Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 08:31:13 -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/04/t1259940750bttqtjnpp46409n.htm/, Retrieved Sun, 28 Apr 2024 13:15:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63767, Retrieved Sun, 28 Apr 2024 13:15:34 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

111

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] [] [2009-12-04 12:26:32] [1f74ef2f756548f1f3a7b6136ea56d7f]
-    D        [Classical Decomposition] [ws9 AD-HOC Foreca...] [2009-12-04 15:31:13] [ac4f1d4b47349b2602192853b2bc5b72] [Current]
-    D          [Classical Decomposition] [ADHOCForecasting(1)] [2009-12-09 17:49:53] [aba88da643e3763d32ff92bd8f92a385] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

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=63767&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=63767&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63767&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	9.3	NA	NA	1.0352168535	NA
2	9.3	NA	NA	1.01178560674111	NA
3	8.7	NA	NA	0.983000307083953	NA
4	8.2	NA	NA	0.968708917284983	NA
5	8.3	NA	NA	0.991189438397787	NA
6	8.5	NA	NA	1.03209909341544	NA
7	8.6	8.79572008904865	8.49166666666667	1.03580609488306	0.977748258577221
8	8.5	8.51300257055876	8.44166666666666	1.00845045258347	0.998472622267997
9	8.2	8.38114673507462	8.40833333333333	0.996766707838408	0.97838640214751
10	8.1	8.12963216316457	8.40833333333333	0.966854172031466	0.996355042568982
11	7.9	8.06279428137143	8.425	0.957008223308181	0.97980919818982
12	8.6	8.5523718055022	8.44166666666666	1.01311413293215	1.00556900419918
13	8.7	8.75189581563124	8.45416666666667	1.0352168535	0.99407033439103
14	8.7	8.56223569704662	8.4625	1.01178560674111	1.01608975830937
15	8.5	8.33502343714935	8.47916666666667	0.983000307083953	1.01979317323996
16	8.4	8.23402579692235	8.5	0.968708917284983	1.02015711477849
17	8.5	8.43750009436116	8.5125	0.991189438397787	1.00740739614102
18	8.7	8.77284229403126	8.5	1.03209909341544	0.991696842187529
19	8.7	8.76119321921922	8.45833333333333	1.03580609488306	0.9930154240766
20	8.6	8.47938755547264	8.40833333333333	1.00845045258347	1.01422419293119
21	8.5	8.33546159429869	8.3625	0.996766707838408	1.01973956737007
22	8.3	8.04503242311182	8.32083333333333	0.966854172031466	1.03169254808168
23	8	7.9192430478752	8.275	0.957008223308181	1.01019755949358
24	8.2	8.32864243447969	8.22083333333333	1.01311413293215	0.984554213307666
25	8.1	8.44995756669374	8.1625	1.0352168535	0.958584695374906
26	8.1	8.1996791879644	8.10416666666667	1.01178560674111	0.987843525864926
27	8	7.91724830663867	8.05416666666667	0.983000307083953	1.01045207755982
28	7.9	7.75774391259057	8.00833333333333	0.968708917284983	1.01833730128402
29	7.9	7.8799560352624	7.95	0.991189438397787	1.00254366453923
30	8	8.1406815993143	7.8875	1.03209909341544	0.982718695283924
31	8	8.10518269245994	7.825	1.03580609488306	0.98702278573464
32	7.9	7.8112891306361	7.74583333333333	1.00845045258347	1.01135675147601
33	8	7.63357170419581	7.65833333333333	0.996766707838408	1.04800220787902
