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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 03:22:32 -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/t1259922202jlj8l2laiwlbf5l.htm/, Retrieved Sun, 28 Apr 2024 17:15:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63242, Retrieved Sun, 28 Apr 2024 17:15:20 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

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] [workshop 9 - ad h...] [2009-12-04 10:22:32] [a18540c86166a2b66550d1fef0503cc2] [Current]
-    D        [Classical Decomposition] [WS9] [2009-12-06 15:00:53] [9f35ad889e41dd0c9322ca60d75b9f47] 
-    D        [Classical Decomposition] [workshop 9 - revi...] [2009-12-11 12:05:10] [f1a50df816abcbb519e7637ff6b72fa0] 

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Dataseries X:

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Histogram

Boxplots

8,6
8,5
8,3
7,8
7,8
8
8,6
8,9
8,9
8,6
8,3
8,3
8,3
8,4
8,5
8,4
8,6
8,5
8,5
8,4
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,6
8,4
8,1
8
8
8
8
7,9
7,8
7,8
7,9
8,1
8
7,6
7,3
7
6,8
7
7,1
7,2
7,1
6,9
6,7
6,7
6,6
6,9
7,3
7,5
7,3
7,1
6,9
7,1

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=63242&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=63242&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63242&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	8.6	NA	NA	0.996702710921287	NA
2	8.5	NA	NA	0.995771473511747	NA
3	8.3	NA	NA	0.998520165033688	NA
4	7.8	NA	NA	1.00619273018036	NA
5	7.8	NA	NA	1.01232015874663	NA
6	8	NA	NA	1.00437744260445	NA
7	8.6	8.3640673297507	8.37083333333333	0.999191716844284	1.02820788749633
8	8.9	8.32165964665616	8.35416666666667	0.996108885385276	1.06949819842443
9	8.9	8.32843497316147	8.35833333333333	0.99642292799539	1.06862814306414
10	8.6	8.37548837152225	8.39166666666667	0.998072099883485	1.02680579549739
11	8.3	8.41760187683547	8.45	0.99616590258408	0.986029052150934
12	8.3	8.5054744910722	8.50416666666667	1.00015378630932	0.975842089552103
13	8.3	8.4927376826418	8.52083333333333	0.996702710921287	0.9773055886283
14	8.4	8.45990847704355	8.49583333333333	0.995771473511747	0.992918543125364
15	8.5	8.44581639590994	8.45833333333333	0.998520165033688	1.00641543712888
16	8.4	8.48975116089679	8.4375	1.00619273018036	0.98942829310355
17	8.6	8.54566934008615	8.44166666666667	1.01232015874663	1.00635768337759
18	8.5	8.49535920202928	8.45833333333333	1.00437744260445	1.00054627448473
19	8.5	8.4681498002553	8.475	0.999191716844284	1.00376117575810
20	8.4	8.45447416470753	8.4875	0.996108885385276	0.993556764897937
21	8.5	8.46129136356085	8.49166666666667	0.99642292799539	1.00457479062899
22	8.5	8.4794542152601	8.49583333333333	0.998072099883485	1.00242300792225
23	8.5	8.46741017196467	8.5	0.99616590258408	1.00384885429824
24	8.5	8.49713987618628	8.49583333333333	1.00015378630932	1.00033659841492
25	8.5	8.4470554750579	8.475	0.996702710921287	1.00626780836215
26	8.5	8.40597085556167	8.44166666666666	0.995771473511747	1.01118599458100
27	8.5	8.39172988697062	8.40416666666667	0.998520165033688	1.01290200167161
