133	1.03064613364681
17	0.7382	0.742395010232255	0.747475	0.993203799768895	0.994349355566193
18	0.7159	0.731200587536166	0.7475625	0.978112983912604	0.979074705632114
19	0.7542	0.754609648627666	0.747854166666666	1.00903315413901	0.999457138364967
20	0.7636	0.767874210828336	0.750629166666667	1.02297411948199	0.994433709625792
21	0.7433	0.776441266901534	0.75495	1.02846713941524	0.957316453524182
22	0.7658	0.786411731107233	0.758225	1.03717462640672	0.973790153056069
23	0.7627	0.757036141590909	0.761175	0.994562540271171	1.00748162220788
24	0.748	0.757783755128853	0.767045833333333	0.987925000303789	0.987088988035657
25	0.7692	0.777332203949773	0.773866666666667	1.00447820979037	0.9895383159112
26	0.785	0.77004329098262	0.779425	0.987963294714205	1.01942320541264
27	0.7913	0.770680276412836	0.78635	0.980072838319878	1.02675522420677
28	0.772	0.775506458781461	0.79455	0.976032293476133	0.995478491840067
29	0.788	0.795361741204097	0.800804166666667	0.993203799768895	0.99074415976691
30	0.807	0.791158913450008	0.8088625	0.978112983912604	1.02002263550431
31	0.8268	0.828239638746151	0.820825	1.00903315413901	0.998261808927268
32	0.8244	0.850504945329494	0.831404166666667	1.02297411948199	0.969306533168504
33	0.8487	0.863291031545404	0.839395833333333	1.02846713941524	0.983098363110197
34	0.8572	0.879532726314782	0.848008333333333	1.03717462640672	0.974608419167805
35	0.8214	0.854793351278396	0.859466666666667	0.994562540271171	0.960934006764964
36	0.8827	0.860186297764509	0.8707	0.987925000303789	1.02617305378382
37	0.9216	0.883719002344196	0.879779166666667	1.00447820979037	1.04286543296604
38	0.8865	0.879003292848412	0.8897125	0.987963294714205	1.00852864512861
39	0.8816	0.882004299935496	0.8999375	0.980072838319878	0.999541612285195
40	0.8884	0.886505731357034	0.908275	0.976032293476133	1.00213678104491
41	0.9466	0.907428236611354	0.9136375	0.993203799768895	1.04316789119868
42	0.918	0.891986060208333	0.911945833333333	0.978112983912604	1.02916406539536
43	0.9337	0.90602768632065	0.897916666666667	1.00903315413901	1.03054245923955
44	0.9559	0.89796241968913	0.877795833333333	1.02297411948199	1.06452116373748
45	0.9626	0.884867415074386	0.860375	1.02846713941524	1.08784658989740
46	0.9434	0.873629474066151	0.842316666666667	1.03717462640672	1.07986283430791
47	0.8639	0.815118593942745	0.819575	0.994562540271171	1.05984577755894
48	0.7996	0.787783744304745	0.7974125	0.987925000303789	1.01499936471231
49	0.668	NA	0.779166666666667	NA	NA
50	0.6572	NA	0.763670833333333	NA	NA
51	0.6928	NA	0.750508333333333	NA	NA
52	0.6438	NA	0.739404166666667	NA	NA
53	0.6454	NA	0.733575	NA	NA
54	0.6873	NA	NA	NA	NA
55	0.7265	NA	NA	NA	NA
56	0.7912	NA	NA	NA	NA
57	0.8114	NA	NA	NA	NA
58	0.8281	NA	NA	NA	NA
59	0.8393	NA	NA	NA	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