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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 01 Dec 2009 12:46:49 -0700

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/2009/Dec/01/t12596969296dvfxko3t4cdtdx.htm/, Retrieved Fri, 26 Apr 2024 14:23:56 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62218, Retrieved Fri, 26 Apr 2024 14:23:56 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

177

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] [Klassiek decompos...] [2009-12-01 19:46:49] [6c304092df7982e5e12293b2743450a3] [Current]
-    D        [Classical Decomposition] [Ad hoc forecasting] [2009-12-04 16:11:06] [34d27ebe78dc2d31581e8710befe8733] 
-   PD          [Classical Decomposition] [Ad hoc forecasting] [2009-12-16 22:54:54] [34d27ebe78dc2d31581e8710befe8733] 
-    D        [Classical Decomposition] [klassieke decompo...] [2009-12-04 18:39:30] [4f1a20f787b3465111b61213cdeef1a9] 
-    D          [Classical Decomposition] [Klassieke decompo...] [2009-12-11 15:40:47] [4f1a20f787b3465111b61213cdeef1a9] 
-    D            [Classical Decomposition] [Klassieke decompo...] [2009-12-11 16:38:20] [4f1a20f787b3465111b61213cdeef1a9] 

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Dataseries X:

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Histogram

Boxplots

8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3
8.2

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=62218&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=62218&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62218&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	8.4	NA	NA	1.03502746171878	NA
2	8.4	NA	NA	0.99657350194391	NA
3	8.4	NA	NA	0.971587648997756	NA
4	8.6	NA	NA	0.990637074150072	NA
5	8.9	NA	NA	1.02786447326418	NA
6	8.8	NA	NA	1.03398937051682	NA
7	8.3	8.53776423862828	8.37083333333333	1.01994196977142	0.972151463546799
8	7.5	8.35395078582325	8.42083333333333	0.992057490646997	0.897778810563211
9	7.2	8.01874013719616	8.425	0.951779244771057	0.897896661671538
10	7.4	7.84846918960419	8.40416666666667	0.933878336888946	0.942859023999456
11	8.8	8.4211737820039	8.375	1.00551328740345	1.04498496620574
12	9.3	8.6936036683872	8.35	1.04115013992661	1.06975201018398
13	9.3	8.64247930535183	8.35	1.03502746171878	1.07608010056107
14	8.7	8.35876024755454	8.3875	0.99657350194391	1.04082420626256
15	8.2	8.21396391590186	8.45416666666667	0.971587648997756	0.998299978421523
16	8.3	8.43279809370249	8.5125	0.990637074150072	0.984252191001507
17	8.5	8.76254463457711	8.525	1.02786447326418	0.970037854809765
18	8.6	8.78029307130533	8.49166666666667	1.03398937051682	0.979466167035524
19	8.5	8.61001012815375	8.44166666666666	1.01994196977142	0.98722299666129
20	8.2	8.34155006719017	8.40833333333333	0.992057490646997	0.983030723780353
21	8.1	8.0028771497833	8.40833333333333	0.951779244771057	1.01213599164387
22	7.9	7.86792498828937	8.425	0.933878336888946	1.00407667990714
23	8.6	8.48820800116413	8.44166666666666	1.00551328740345	1.01317027090059
24	8.7	8.80205680796289	8.45416666666667	1.04115013992661	0.98840534545624
25	8.7	8.75891989479519	8.4625	1.03502746171878	0.993273155194603
26	8.5	8.45011281856606	8.47916666666667	0.99657350194391	1.00590372963120
27	8.4	8.25849501648092	8.5	0.971587648997756	1.01713447586233