28	8.5	8.41428670613326	8.3625	1.00619273018036	1.01018663813823
29	8.6	8.42334732090427	8.32083333333333	1.01232015874663	1.02097179094792
30	8.4	8.3112233375518	8.275	1.00437744260445	1.01068153974964
31	8.1	8.21418857222405	8.22083333333333	0.999191716844284	0.98609861811425
32	8	8.13073877695731	8.1625	0.996108885385276	0.983920430782031
33	8	8.07932924116262	8.10833333333333	0.99642292799539	0.990181209504564
34	8	8.05111493906011	8.06666666666667	0.998072099883485	0.99365119744942
35	8	7.99423136823724	8.025	0.99616590258408	1.00072159930043
36	7.9	7.96789183093094	7.96666666666667	1.00015378630932	0.991479323217293
37	7.8	7.87395141627817	7.9	0.996702710921287	0.99060809339955
38	7.8	7.79191178022942	7.825	0.995771473511747	1.00103802763670
39	7.9	7.72188927626052	7.73333333333333	0.998520165033688	1.02306569252256
40	8.1	7.68898944646159	7.64166666666667	1.00619273018036	1.05345443070254
41	8	7.6556712005214	7.5625	1.01232015874663	1.04497695766442
42	7.6	7.5286459135225	7.49583333333333	1.00437744260445	1.00947767862868
43	7.3	7.43148839402936	7.4375	0.999191716844284	0.982306586909965
44	7	7.3421525760273	7.37083333333333	0.996108885385276	0.95339887417425
45	6.8	7.25728032556642	7.28333333333333	0.99642292799539	0.93699012508095
46	7	7.161167316664	7.175	0.998072099883485	0.977494267409592
47	7.1	7.0312709957393	7.05833333333333	0.99616590258408	1.00977476252904
48	7.2	6.97190535206457	6.97083333333333	1.00015378630932	1.03271625709432
49	7.1	6.9187779849786	6.94166666666667	0.996702710921287	1.02619277788865
50	6.9	6.93305888432554	6.9625	0.995771473511747	0.995231702935586
51	6.7	6.99380165592345	7.00416666666667	0.998520165033688	0.95799113695559
52	6.7	7.07269639922612	7.02916666666667	1.00619273018036	0.947304906334323
53	6.6	7.11154911519509	7.025	1.01232015874663	0.92806783628871
54	6.9	7.04319681626368	7.0125	1.00437744260445	0.979668775415587
55	7.3	NA	NA	0.999191716844284	NA
56	7.5	NA	NA	0.996108885385276	NA
57	7.3	NA	NA	0.99642292799539	NA
58	7.1	NA	NA	0.998072099883485	NA
59	6.9	NA	NA	0.99616590258408	NA
60	7.1	NA	NA	1.00015378630932	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.6 & NA & NA & 0.996702710921287 & NA \tabularnewline
2 & 8.5 & NA & NA & 0.995771473511747 & NA \tabularnewline
3 & 8.3 & NA & NA & 0.998520165033688 & NA \tabularnewline
4 & 7.8 & NA & NA & 1.00619273018036 & NA \tabularnewline
5 & 7.8 & NA & NA & 1.01232015874663 & NA \tabularnewline
6 & 8 & NA & NA & 1.00437744260445 & NA \tabularnewline
7 & 8.6 & 8.3640673297507 & 8.37083333333333 & 0.999191716844284 & 1.02820788749633 \tabularnewline
8 & 8.9 & 8.32165964665616 & 8.35416666666667 & 0.996108885385276 & 1.06949819842443 \tabularnewline
9 & 8.9 & 8.32843497316147 & 8.35833333333333 & 0.99642292799539 & 1.06862814306414 \tabularnewline
10 & 8.6 & 8.37548837152225 & 8.39166666666667 & 0.998072099883485 & 1.02680579549739 \tabularnewline
11 & 8.3 & 8.41760187683547 & 8.45 & 0.99616590258408 & 0.986029052150934 \tabularnewline
12 & 8.3 & 8.5054744910722 & 8.50416666666667 & 1.00015378630932 & 0.975842089552103 \tabularnewline