34	7.7	7.32794891218848	7.57916666666667	0.966854172031466	1.05077151768794
35	7.2	7.18952427760271	7.5125	0.957008223308181	1.00145708144139
36	7.5	7.55192159923171	7.45416666666667	1.01311413293215	0.993124716861866
37	7.3	7.64766450523124	7.3875	1.0352168535	0.954539780740456
38	7	7.3902507025715	7.30416666666667	1.01178560674111	0.947193847911585
39	7	7.06941054177876	7.19166666666667	0.983000307083953	0.990181565864855
40	7	6.83747044116983	7.05833333333333	0.968708917284983	1.02377042215079
41	7.2	6.9011564648446	6.9625	0.991189438397787	1.04330339946323
42	7.3	7.16448787345887	6.94166666666667	1.03209909341544	1.01891441913708
43	7.1	7.22474751180934	6.975	1.03580609488306	0.982733304990184
44	6.8	7.08016255251308	7.02083333333333	1.00845045258347	0.960429926511554
45	6.4	7.0147457064128	7.0375	0.996766707838408	0.912363793052283
46	6.1	6.78409344042078	7.01666666666667	0.966854172031466	0.899162143559987
47	6.5	6.68709496036592	6.9875	0.957008223308181	0.97202148893132
48	7.7	7.0833563127506	6.99166666666667	1.01311413293215	1.08705529695568
49	7.9	7.29396541361874	7.04583333333333	1.0352168535	1.08308712093009
50	7.5	7.21740399475323	7.13333333333333	1.01178560674111	1.03915479935060
51	6.9	7.11446472252011	7.2375	0.983000307083953	0.969855114771848
52	6.6	7.11193796773391	7.34166666666667	0.968708917284983	0.92801709322318
53	6.9	7.3637115360969	7.42916666666667	0.991189438397787	0.937027471293005
54	7.7	7.7235415490589	7.48333333333333	1.03209909341544	0.99695197482795
55	8	7.78580914653767	7.51666666666667	1.03580609488306	1.02751041663506
56	8	NA	NA	1.00845045258347	NA
57	7.7	NA	NA	0.996766707838408	NA
58	7.3	NA	NA	0.966854172031466	NA
59	7.4	NA	NA	0.957008223308181	NA
60	8.1	NA	NA	1.01311413293215	NA
61	8.3	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 9.3 & NA & NA & 1.0352168535 & NA \tabularnewline
2 & 9.3 & NA & NA & 1.01178560674111 & NA \tabularnewline
3 & 8.7 & NA & NA & 0.983000307083953 & NA \tabularnewline
4 & 8.2 & NA & NA & 0.968708917284983 & NA \tabularnewline
5 & 8.3 & NA & NA & 0.991189438397787 & NA \tabularnewline
6 & 8.5 & NA & NA & 1.03209909341544 & NA \tabularnewline
7 & 8.6 & 8.79572008904865 & 8.49166666666667 & 1.03580609488306 & 0.977748258577221 \tabularnewline
8 & 8.5 & 8.51300257055876 & 8.44166666666666 & 1.00845045258347 & 0.998472622267997 \tabularnewline
9 & 8.2 & 8.38114673507462 & 8.40833333333333 & 0.996766707838408 & 0.97838640214751 \tabularnewline
10 & 8.1 & 8.12963216316457 & 8.40833333333333 & 0.966854172031466 & 0.996355042568982 \tabularnewline
11 & 7.9 & 8.06279428137143 & 8.425 & 0.957008223308181 & 0.97980919818982 \tabularnewline
12 & 8.6 & 8.5523718055022 & 8.44166666666666 & 1.01311413293215 & 1.00556900419918 \tabularnewline
13 & 8.7 & 8.75189581563124 & 8.45416666666667 & 1.0352168535 & 0.99407033439103 \tabularnewline
14 & 8.7 & 8.56223569704662 & 8.4625 & 1.01178560674111 & 1.01608975830937 \tabularnewline
15 & 8.5 & 8.33502343714935 & 8.47916666666667 & 0.983000307083953 & 1.01979317323996 \tabularnewline
16 & 8.4 & 8.23402579692235 & 8.5 & 0.968708917284983 & 1.02015711477849 \tabularnewline