28	8.5	8.43279809370249	8.5125	0.990637074150072	1.00796911126660
29	8.7	8.7368480227455	8.5	1.02786447326418	0.995782458084474
30	8.7	8.74582675895476	8.45833333333333	1.03398937051682	0.994760157019136
31	8.6	8.5760120624947	8.40833333333333	1.01994196977142	1.00279709698756
32	8.5	8.29608076553551	8.3625	0.992057490646997	1.02458018915530
33	8.3	7.91959646586584	8.32083333333333	0.951779244771057	1.04803319661219
34	8	7.72784323775603	8.275	0.933878336888946	1.03521768672976
35	8.2	8.26615715019587	8.22083333333333	1.00551328740345	0.991996625639484
36	8.1	8.49838801715096	8.1625	1.04115013992661	0.953121931318392
37	8.1	8.38803505434596	8.10416666666667	1.03502746171878	0.965661200450429
38	8	8.0265690802399	8.05416666666667	0.99657350194391	0.996689858397243
39	7.9	7.7807977557237	8.00833333333333	0.971587648997756	1.01532005432073
40	7.9	7.87556473949307	7.95	0.990637074150072	1.00310266772164
41	8	8.1072810328712	7.8875	1.02786447326418	0.986767322800798
42	8	8.09096682429411	7.825	1.03398937051682	0.988756989582385
43	7.9	7.90030050752114	7.74583333333333	1.01994196977142	0.999961962520178
44	8	7.59750694920492	7.65833333333333	0.992057490646997	1.05297699014770
45	7.7	7.21369352599397	7.57916666666667	0.951779244771057	1.06741435192023
46	7.2	7.01576100587821	7.5125	0.933878336888946	1.02626072837536
47	7.5	7.49526362985323	7.45416666666667	1.00551328740345	1.00063191508407
48	7.3	7.69149665870783	7.3875	1.04115013992661	0.949100067765796
49	7	7.56001308497093	7.30416666666667	1.03502746171878	0.92592432332105
50	7	7.16702443481328	7.19166666666667	0.99657350194391	0.976695428300485
51	7	6.85778948917582	7.05833333333333	0.971587648997756	1.02073707731167
52	7.2	6.89731062876987	6.9625	0.990637074150072	1.04388512965728
53	7.3	7.13509255190883	6.94166666666667	1.02786447326418	1.02311216664555
54	7.1	7.21207585935482	6.975	1.03398937051682	0.984459972199344
55	6.8	7.16084257943686	7.02083333333333	1.01994196977142	0.949608921654966
56	6.4	6.98160459042824	7.0375	0.992057490646997	0.916694710664993
57	6.1	6.67831770081025	7.01666666666667	0.951779244771057	0.91340368537123
58	6.5	6.52547487901151	6.9875	0.933878336888946	0.996096088103343
59	7.7	7.03021373442913	6.99166666666667	1.00551328740345	1.0952725323685
60	7.9	7.33577036089958	7.04583333333333	1.04115013992661	1.07691484484136
61	7.5	7.38319589359398	7.13333333333333	1.03502746171878	1.01582026375697
62	6.9	7.21270072031904	7.2375	0.99657350194391	0.95664582069264
63	6.6	7.13307265639186	7.34166666666667	0.971587648997756	0.925267457367874
64	6.9	7.35960793003991	7.42916666666667	0.990637074150072	0.93754994363709
65	7.7	7.69185247492693	7.48333333333333	1.02786447326418	1.00105924094353
66	8	7.77215343505143	7.51666666666667	1.03398937051682	1.02931575744774
67	8	7.71331114639638	7.5625	1.01994196977142	1.03716806546013
68	7.7	NA	NA	0.992057490646997	NA
69	7.3	NA	NA	0.951779244771057	NA
70	7.4	NA	NA	0.933878336888946	NA
71	8.1	NA	NA	1.00551328740345	NA
72	8.3	NA	NA	1.04115013992661	NA
73	8.2	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.4 & NA & NA & 1.03502746171878 & NA \tabularnewline
2 & 8.4 & NA & NA & 0.99657350194391 & NA \tabularnewline
3 & 8.4 & NA & NA & 0.971587648997756 & NA \tabularnewline
4 & 8.6 & NA & NA & 0.990637074150072 & NA \tabularnewline