13 & 8.3 & 8.4927376826418 & 8.52083333333333 & 0.996702710921287 & 0.9773055886283 \tabularnewline
14 & 8.4 & 8.45990847704355 & 8.49583333333333 & 0.995771473511747 & 0.992918543125364 \tabularnewline
15 & 8.5 & 8.44581639590994 & 8.45833333333333 & 0.998520165033688 & 1.00641543712888 \tabularnewline
16 & 8.4 & 8.48975116089679 & 8.4375 & 1.00619273018036 & 0.98942829310355 \tabularnewline
17 & 8.6 & 8.54566934008615 & 8.44166666666667 & 1.01232015874663 & 1.00635768337759 \tabularnewline
18 & 8.5 & 8.49535920202928 & 8.45833333333333 & 1.00437744260445 & 1.00054627448473 \tabularnewline
19 & 8.5 & 8.4681498002553 & 8.475 & 0.999191716844284 & 1.00376117575810 \tabularnewline
20 & 8.4 & 8.45447416470753 & 8.4875 & 0.996108885385276 & 0.993556764897937 \tabularnewline
21 & 8.5 & 8.46129136356085 & 8.49166666666667 & 0.99642292799539 & 1.00457479062899 \tabularnewline
22 & 8.5 & 8.4794542152601 & 8.49583333333333 & 0.998072099883485 & 1.00242300792225 \tabularnewline
23 & 8.5 & 8.46741017196467 & 8.5 & 0.99616590258408 & 1.00384885429824 \tabularnewline
24 & 8.5 & 8.49713987618628 & 8.49583333333333 & 1.00015378630932 & 1.00033659841492 \tabularnewline
25 & 8.5 & 8.4470554750579 & 8.475 & 0.996702710921287 & 1.00626780836215 \tabularnewline
26 & 8.5 & 8.40597085556167 & 8.44166666666666 & 0.995771473511747 & 1.01118599458100 \tabularnewline
27 & 8.5 & 8.39172988697062 & 8.40416666666667 & 0.998520165033688 & 1.01290200167161 \tabularnewline
28 & 8.5 & 8.41428670613326 & 8.3625 & 1.00619273018036 & 1.01018663813823 \tabularnewline
29 & 8.6 & 8.42334732090427 & 8.32083333333333 & 1.01232015874663 & 1.02097179094792 \tabularnewline
30 & 8.4 & 8.3112233375518 & 8.275 & 1.00437744260445 & 1.01068153974964 \tabularnewline
31 & 8.1 & 8.21418857222405 & 8.22083333333333 & 0.999191716844284 & 0.98609861811425 \tabularnewline
32 & 8 & 8.13073877695731 & 8.1625 & 0.996108885385276 & 0.983920430782031 \tabularnewline
33 & 8 & 8.07932924116262 & 8.10833333333333 & 0.99642292799539 & 0.990181209504564 \tabularnewline
34 & 8 & 8.05111493906011 & 8.06666666666667 & 0.998072099883485 & 0.99365119744942 \tabularnewline
35 & 8 & 7.99423136823724 & 8.025 & 0.99616590258408 & 1.00072159930043 \tabularnewline
36 & 7.9 & 7.96789183093094 & 7.96666666666667 & 1.00015378630932 & 0.991479323217293 \tabularnewline
37 & 7.8 & 7.87395141627817 & 7.9 & 0.996702710921287 & 0.99060809339955 \tabularnewline
38 & 7.8 & 7.79191178022942 & 7.825 & 0.995771473511747 & 1.00103802763670 \tabularnewline
39 & 7.9 & 7.72188927626052 & 7.73333333333333 & 0.998520165033688 & 1.02306569252256 \tabularnewline
40 & 8.1 & 7.68898944646159 & 7.64166666666667 & 1.00619273018036 & 1.05345443070254 \tabularnewline
41 & 8 & 7.6556712005214 & 7.5625 & 1.01232015874663 & 1.04497695766442 \tabularnewline
42 & 7.6 & 7.5286459135225 & 7.49583333333333 & 1.00437744260445 & 1.00947767862868 \tabularnewline
43 & 7.3 & 7.43148839402936 & 7.4375 & 0.999191716844284 & 0.982306586909965 \tabularnewline
44 & 7 & 7.3421525760273 & 7.37083333333333 & 0.996108885385276 & 0.95339887417425 \tabularnewline