17 & 8.5 & 8.43750009436116 & 8.5125 & 0.991189438397787 & 1.00740739614102 \tabularnewline
18 & 8.7 & 8.77284229403126 & 8.5 & 1.03209909341544 & 0.991696842187529 \tabularnewline
19 & 8.7 & 8.76119321921922 & 8.45833333333333 & 1.03580609488306 & 0.9930154240766 \tabularnewline
20 & 8.6 & 8.47938755547264 & 8.40833333333333 & 1.00845045258347 & 1.01422419293119 \tabularnewline
21 & 8.5 & 8.33546159429869 & 8.3625 & 0.996766707838408 & 1.01973956737007 \tabularnewline
22 & 8.3 & 8.04503242311182 & 8.32083333333333 & 0.966854172031466 & 1.03169254808168 \tabularnewline
23 & 8 & 7.9192430478752 & 8.275 & 0.957008223308181 & 1.01019755949358 \tabularnewline
24 & 8.2 & 8.32864243447969 & 8.22083333333333 & 1.01311413293215 & 0.984554213307666 \tabularnewline
25 & 8.1 & 8.44995756669374 & 8.1625 & 1.0352168535 & 0.958584695374906 \tabularnewline
26 & 8.1 & 8.1996791879644 & 8.10416666666667 & 1.01178560674111 & 0.987843525864926 \tabularnewline
27 & 8 & 7.91724830663867 & 8.05416666666667 & 0.983000307083953 & 1.01045207755982 \tabularnewline
28 & 7.9 & 7.75774391259057 & 8.00833333333333 & 0.968708917284983 & 1.01833730128402 \tabularnewline
29 & 7.9 & 7.8799560352624 & 7.95 & 0.991189438397787 & 1.00254366453923 \tabularnewline
30 & 8 & 8.1406815993143 & 7.8875 & 1.03209909341544 & 0.982718695283924 \tabularnewline
31 & 8 & 8.10518269245994 & 7.825 & 1.03580609488306 & 0.98702278573464 \tabularnewline
32 & 7.9 & 7.8112891306361 & 7.74583333333333 & 1.00845045258347 & 1.01135675147601 \tabularnewline
33 & 8 & 7.63357170419581 & 7.65833333333333 & 0.996766707838408 & 1.04800220787902 \tabularnewline
34 & 7.7 & 7.32794891218848 & 7.57916666666667 & 0.966854172031466 & 1.05077151768794 \tabularnewline
35 & 7.2 & 7.18952427760271 & 7.5125 & 0.957008223308181 & 1.00145708144139 \tabularnewline
36 & 7.5 & 7.55192159923171 & 7.45416666666667 & 1.01311413293215 & 0.993124716861866 \tabularnewline
37 & 7.3 & 7.64766450523124 & 7.3875 & 1.0352168535 & 0.954539780740456 \tabularnewline
38 & 7 & 7.3902507025715 & 7.30416666666667 & 1.01178560674111 & 0.947193847911585 \tabularnewline
39 & 7 & 7.06941054177876 & 7.19166666666667 & 0.983000307083953 & 0.990181565864855 \tabularnewline
40 & 7 & 6.83747044116983 & 7.05833333333333 & 0.968708917284983 & 1.02377042215079 \tabularnewline
41 & 7.2 & 6.9011564648446 & 6.9625 & 0.991189438397787 & 1.04330339946323 \tabularnewline
42 & 7.3 & 7.16448787345887 & 6.94166666666667 & 1.03209909341544 & 1.01891441913708 \tabularnewline
43 & 7.1 & 7.22474751180934 & 6.975 & 1.03580609488306 & 0.982733304990184 \tabularnewline
44 & 6.8 & 7.08016255251308 & 7.02083333333333 & 1.00845045258347 & 0.960429926511554 \tabularnewline
45 & 6.4 & 7.0147457064128 & 7.0375 & 0.996766707838408 & 0.912363793052283 \tabularnewline
46 & 6.1 & 6.78409344042078 & 7.01666666666667 & 0.966854172031466 & 0.899162143559987 \tabularnewline
47 & 6.5 & 6.68709496036592 & 6.9875 & 0.957008223308181 & 0.97202148893132 \tabularnewline
48 & 7.7 & 7.0833563127506 & 6.99166666666667 & 1.01311413293215 & 1.08705529695568 \tabularnewline