5 & 8.9 & NA & NA & 1.02786447326418 & NA \tabularnewline
6 & 8.8 & NA & NA & 1.03398937051682 & NA \tabularnewline
7 & 8.3 & 8.53776423862828 & 8.37083333333333 & 1.01994196977142 & 0.972151463546799 \tabularnewline
8 & 7.5 & 8.35395078582325 & 8.42083333333333 & 0.992057490646997 & 0.897778810563211 \tabularnewline
9 & 7.2 & 8.01874013719616 & 8.425 & 0.951779244771057 & 0.897896661671538 \tabularnewline
10 & 7.4 & 7.84846918960419 & 8.40416666666667 & 0.933878336888946 & 0.942859023999456 \tabularnewline
11 & 8.8 & 8.4211737820039 & 8.375 & 1.00551328740345 & 1.04498496620574 \tabularnewline
12 & 9.3 & 8.6936036683872 & 8.35 & 1.04115013992661 & 1.06975201018398 \tabularnewline
13 & 9.3 & 8.64247930535183 & 8.35 & 1.03502746171878 & 1.07608010056107 \tabularnewline
14 & 8.7 & 8.35876024755454 & 8.3875 & 0.99657350194391 & 1.04082420626256 \tabularnewline
15 & 8.2 & 8.21396391590186 & 8.45416666666667 & 0.971587648997756 & 0.998299978421523 \tabularnewline
16 & 8.3 & 8.43279809370249 & 8.5125 & 0.990637074150072 & 0.984252191001507 \tabularnewline
17 & 8.5 & 8.76254463457711 & 8.525 & 1.02786447326418 & 0.970037854809765 \tabularnewline
18 & 8.6 & 8.78029307130533 & 8.49166666666667 & 1.03398937051682 & 0.979466167035524 \tabularnewline
19 & 8.5 & 8.61001012815375 & 8.44166666666666 & 1.01994196977142 & 0.98722299666129 \tabularnewline
20 & 8.2 & 8.34155006719017 & 8.40833333333333 & 0.992057490646997 & 0.983030723780353 \tabularnewline
21 & 8.1 & 8.0028771497833 & 8.40833333333333 & 0.951779244771057 & 1.01213599164387 \tabularnewline
22 & 7.9 & 7.86792498828937 & 8.425 & 0.933878336888946 & 1.00407667990714 \tabularnewline
23 & 8.6 & 8.48820800116413 & 8.44166666666666 & 1.00551328740345 & 1.01317027090059 \tabularnewline
24 & 8.7 & 8.80205680796289 & 8.45416666666667 & 1.04115013992661 & 0.98840534545624 \tabularnewline
25 & 8.7 & 8.75891989479519 & 8.4625 & 1.03502746171878 & 0.993273155194603 \tabularnewline
26 & 8.5 & 8.45011281856606 & 8.47916666666667 & 0.99657350194391 & 1.00590372963120 \tabularnewline
27 & 8.4 & 8.25849501648092 & 8.5 & 0.971587648997756 & 1.01713447586233 \tabularnewline
28 & 8.5 & 8.43279809370249 & 8.5125 & 0.990637074150072 & 1.00796911126660 \tabularnewline
29 & 8.7 & 8.7368480227455 & 8.5 & 1.02786447326418 & 0.995782458084474 \tabularnewline
30 & 8.7 & 8.74582675895476 & 8.45833333333333 & 1.03398937051682 & 0.994760157019136 \tabularnewline
31 & 8.6 & 8.5760120624947 & 8.40833333333333 & 1.01994196977142 & 1.00279709698756 \tabularnewline
32 & 8.5 & 8.29608076553551 & 8.3625 & 0.992057490646997 & 1.02458018915530 \tabularnewline
33 & 8.3 & 7.91959646586584 & 8.32083333333333 & 0.951779244771057 & 1.04803319661219 \tabularnewline
34 & 8 & 7.72784323775603 & 8.275 & 0.933878336888946 & 1.03521768672976 \tabularnewline
35 & 8.2 & 8.26615715019587 & 8.22083333333333 & 1.00551328740345 & 0.991996625639484 \tabularnewline
36 & 8.1 & 8.49838801715096 & 8.1625 & 1.04115013992661 & 0.953121931318392 \tabularnewline
37 & 8.1 & 8.38803505434596 & 8.10416666666667 & 1.03502746171878 & 0.965661200450429 \tabularnewline
38 & 8 & 8.0265690802399 & 8.05416666666667 & 0.99657350194391 & 0.996689858397243 \tabularnewline
39 & 7.9 & 7.7807977557237 & 8.00833333333333 & 0.971587648997756 & 1.01532005432073 \tabularnewline