45 & 6.8 & 7.25728032556642 & 7.28333333333333 & 0.99642292799539 & 0.93699012508095 \tabularnewline
46 & 7 & 7.161167316664 & 7.175 & 0.998072099883485 & 0.977494267409592 \tabularnewline
47 & 7.1 & 7.0312709957393 & 7.05833333333333 & 0.99616590258408 & 1.00977476252904 \tabularnewline
48 & 7.2 & 6.97190535206457 & 6.97083333333333 & 1.00015378630932 & 1.03271625709432 \tabularnewline
49 & 7.1 & 6.9187779849786 & 6.94166666666667 & 0.996702710921287 & 1.02619277788865 \tabularnewline
50 & 6.9 & 6.93305888432554 & 6.9625 & 0.995771473511747 & 0.995231702935586 \tabularnewline
51 & 6.7 & 6.99380165592345 & 7.00416666666667 & 0.998520165033688 & 0.95799113695559 \tabularnewline
52 & 6.7 & 7.07269639922612 & 7.02916666666667 & 1.00619273018036 & 0.947304906334323 \tabularnewline
53 & 6.6 & 7.11154911519509 & 7.025 & 1.01232015874663 & 0.92806783628871 \tabularnewline
54 & 6.9 & 7.04319681626368 & 7.0125 & 1.00437744260445 & 0.979668775415587 \tabularnewline
55 & 7.3 & NA & NA & 0.999191716844284 & NA \tabularnewline
56 & 7.5 & NA & NA & 0.996108885385276 & NA \tabularnewline
57 & 7.3 & NA & NA & 0.99642292799539 & NA \tabularnewline
58 & 7.1 & NA & NA & 0.998072099883485 & NA \tabularnewline
59 & 6.9 & NA & NA & 0.99616590258408 & NA \tabularnewline
60 & 7.1 & NA & NA & 1.00015378630932 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63242&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]8.6[/C][C]NA[/C][C]NA[/C][C]0.996702710921287[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]0.995771473511747[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]0.998520165033688[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]7.8[/C][C]NA[/C][C]NA[/C][C]1.00619273018036[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]7.8[/C][C]NA[/C][C]NA[/C][C]1.01232015874663[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]8[/C][C]NA[/C][C]NA[/C][C]1.00437744260445[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.6[/C][C]8.3640673297507[/C][C]8.37083333333333[/C][C]0.999191716844284[/C][C]1.02820788749633[/C][/ROW]
[ROW][C]8[/C][C]8.9[/C][C]8.32165964665616[/C][C]8.35416666666667[/C][C]0.996108885385276[/C][C]1.06949819842443[/C][/ROW]
[ROW][C]9[/C][C]8.9[/C][C]8.32843497316147[/C][C]8.35833333333333[/C][C]0.99642292799539[/C][C]1.06862814306414[/C][/ROW]
[ROW][C]10[/C][C]8.6[/C][C]8.37548837152225[/C][C]8.39166666666667[/C][C]0.998072099883485[/C][C]1.02680579549739[/C][/ROW]
[ROW][C]11[/C][C]8.3[/C][C]8.41760187683547[/C][C]8.45[/C][C]0.99616590258408[/C][C]0.986029052150934[/C][/ROW]
[ROW][C]12[/C][C]8.3[/C][C]8.5054744910722[/C][C]8.50416666666667[/C][C]1.00015378630932[/C][C]0.975842089552103[/C][/ROW]
[ROW][C]13[/C][C]8.3[/C][C]8.4927376826418[/C][C]8.52083333333333[/C][C]0.996702710921287[/C][C]0.9773055886283[/C][/ROW]
[ROW][C]14[/C][C]8.4[/C][C]8.45990847704355[/C][C]8.49583333333333[/C][C]0.995771473511747[/C][C]0.992918543125364[/C][/ROW]
[ROW][C]15[/C][C]8.5[/C][C]8.44581639590994[/C][C]8.45833333333333[/C][C]0.998520165033688[/C][C]1.00641543712888[/C][/ROW]