49 & 7.9 & 7.29396541361874 & 7.04583333333333 & 1.0352168535 & 1.08308712093009 \tabularnewline
50 & 7.5 & 7.21740399475323 & 7.13333333333333 & 1.01178560674111 & 1.03915479935060 \tabularnewline
51 & 6.9 & 7.11446472252011 & 7.2375 & 0.983000307083953 & 0.969855114771848 \tabularnewline
52 & 6.6 & 7.11193796773391 & 7.34166666666667 & 0.968708917284983 & 0.92801709322318 \tabularnewline
53 & 6.9 & 7.3637115360969 & 7.42916666666667 & 0.991189438397787 & 0.937027471293005 \tabularnewline
54 & 7.7 & 7.7235415490589 & 7.48333333333333 & 1.03209909341544 & 0.99695197482795 \tabularnewline
55 & 8 & 7.78580914653767 & 7.51666666666667 & 1.03580609488306 & 1.02751041663506 \tabularnewline
56 & 8 & NA & NA & 1.00845045258347 & NA \tabularnewline
57 & 7.7 & NA & NA & 0.996766707838408 & NA \tabularnewline
58 & 7.3 & NA & NA & 0.966854172031466 & NA \tabularnewline
59 & 7.4 & NA & NA & 0.957008223308181 & NA \tabularnewline
60 & 8.1 & NA & NA & 1.01311413293215 & NA \tabularnewline
61 & 8.3 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63767&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]9.3[/C][C]NA[/C][C]NA[/C][C]1.0352168535[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.3[/C][C]NA[/C][C]NA[/C][C]1.01178560674111[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]8.7[/C][C]NA[/C][C]NA[/C][C]0.983000307083953[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]8.2[/C][C]NA[/C][C]NA[/C][C]0.968708917284983[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]0.991189438397787[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]8.5[/C][C]NA[/C][C]NA[/C][C]1.03209909341544[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]8.6[/C][C]8.79572008904865[/C][C]8.49166666666667[/C][C]1.03580609488306[/C][C]0.977748258577221[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]8.51300257055876[/C][C]8.44166666666666[/C][C]1.00845045258347[/C][C]0.998472622267997[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]8.38114673507462[/C][C]8.40833333333333[/C][C]0.996766707838408[/C][C]0.97838640214751[/C][/ROW]
[ROW][C]10[/C][C]8.1[/C][C]8.12963216316457[/C][C]8.40833333333333[/C][C]0.966854172031466[/C][C]0.996355042568982[/C][/ROW]
[ROW][C]11[/C][C]7.9[/C][C]8.06279428137143[/C][C]8.425[/C][C]0.957008223308181[/C][C]0.97980919818982[/C][/ROW]
[ROW][C]12[/C][C]8.6[/C][C]8.5523718055022[/C][C]8.44166666666666[/C][C]1.01311413293215[/C][C]1.00556900419918[/C][/ROW]
[ROW][C]13[/C][C]8.7[/C][C]8.75189581563124[/C][C]8.45416666666667[/C][C]1.0352168535[/C][C]0.99407033439103[/C][/ROW]
[ROW][C]14[/C][C]8.7[/C][C]8.56223569704662[/C][C]8.4625[/C][C]1.01178560674111[/C][C]1.01608975830937[/C][/ROW]
[ROW][C]15[/C][C]8.5[/C][C]8.33502343714935[/C][C]8.47916666666667[/C][C]0.983000307083953[/C][C]1.01979317323996[/C][/ROW]
[ROW][C]16[/C][C]8.4[/C][C]8.23402579692235[/C][C]8.5[/C][C]0.968708917284983[/C][C]1.02015711477849[/C][/ROW]
[ROW][C]17[/C][C]8.5[/C][C]8.43750009436116[/C][C]8.5125[/C][C]0.991189438397787[/C][C]1.00740739614102[/C][/ROW]
[ROW][C]18[/C][C]8.7[/C][C]8.77284229403126[/C][C]8.5[/C][C]1.03209909341544[/C][C]0.991696842187529[/C][/ROW]