40 & 7.9 & 7.87556473949307 & 7.95 & 0.990637074150072 & 1.00310266772164 \tabularnewline
41 & 8 & 8.1072810328712 & 7.8875 & 1.02786447326418 & 0.986767322800798 \tabularnewline
42 & 8 & 8.09096682429411 & 7.825 & 1.03398937051682 & 0.988756989582385 \tabularnewline
43 & 7.9 & 7.90030050752114 & 7.74583333333333 & 1.01994196977142 & 0.999961962520178 \tabularnewline
44 & 8 & 7.59750694920492 & 7.65833333333333 & 0.992057490646997 & 1.05297699014770 \tabularnewline
45 & 7.7 & 7.21369352599397 & 7.57916666666667 & 0.951779244771057 & 1.06741435192023 \tabularnewline
46 & 7.2 & 7.01576100587821 & 7.5125 & 0.933878336888946 & 1.02626072837536 \tabularnewline
47 & 7.5 & 7.49526362985323 & 7.45416666666667 & 1.00551328740345 & 1.00063191508407 \tabularnewline
48 & 7.3 & 7.69149665870783 & 7.3875 & 1.04115013992661 & 0.949100067765796 \tabularnewline
49 & 7 & 7.56001308497093 & 7.30416666666667 & 1.03502746171878 & 0.92592432332105 \tabularnewline
50 & 7 & 7.16702443481328 & 7.19166666666667 & 0.99657350194391 & 0.976695428300485 \tabularnewline
51 & 7 & 6.85778948917582 & 7.05833333333333 & 0.971587648997756 & 1.02073707731167 \tabularnewline
52 & 7.2 & 6.89731062876987 & 6.9625 & 0.990637074150072 & 1.04388512965728 \tabularnewline
53 & 7.3 & 7.13509255190883 & 6.94166666666667 & 1.02786447326418 & 1.02311216664555 \tabularnewline
54 & 7.1 & 7.21207585935482 & 6.975 & 1.03398937051682 & 0.984459972199344 \tabularnewline
55 & 6.8 & 7.16084257943686 & 7.02083333333333 & 1.01994196977142 & 0.949608921654966 \tabularnewline
56 & 6.4 & 6.98160459042824 & 7.0375 & 0.992057490646997 & 0.916694710664993 \tabularnewline
57 & 6.1 & 6.67831770081025 & 7.01666666666667 & 0.951779244771057 & 0.91340368537123 \tabularnewline
58 & 6.5 & 6.52547487901151 & 6.9875 & 0.933878336888946 & 0.996096088103343 \tabularnewline
59 & 7.7 & 7.03021373442913 & 6.99166666666667 & 1.00551328740345 & 1.0952725323685 \tabularnewline
60 & 7.9 & 7.33577036089958 & 7.04583333333333 & 1.04115013992661 & 1.07691484484136 \tabularnewline
61 & 7.5 & 7.38319589359398 & 7.13333333333333 & 1.03502746171878 & 1.01582026375697 \tabularnewline
62 & 6.9 & 7.21270072031904 & 7.2375 & 0.99657350194391 & 0.95664582069264 \tabularnewline
63 & 6.6 & 7.13307265639186 & 7.34166666666667 & 0.971587648997756 & 0.925267457367874 \tabularnewline
64 & 6.9 & 7.35960793003991 & 7.42916666666667 & 0.990637074150072 & 0.93754994363709 \tabularnewline
65 & 7.7 & 7.69185247492693 & 7.48333333333333 & 1.02786447326418 & 1.00105924094353 \tabularnewline
66 & 8 & 7.77215343505143 & 7.51666666666667 & 1.03398937051682 & 1.02931575744774 \tabularnewline
67 & 8 & 7.71331114639638 & 7.5625 & 1.01994196977142 & 1.03716806546013 \tabularnewline
68 & 7.7 & NA & NA & 0.992057490646997 & NA \tabularnewline
69 & 7.3 & NA & NA & 0.951779244771057 & NA \tabularnewline
70 & 7.4 & NA & NA & 0.933878336888946 & NA \tabularnewline
71 & 8.1 & NA & NA & 1.00551328740345 & NA \tabularnewline
72 & 8.3 & NA & NA & 1.04115013992661 & NA \tabularnewline