[ROW][C]16[/C][C]8.4[/C][C]8.48975116089679[/C][C]8.4375[/C][C]1.00619273018036[/C][C]0.98942829310355[/C][/ROW]
[ROW][C]17[/C][C]8.6[/C][C]8.54566934008615[/C][C]8.44166666666667[/C][C]1.01232015874663[/C][C]1.00635768337759[/C][/ROW]
[ROW][C]18[/C][C]8.5[/C][C]8.49535920202928[/C][C]8.45833333333333[/C][C]1.00437744260445[/C][C]1.00054627448473[/C][/ROW]
[ROW][C]19[/C][C]8.5[/C][C]8.4681498002553[/C][C]8.475[/C][C]0.999191716844284[/C][C]1.00376117575810[/C][/ROW]
[ROW][C]20[/C][C]8.4[/C][C]8.45447416470753[/C][C]8.4875[/C][C]0.996108885385276[/C][C]0.993556764897937[/C][/ROW]
[ROW][C]21[/C][C]8.5[/C][C]8.46129136356085[/C][C]8.49166666666667[/C][C]0.99642292799539[/C][C]1.00457479062899[/C][/ROW]
[ROW][C]22[/C][C]8.5[/C][C]8.4794542152601[/C][C]8.49583333333333[/C][C]0.998072099883485[/C][C]1.00242300792225[/C][/ROW]
[ROW][C]23[/C][C]8.5[/C][C]8.46741017196467[/C][C]8.5[/C][C]0.99616590258408[/C][C]1.00384885429824[/C][/ROW]
[ROW][C]24[/C][C]8.5[/C][C]8.49713987618628[/C][C]8.49583333333333[/C][C]1.00015378630932[/C][C]1.00033659841492[/C][/ROW]
[ROW][C]25[/C][C]8.5[/C][C]8.4470554750579[/C][C]8.475[/C][C]0.996702710921287[/C][C]1.00626780836215[/C][/ROW]
[ROW][C]26[/C][C]8.5[/C][C]8.40597085556167[/C][C]8.44166666666666[/C][C]0.995771473511747[/C][C]1.01118599458100[/C][/ROW]
[ROW][C]27[/C][C]8.5[/C][C]8.39172988697062[/C][C]8.40416666666667[/C][C]0.998520165033688[/C][C]1.01290200167161[/C][/ROW]
[ROW][C]28[/C][C]8.5[/C][C]8.41428670613326[/C][C]8.3625[/C][C]1.00619273018036[/C][C]1.01018663813823[/C][/ROW]
[ROW][C]29[/C][C]8.6[/C][C]8.42334732090427[/C][C]8.32083333333333[/C][C]1.01232015874663[/C][C]1.02097179094792[/C][/ROW]
[ROW][C]30[/C][C]8.4[/C][C]8.3112233375518[/C][C]8.275[/C][C]1.00437744260445[/C][C]1.01068153974964[/C][/ROW]
[ROW][C]31[/C][C]8.1[/C][C]8.21418857222405[/C][C]8.22083333333333[/C][C]0.999191716844284[/C][C]0.98609861811425[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]8.13073877695731[/C][C]8.1625[/C][C]0.996108885385276[/C][C]0.983920430782031[/C][/ROW]
[ROW][C]33[/C][C]8[/C][C]8.07932924116262[/C][C]8.10833333333333[/C][C]0.99642292799539[/C][C]0.990181209504564[/C][/ROW]
[ROW][C]34[/C][C]8[/C][C]8.05111493906011[/C][C]8.06666666666667[/C][C]0.998072099883485[/C][C]0.99365119744942[/C][/ROW]
[ROW][C]35[/C][C]8[/C][C]7.99423136823724[/C][C]8.025[/C][C]0.99616590258408[/C][C]1.00072159930043[/C][/ROW]
[ROW][C]36[/C][C]7.9[/C][C]7.96789183093094[/C][C]7.96666666666667[/C][C]1.00015378630932[/C][C]0.991479323217293[/C][/ROW]
[ROW][C]37[/C][C]7.8[/C][C]7.87395141627817[/C][C]7.9[/C][C]0.996702710921287[/C][C]0.99060809339955[/C][/ROW]
[ROW][C]38[/C][C]7.8[/C][C]7.79191178022942[/C][C]7.825[/C][C]0.995771473511747[/C][C]1.00103802763670[/C][/ROW]
[ROW][C]39[/C][C]7.9[/C][C]7.72188927626052[/C][C]7.73333333333333[/C][C]0.998520165033688[/C][C]1.02306569252256[/C][/ROW]
[ROW][C]40[/C][C]8.1[/C][C]7.68898944646159[/C][C]7.64166666666667[/C][C]1.00619273018036[/C][C]1.05345443070254[/C][/ROW]
[ROW][C]41[/C][C]8[/C][C]7.6556712005214[/C][C]7.5625[/C][C]1.01232015874663[/C][C]1.04497695766442[/C][/ROW]