[ROW][C]19[/C][C]8.7[/C][C]8.76119321921922[/C][C]8.45833333333333[/C][C]1.03580609488306[/C][C]0.9930154240766[/C][/ROW]
[ROW][C]20[/C][C]8.6[/C][C]8.47938755547264[/C][C]8.40833333333333[/C][C]1.00845045258347[/C][C]1.01422419293119[/C][/ROW]
[ROW][C]21[/C][C]8.5[/C][C]8.33546159429869[/C][C]8.3625[/C][C]0.996766707838408[/C][C]1.01973956737007[/C][/ROW]
[ROW][C]22[/C][C]8.3[/C][C]8.04503242311182[/C][C]8.32083333333333[/C][C]0.966854172031466[/C][C]1.03169254808168[/C][/ROW]
[ROW][C]23[/C][C]8[/C][C]7.9192430478752[/C][C]8.275[/C][C]0.957008223308181[/C][C]1.01019755949358[/C][/ROW]
[ROW][C]24[/C][C]8.2[/C][C]8.32864243447969[/C][C]8.22083333333333[/C][C]1.01311413293215[/C][C]0.984554213307666[/C][/ROW]
[ROW][C]25[/C][C]8.1[/C][C]8.44995756669374[/C][C]8.1625[/C][C]1.0352168535[/C][C]0.958584695374906[/C][/ROW]
[ROW][C]26[/C][C]8.1[/C][C]8.1996791879644[/C][C]8.10416666666667[/C][C]1.01178560674111[/C][C]0.987843525864926[/C][/ROW]
[ROW][C]27[/C][C]8[/C][C]7.91724830663867[/C][C]8.05416666666667[/C][C]0.983000307083953[/C][C]1.01045207755982[/C][/ROW]
[ROW][C]28[/C][C]7.9[/C][C]7.75774391259057[/C][C]8.00833333333333[/C][C]0.968708917284983[/C][C]1.01833730128402[/C][/ROW]
[ROW][C]29[/C][C]7.9[/C][C]7.8799560352624[/C][C]7.95[/C][C]0.991189438397787[/C][C]1.00254366453923[/C][/ROW]
[ROW][C]30[/C][C]8[/C][C]8.1406815993143[/C][C]7.8875[/C][C]1.03209909341544[/C][C]0.982718695283924[/C][/ROW]
[ROW][C]31[/C][C]8[/C][C]8.10518269245994[/C][C]7.825[/C][C]1.03580609488306[/C][C]0.98702278573464[/C][/ROW]
[ROW][C]32[/C][C]7.9[/C][C]7.8112891306361[/C][C]7.74583333333333[/C][C]1.00845045258347[/C][C]1.01135675147601[/C][/ROW]
[ROW][C]33[/C][C]8[/C][C]7.63357170419581[/C][C]7.65833333333333[/C][C]0.996766707838408[/C][C]1.04800220787902[/C][/ROW]
[ROW][C]34[/C][C]7.7[/C][C]7.32794891218848[/C][C]7.57916666666667[/C][C]0.966854172031466[/C][C]1.05077151768794[/C][/ROW]
[ROW][C]35[/C][C]7.2[/C][C]7.18952427760271[/C][C]7.5125[/C][C]0.957008223308181[/C][C]1.00145708144139[/C][/ROW]
[ROW][C]36[/C][C]7.5[/C][C]7.55192159923171[/C][C]7.45416666666667[/C][C]1.01311413293215[/C][C]0.993124716861866[/C][/ROW]
[ROW][C]37[/C][C]7.3[/C][C]7.64766450523124[/C][C]7.3875[/C][C]1.0352168535[/C][C]0.954539780740456[/C][/ROW]
[ROW][C]38[/C][C]7[/C][C]7.3902507025715[/C][C]7.30416666666667[/C][C]1.01178560674111[/C][C]0.947193847911585[/C][/ROW]
[ROW][C]39[/C][C]7[/C][C]7.06941054177876[/C][C]7.19166666666667[/C][C]0.983000307083953[/C][C]0.990181565864855[/C][/ROW]
[ROW][C]40[/C][C]7[/C][C]6.83747044116983[/C][C]7.05833333333333[/C][C]0.968708917284983[/C][C]1.02377042215079[/C][/ROW]
[ROW][C]41[/C][C]7.2[/C][C]6.9011564648446[/C][C]6.9625[/C][C]0.991189438397787[/C][C]1.04330339946323[/C][/ROW]
[ROW][C]42[/C][C]7.3[/C][C]7.16448787345887[/C][C]6.94166666666667[/C][C]1.03209909341544[/C][C]1.01891441913708[/C][/ROW]
[ROW][C]43[/C][C]7.1[/C][C]7.22474751180934[/C][C]6.975[/C][C]1.03580609488306[/C][C]0.982733304990184[/C][/ROW]
[ROW][C]44[/C][C]6.8[/C][C]7.08016255251308[/C][C]7.02083333333333[/C][C]1.00845045258347[/C][C]0.960429926511554[/C][/ROW]