73 & 8.2 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62218&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]8.4[/C][C]NA[/C][C]NA[/C][C]1.03502746171878[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]8.4[/C][C]NA[/C][C]NA[/C][C]0.99657350194391[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.4[/C][C]NA[/C][C]NA[/C][C]0.971587648997756[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]8.6[/C][C]NA[/C][C]NA[/C][C]0.990637074150072[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8.9[/C][C]NA[/C][C]NA[/C][C]1.02786447326418[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]8.8[/C][C]NA[/C][C]NA[/C][C]1.03398937051682[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.3[/C][C]8.53776423862828[/C][C]8.37083333333333[/C][C]1.01994196977142[/C][C]0.972151463546799[/C][/ROW]
[ROW][C]8[/C][C]7.5[/C][C]8.35395078582325[/C][C]8.42083333333333[/C][C]0.992057490646997[/C][C]0.897778810563211[/C][/ROW]
[ROW][C]9[/C][C]7.2[/C][C]8.01874013719616[/C][C]8.425[/C][C]0.951779244771057[/C][C]0.897896661671538[/C][/ROW]
[ROW][C]10[/C][C]7.4[/C][C]7.84846918960419[/C][C]8.40416666666667[/C][C]0.933878336888946[/C][C]0.942859023999456[/C][/ROW]
[ROW][C]11[/C][C]8.8[/C][C]8.4211737820039[/C][C]8.375[/C][C]1.00551328740345[/C][C]1.04498496620574[/C][/ROW]
[ROW][C]12[/C][C]9.3[/C][C]8.6936036683872[/C][C]8.35[/C][C]1.04115013992661[/C][C]1.06975201018398[/C][/ROW]
[ROW][C]13[/C][C]9.3[/C][C]8.64247930535183[/C][C]8.35[/C][C]1.03502746171878[/C][C]1.07608010056107[/C][/ROW]
[ROW][C]14[/C][C]8.7[/C][C]8.35876024755454[/C][C]8.3875[/C][C]0.99657350194391[/C][C]1.04082420626256[/C][/ROW]
[ROW][C]15[/C][C]8.2[/C][C]8.21396391590186[/C][C]8.45416666666667[/C][C]0.971587648997756[/C][C]0.998299978421523[/C][/ROW]
[ROW][C]16[/C][C]8.3[/C][C]8.43279809370249[/C][C]8.5125[/C][C]0.990637074150072[/C][C]0.984252191001507[/C][/ROW]
[ROW][C]17[/C][C]8.5[/C][C]8.76254463457711[/C][C]8.525[/C][C]1.02786447326418[/C][C]0.970037854809765[/C][/ROW]
[ROW][C]18[/C][C]8.6[/C][C]8.78029307130533[/C][C]8.49166666666667[/C][C]1.03398937051682[/C][C]0.979466167035524[/C][/ROW]
[ROW][C]19[/C][C]8.5[/C][C]8.61001012815375[/C][C]8.44166666666666[/C][C]1.01994196977142[/C][C]0.98722299666129[/C][/ROW]
[ROW][C]20[/C][C]8.2[/C][C]8.34155006719017[/C][C]8.40833333333333[/C][C]0.992057490646997[/C][C]0.983030723780353[/C][/ROW]
[ROW][C]21[/C][C]8.1[/C][C]8.0028771497833[/C][C]8.40833333333333[/C][C]0.951779244771057[/C][C]1.01213599164387[/C][/ROW]
[ROW][C]22[/C][C]7.9[/C][C]7.86792498828937[/C][C]8.425[/C][C]0.933878336888946[/C][C]1.00407667990714[/C][/ROW]
[ROW][C]23[/C][C]8.6[/C][C]8.48820800116413[/C][C]8.44166666666666[/C][C]1.00551328740345[/C][C]1.01317027090059[/C][/ROW]
[ROW][C]24[/C][C]8.7[/C][C]8.80205680796289[/C][C]8.45416666666667[/C][C]1.04115013992661[/C][C]0.98840534545624[/C][/ROW]
[ROW][C]25[/C][C]8.7[/C][C]8.75891989479519[/C][C]8.4625[/C][C]1.03502746171878[/C][C]0.993273155194603[/C][/ROW]
[ROW][C]26[/C][C]8.5[/C][C]8.45011281856606[/C][C]8.47916666666667[/C][C]0.99657350194391[/C][C]1.00590372963120[/C][/ROW]
[ROW][C]27[/C][C]8.4[/C][C]8.25849501648092[/C][C]8.5[/C][C]0.971587648997756[/C][C]1.01713447586233[/C][/ROW]
[ROW][C]28[/C][C]8.5[/C][C]8.43279809370249[/C][C]8.5125[/C][C]0.990637074150072[/C][C]1.00796911126660[/C][/ROW]
[ROW][C]29[/C][C]8.7[/C][C]8.7368480227455[/C][C]8.5[/C][C]1.02786447326418[/C][C]0.995782458084474[/C][/ROW]
[ROW][C]30[/C][C]8.7[/C][C]8.74582675895476[/C][C]8.45833333333333[/C][C]1.03398937051682[/C][C]0.994760157019136[/C][/ROW]