[ROW][C]42[/C][C]7.6[/C][C]7.5286459135225[/C][C]7.49583333333333[/C][C]1.00437744260445[/C][C]1.00947767862868[/C][/ROW]
[ROW][C]43[/C][C]7.3[/C][C]7.43148839402936[/C][C]7.4375[/C][C]0.999191716844284[/C][C]0.982306586909965[/C][/ROW]
[ROW][C]44[/C][C]7[/C][C]7.3421525760273[/C][C]7.37083333333333[/C][C]0.996108885385276[/C][C]0.95339887417425[/C][/ROW]
[ROW][C]45[/C][C]6.8[/C][C]7.25728032556642[/C][C]7.28333333333333[/C][C]0.99642292799539[/C][C]0.93699012508095[/C][/ROW]
[ROW][C]46[/C][C]7[/C][C]7.161167316664[/C][C]7.175[/C][C]0.998072099883485[/C][C]0.977494267409592[/C][/ROW]
[ROW][C]47[/C][C]7.1[/C][C]7.0312709957393[/C][C]7.05833333333333[/C][C]0.99616590258408[/C][C]1.00977476252904[/C][/ROW]
[ROW][C]48[/C][C]7.2[/C][C]6.97190535206457[/C][C]6.97083333333333[/C][C]1.00015378630932[/C][C]1.03271625709432[/C][/ROW]
[ROW][C]49[/C][C]7.1[/C][C]6.9187779849786[/C][C]6.94166666666667[/C][C]0.996702710921287[/C][C]1.02619277788865[/C][/ROW]
[ROW][C]50[/C][C]6.9[/C][C]6.93305888432554[/C][C]6.9625[/C][C]0.995771473511747[/C][C]0.995231702935586[/C][/ROW]
[ROW][C]51[/C][C]6.7[/C][C]6.99380165592345[/C][C]7.00416666666667[/C][C]0.998520165033688[/C][C]0.95799113695559[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.07269639922612[/C][C]7.02916666666667[/C][C]1.00619273018036[/C][C]0.947304906334323[/C][/ROW]
[ROW][C]53[/C][C]6.6[/C][C]7.11154911519509[/C][C]7.025[/C][C]1.01232015874663[/C][C]0.92806783628871[/C][/ROW]
[ROW][C]54[/C][C]6.9[/C][C]7.04319681626368[/C][C]7.0125[/C][C]1.00437744260445[/C][C]0.979668775415587[/C][/ROW]
[ROW][C]55[/C][C]7.3[/C][C]NA[/C][C]NA[/C][C]0.999191716844284[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]7.5[/C][C]NA[/C][C]NA[/C][C]0.996108885385276[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]7.3[/C][C]NA[/C][C]NA[/C][C]0.99642292799539[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]7.1[/C][C]NA[/C][C]NA[/C][C]0.998072099883485[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]6.9[/C][C]NA[/C][C]NA[/C][C]0.99616590258408[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]7.1[/C][C]NA[/C][C]NA[/C][C]1.00015378630932[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63242&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63242&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	8.6	NA	NA	0.996702710921287	NA
2	8.5	NA	NA	0.995771473511747	NA
3	8.3	NA	NA	0.998520165033688	NA
4	7.8	NA	NA	1.00619273018036	NA
5	7.8	NA	NA	1.01232015874663	NA
6	8	NA	NA	1.00437744260445	NA
7	8.6	8.3640673297507	8.37083333333333	0.999191716844284	1.02820788749633
8	8.9	8.32165964665616	8.35416666666667	0.996108885385276	1.06949819842443
9	8.9	8.32843497316147	8.35833333333333	0.99642292799539	1.06862814306414
10	8.6	8.37548837152225	8.39166666666667	0.998072099883485	1.02680579549739
11	8.3	8.41760187683547	8.45	0.99616590258408	0.986029052150934
12	8.3	8.5054744910722	8.50416666666667	1.00015378630932	0.975842089552103
13	8.3	8.4927376826418	8.52083333333333	0.996702710921287	0.9773055886283
14	8.4	8.45990847704355	8.49583333333333	0.995771473511747	0.992918543125364