[ROW][C]31[/C][C]8.6[/C][C]8.5760120624947[/C][C]8.40833333333333[/C][C]1.01994196977142[/C][C]1.00279709698756[/C][/ROW]
[ROW][C]32[/C][C]8.5[/C][C]8.29608076553551[/C][C]8.3625[/C][C]0.992057490646997[/C][C]1.02458018915530[/C][/ROW]
[ROW][C]33[/C][C]8.3[/C][C]7.91959646586584[/C][C]8.32083333333333[/C][C]0.951779244771057[/C][C]1.04803319661219[/C][/ROW]
[ROW][C]34[/C][C]8[/C][C]7.72784323775603[/C][C]8.275[/C][C]0.933878336888946[/C][C]1.03521768672976[/C][/ROW]
[ROW][C]35[/C][C]8.2[/C][C]8.26615715019587[/C][C]8.22083333333333[/C][C]1.00551328740345[/C][C]0.991996625639484[/C][/ROW]
[ROW][C]36[/C][C]8.1[/C][C]8.49838801715096[/C][C]8.1625[/C][C]1.04115013992661[/C][C]0.953121931318392[/C][/ROW]
[ROW][C]37[/C][C]8.1[/C][C]8.38803505434596[/C][C]8.10416666666667[/C][C]1.03502746171878[/C][C]0.965661200450429[/C][/ROW]
[ROW][C]38[/C][C]8[/C][C]8.0265690802399[/C][C]8.05416666666667[/C][C]0.99657350194391[/C][C]0.996689858397243[/C][/ROW]
[ROW][C]39[/C][C]7.9[/C][C]7.7807977557237[/C][C]8.00833333333333[/C][C]0.971587648997756[/C][C]1.01532005432073[/C][/ROW]
[ROW][C]40[/C][C]7.9[/C][C]7.87556473949307[/C][C]7.95[/C][C]0.990637074150072[/C][C]1.00310266772164[/C][/ROW]
[ROW][C]41[/C][C]8[/C][C]8.1072810328712[/C][C]7.8875[/C][C]1.02786447326418[/C][C]0.986767322800798[/C][/ROW]
[ROW][C]42[/C][C]8[/C][C]8.09096682429411[/C][C]7.825[/C][C]1.03398937051682[/C][C]0.988756989582385[/C][/ROW]
[ROW][C]43[/C][C]7.9[/C][C]7.90030050752114[/C][C]7.74583333333333[/C][C]1.01994196977142[/C][C]0.999961962520178[/C][/ROW]
[ROW][C]44[/C][C]8[/C][C]7.59750694920492[/C][C]7.65833333333333[/C][C]0.992057490646997[/C][C]1.05297699014770[/C][/ROW]
[ROW][C]45[/C][C]7.7[/C][C]7.21369352599397[/C][C]7.57916666666667[/C][C]0.951779244771057[/C][C]1.06741435192023[/C][/ROW]
[ROW][C]46[/C][C]7.2[/C][C]7.01576100587821[/C][C]7.5125[/C][C]0.933878336888946[/C][C]1.02626072837536[/C][/ROW]
[ROW][C]47[/C][C]7.5[/C][C]7.49526362985323[/C][C]7.45416666666667[/C][C]1.00551328740345[/C][C]1.00063191508407[/C][/ROW]
[ROW][C]48[/C][C]7.3[/C][C]7.69149665870783[/C][C]7.3875[/C][C]1.04115013992661[/C][C]0.949100067765796[/C][/ROW]
[ROW][C]49[/C][C]7[/C][C]7.56001308497093[/C][C]7.30416666666667[/C][C]1.03502746171878[/C][C]0.92592432332105[/C][/ROW]
[ROW][C]50[/C][C]7[/C][C]7.16702443481328[/C][C]7.19166666666667[/C][C]0.99657350194391[/C][C]0.976695428300485[/C][/ROW]
[ROW][C]51[/C][C]7[/C][C]6.85778948917582[/C][C]7.05833333333333[/C][C]0.971587648997756[/C][C]1.02073707731167[/C][/ROW]
[ROW][C]52[/C][C]7.2[/C][C]6.89731062876987[/C][C]6.9625[/C][C]0.990637074150072[/C][C]1.04388512965728[/C][/ROW]
[ROW][C]53[/C][C]7.3[/C][C]7.13509255190883[/C][C]6.94166666666667[/C][C]1.02786447326418[/C][C]1.02311216664555[/C][/ROW]
[ROW][C]54[/C][C]7.1[/C][C]7.21207585935482[/C][C]6.975[/C][C]1.03398937051682[/C][C]0.984459972199344[/C][/ROW]
[ROW][C]55[/C][C]6.8[/C][C]7.16084257943686[/C][C]7.02083333333333[/C][C]1.01994196977142[/C][C]0.949608921654966[/C][/ROW]
[ROW][C]56[/C][C]6.4[/C][C]6.98160459042824[/C][C]7.0375[/C][C]0.992057490646997[/C][C]0.916694710664993[/C][/ROW]
[ROW][C]57[/C][C]6.1[/C][C]6.67831770081025[/C][C]7.01666666666667[/C][C]0.951779244771057[/C][C]0.91340368537123[/C][/ROW]