15	8.5	8.44581639590994	8.45833333333333	0.998520165033688	1.00641543712888
16	8.4	8.48975116089679	8.4375	1.00619273018036	0.98942829310355
17	8.6	8.54566934008615	8.44166666666667	1.01232015874663	1.00635768337759
18	8.5	8.49535920202928	8.45833333333333	1.00437744260445	1.00054627448473
19	8.5	8.4681498002553	8.475	0.999191716844284	1.00376117575810
20	8.4	8.45447416470753	8.4875	0.996108885385276	0.993556764897937
21	8.5	8.46129136356085	8.49166666666667	0.99642292799539	1.00457479062899
22	8.5	8.4794542152601	8.49583333333333	0.998072099883485	1.00242300792225
23	8.5	8.46741017196467	8.5	0.99616590258408	1.00384885429824
24	8.5	8.49713987618628	8.49583333333333	1.00015378630932	1.00033659841492
25	8.5	8.4470554750579	8.475	0.996702710921287	1.00626780836215
26	8.5	8.40597085556167	8.44166666666666	0.995771473511747	1.01118599458100
27	8.5	8.39172988697062	8.40416666666667	0.998520165033688	1.01290200167161
28	8.5	8.41428670613326	8.3625	1.00619273018036	1.01018663813823
29	8.6	8.42334732090427	8.32083333333333	1.01232015874663	1.02097179094792
30	8.4	8.3112233375518	8.275	1.00437744260445	1.01068153974964
31	8.1	8.21418857222405	8.22083333333333	0.999191716844284	0.98609861811425
32	8	8.13073877695731	8.1625	0.996108885385276	0.983920430782031
33	8	8.07932924116262	8.10833333333333	0.99642292799539	0.990181209504564
34	8	8.05111493906011	8.06666666666667	0.998072099883485	0.99365119744942
35	8	7.99423136823724	8.025	0.99616590258408	1.00072159930043
36	7.9	7.96789183093094	7.96666666666667	1.00015378630932	0.991479323217293
37	7.8	7.87395141627817	7.9	0.996702710921287	0.99060809339955
38	7.8	7.79191178022942	7.825	0.995771473511747	1.00103802763670
39	7.9	7.72188927626052	7.73333333333333	0.998520165033688	1.02306569252256
40	8.1	7.68898944646159	7.64166666666667	1.00619273018036	1.05345443070254
41	8	7.6556712005214	7.5625	1.01232015874663	1.04497695766442
42	7.6	7.5286459135225	7.49583333333333	1.00437744260445	1.00947767862868
43	7.3	7.43148839402936	7.4375	0.999191716844284	0.982306586909965
44	7	7.3421525760273	7.37083333333333	0.996108885385276	0.95339887417425
45	6.8	7.25728032556642	7.28333333333333	0.99642292799539	0.93699012508095
46	7	7.161167316664	7.175	0.998072099883485	0.977494267409592
47	7.1	7.0312709957393	7.05833333333333	0.99616590258408	1.00977476252904
48	7.2	6.97190535206457	6.97083333333333	1.00015378630932	1.03271625709432
49	7.1	6.9187779849786	6.94166666666667	0.996702710921287	1.02619277788865
50	6.9	6.93305888432554	6.9625	0.995771473511747	0.995231702935586
51	6.7	6.99380165592345	7.00416666666667	0.998520165033688	0.95799113695559
52	6.7	7.07269639922612	7.02916666666667	1.00619273018036	0.947304906334323
53	6.6	7.11154911519509	7.025	1.01232015874663	0.92806783628871
54	6.9	7.04319681626368	7.0125	1.00437744260445	0.979668775415587
55	7.3	NA	NA	0.999191716844284	NA
56	7.5	NA	NA	0.996108885385276	NA
57	7.3	NA	NA	0.99642292799539	NA
58	7.1	NA	NA	0.998072099883485	NA
59	6.9	NA	NA	0.99616590258408	NA
60	7.1	NA	NA	1.00015378630932	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