[ROW][C]58[/C][C]6.5[/C][C]6.52547487901151[/C][C]6.9875[/C][C]0.933878336888946[/C][C]0.996096088103343[/C][/ROW]
[ROW][C]59[/C][C]7.7[/C][C]7.03021373442913[/C][C]6.99166666666667[/C][C]1.00551328740345[/C][C]1.0952725323685[/C][/ROW]
[ROW][C]60[/C][C]7.9[/C][C]7.33577036089958[/C][C]7.04583333333333[/C][C]1.04115013992661[/C][C]1.07691484484136[/C][/ROW]
[ROW][C]61[/C][C]7.5[/C][C]7.38319589359398[/C][C]7.13333333333333[/C][C]1.03502746171878[/C][C]1.01582026375697[/C][/ROW]
[ROW][C]62[/C][C]6.9[/C][C]7.21270072031904[/C][C]7.2375[/C][C]0.99657350194391[/C][C]0.95664582069264[/C][/ROW]
[ROW][C]63[/C][C]6.6[/C][C]7.13307265639186[/C][C]7.34166666666667[/C][C]0.971587648997756[/C][C]0.925267457367874[/C][/ROW]
[ROW][C]64[/C][C]6.9[/C][C]7.35960793003991[/C][C]7.42916666666667[/C][C]0.990637074150072[/C][C]0.93754994363709[/C][/ROW]
[ROW][C]65[/C][C]7.7[/C][C]7.69185247492693[/C][C]7.48333333333333[/C][C]1.02786447326418[/C][C]1.00105924094353[/C][/ROW]
[ROW][C]66[/C][C]8[/C][C]7.77215343505143[/C][C]7.51666666666667[/C][C]1.03398937051682[/C][C]1.02931575744774[/C][/ROW]
[ROW][C]67[/C][C]8[/C][C]7.71331114639638[/C][C]7.5625[/C][C]1.01994196977142[/C][C]1.03716806546013[/C][/ROW]
[ROW][C]68[/C][C]7.7[/C][C]NA[/C][C]NA[/C][C]0.992057490646997[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]7.3[/C][C]NA[/C][C]NA[/C][C]0.951779244771057[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]7.4[/C][C]NA[/C][C]NA[/C][C]0.933878336888946[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]8.1[/C][C]NA[/C][C]NA[/C][C]1.00551328740345[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]1.04115013992661[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]8.2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62218&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62218&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	8.4	NA	NA	1.03502746171878	NA
2	8.4	NA	NA	0.99657350194391	NA
3	8.4	NA	NA	0.971587648997756	NA
4	8.6	NA	NA	0.990637074150072	NA
5	8.9	NA	NA	1.02786447326418	NA
6	8.8	NA	NA	1.03398937051682	NA
7	8.3	8.53776423862828	8.37083333333333	1.01994196977142	0.972151463546799
8	7.5	8.35395078582325	8.42083333333333	0.992057490646997	0.897778810563211
9	7.2	8.01874013719616	8.425	0.951779244771057	0.897896661671538
10	7.4	7.84846918960419	8.40416666666667	0.933878336888946	0.942859023999456
11	8.8	8.4211737820039	8.375	1.00551328740345	1.04498496620574
12	9.3	8.6936036683872	8.35	1.04115013992661	1.06975201018398
13	9.3	8.64247930535183	8.35	1.03502746171878	1.07608010056107
14	8.7	8.35876024755454	8.3875	0.99657350194391	1.04082420626256
15	8.2	8.21396391590186	8.45416666666667	0.971587648997756	0.998299978421523
16	8.3	8.43279809370249	8.5125	0.990637074150072	0.984252191001507
17	8.5	8.76254463457711	8.525	1.02786447326418	0.970037854809765
18	8.6	8.78029307130533	8.49166666666667	1.03398937051682	0.979466167035524
19	8.5	8.61001012815375	8.44166666666666	1.01994196977142	0.98722299666129
20	8.2	8.34155006719017	8.40833333333333	0.992057490646997	0.983030723780353
21	8.1	8.0028771497833	8.40833333333333	0.951779244771057	1.01213599164387
22	7.9	7.86792498828937	8.425	0.933878336888946	1.00407667990714
23	8.6	8.48820800116413	8.44166666666666	1.00551328740345	1.01317027090059
24	8.7	8.80205680796289	8.45416666666667	1.04115013992661	0.98840534545624
25	8.7	8.75891989479519	8.4625	1.03502746171878	0.993273155194603
26	8.5	8.45011281856606	8.47916666666667	0.99657350194391	1.00590372963120
27	8.4	8.25849501648092	8.5	0.971587648997756	1.01713447586233
28	8.5	8.43279809370249	8.5125	0.990637074150072	1.00796911126660
29	8.7	8.7368480227455	8.5	1.02786447326418	0.995782458084474
30	8.7	8.74582675895476	8.45833333333333	1.03398937051682	0.994760157019136
31	8.6	8.5760120624947	8.40833333333333	1.01994196977142	1.00279709698756
32	8.5	8.29608076553551	8.3625	0.992057490646997	1.02458018915530
33	8.3	7.91959646586584	8.32083333333333	0.951779244771057	1.04803319661219
34	8	7.72784323775603	8.275	0.933878336888946	1.03521768672976
35	8.2	8.26615715019587	8.22083333333333	1.00551328740345	0.991996625639484
36	8.1	8.49838801715096	8.1625	1.04115013992661	0.953121931318392
37	8.1	8.38803505434596	8.10416666666667	1.03502746171878	0.965661200450429
38	8	8.0265690802399	8.05416666666667	0.99657350194391	0.996689858397243
39	7.9	7.7807977557237	8.00833333333333	0.971587648997756	1.01532005432073
40	7.9	7.87556473949307	7.95	0.990637074150072	1.00310266772164
41	8	8.1072810328712	7.8875	1.02786447326418	0.986767322800798
42	8	8.09096682429411	7.825	1.03398937051682	0.988756989582385
43	7.9	7.90030050752114	7.74583333333333	1.01994196977142	0.999961962520178
44	8	7.59750694920492	7.65833333333333	0.992057490646997	1.05297699014770
45	7.7	7.21369352599397	7.57916666666667	0.951779244771057	1.06741435192023
46	7.2	7.01576100587821	7.5125	0.933878336888946	1.02626072837536
47	7.5	7.49526362985323	7.45416666666667	1.00551328740345	1.00063191508407
48	7.3	7.69149665870783	7.3875	1.04115013992661	0.949100067765796
49	7	7.56001308497093	7.30416666666667	1.03502746171878	0.92592432332105
50	7	7.16702443481328	7.19166666666667	0.99657350194391	0.976695428300485
51	7	6.85778948917582	7.05833333333333	0.971587648997756	1.02073707731167
52	7.2	6.89731062876987	6.9625	0.990637074150072	1.04388512965728
53	7.3	7.13509255190883	6.94166666666667	1.02786447326418	1.02311216664555
54	7.1	7.21207585935482	6.975	1.03398937051682	0.984459972199344
55	6.8	7.16084257943686	7.02083333333333	1.01994196977142	0.949608921654966
56	6.4	6.98160459042824	7.0375	0.992057490646997	0.916694710664993
57	6.1	6.67831770081025	7.01666666666667	0.951779244771057	0.91340368537123
58	6.5	6.52547487901151	6.9875	0.933878336888946	0.996096088103343
59	7.7	7.03021373442913	6.99166666666667	1.00551328740345	1.0952725323685
60	7.9	7.33577036089958	7.04583333333333	1.04115013992661	1.07691484484136
61	7.5	7.38319589359398	7.13333333333333	1.03502746171878	1.01582026375697
62	6.9	7.21270072031904	7.2375	0.99657350194391	0.95664582069264
63	6.6	7.13307265639186	7.34166666666667	0.971587648997756	0.925267457367874
64	6.9	7.35960793003991	7.42916666666667	0.990637074150072	0.93754994363709
65	7.7	7.69185247492693	7.48333333333333	1.02786447326418	1.00105924094353
66	8	7.77215343505143	7.51666666666667	1.03398937051682	1.02931575744774
67	8	7.71331114639638	7.5625	1.01994196977142	1.03716806546013
68	7.7	NA	NA	0.992057490646997	NA
69	7.3	NA	NA	0.951779244771057	NA
70	7.4	NA	NA	0.933878336888946	NA
71	8.1	NA	NA	1.00551328740345	NA
72	8.3	NA	NA	1.04115013992661	NA
73	8.2	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