[ROW][C]45[/C][C]6.4[/C][C]7.0147457064128[/C][C]7.0375[/C][C]0.996766707838408[/C][C]0.912363793052283[/C][/ROW]
[ROW][C]46[/C][C]6.1[/C][C]6.78409344042078[/C][C]7.01666666666667[/C][C]0.966854172031466[/C][C]0.899162143559987[/C][/ROW]
[ROW][C]47[/C][C]6.5[/C][C]6.68709496036592[/C][C]6.9875[/C][C]0.957008223308181[/C][C]0.97202148893132[/C][/ROW]
[ROW][C]48[/C][C]7.7[/C][C]7.0833563127506[/C][C]6.99166666666667[/C][C]1.01311413293215[/C][C]1.08705529695568[/C][/ROW]
[ROW][C]49[/C][C]7.9[/C][C]7.29396541361874[/C][C]7.04583333333333[/C][C]1.0352168535[/C][C]1.08308712093009[/C][/ROW]
[ROW][C]50[/C][C]7.5[/C][C]7.21740399475323[/C][C]7.13333333333333[/C][C]1.01178560674111[/C][C]1.03915479935060[/C][/ROW]
[ROW][C]51[/C][C]6.9[/C][C]7.11446472252011[/C][C]7.2375[/C][C]0.983000307083953[/C][C]0.969855114771848[/C][/ROW]
[ROW][C]52[/C][C]6.6[/C][C]7.11193796773391[/C][C]7.34166666666667[/C][C]0.968708917284983[/C][C]0.92801709322318[/C][/ROW]
[ROW][C]53[/C][C]6.9[/C][C]7.3637115360969[/C][C]7.42916666666667[/C][C]0.991189438397787[/C][C]0.937027471293005[/C][/ROW]
[ROW][C]54[/C][C]7.7[/C][C]7.7235415490589[/C][C]7.48333333333333[/C][C]1.03209909341544[/C][C]0.99695197482795[/C][/ROW]
[ROW][C]55[/C][C]8[/C][C]7.78580914653767[/C][C]7.51666666666667[/C][C]1.03580609488306[/C][C]1.02751041663506[/C][/ROW]
[ROW][C]56[/C][C]8[/C][C]NA[/C][C]NA[/C][C]1.00845045258347[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]7.7[/C][C]NA[/C][C]NA[/C][C]0.996766707838408[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]7.3[/C][C]NA[/C][C]NA[/C][C]0.966854172031466[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]7.4[/C][C]NA[/C][C]NA[/C][C]0.957008223308181[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]8.1[/C][C]NA[/C][C]NA[/C][C]1.01311413293215[/C][C]NA[/C][/ROW]
[ROW][C]61[/C][C]8.3[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63767&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63767&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	9.3	NA	NA	1.0352168535	NA
2	9.3	NA	NA	1.01178560674111	NA
3	8.7	NA	NA	0.983000307083953	NA
4	8.2	NA	NA	0.968708917284983	NA
5	8.3	NA	NA	0.991189438397787	NA
6	8.5	NA	NA	1.03209909341544	NA
7	8.6	8.79572008904865	8.49166666666667	1.03580609488306	0.977748258577221
8	8.5	8.51300257055876	8.44166666666666	1.00845045258347	0.998472622267997
9	8.2	8.38114673507462	8.40833333333333	0.996766707838408	0.97838640214751
10	8.1	8.12963216316457	8.40833333333333	0.966854172031466	0.996355042568982
11	7.9	8.06279428137143	8.425	0.957008223308181	0.97980919818982
12	8.6	8.5523718055022	8.44166666666666	1.01311413293215	1.00556900419918
13	8.7	8.75189581563124	8.45416666666667	1.0352168535	0.99407033439103
14	8.7	8.56223569704662	8.4625	1.01178560674111	1.01608975830937
15	8.5	8.33502343714935	8.47916666666667	0.983000307083953	1.01979317323996
16	8.4	8.23402579692235	8.5	0.968708917284983	1.02015711477849
17	8.5	8.43750009436116	8.5125	0.991189438397787	1.00740739614102
18	8.7	8.77284229403126	8.5	1.03209909341544	0.991696842187529
19	8.7	8.76119321921922	8.45833333333333	1.03580609488306	0.9930154240766
20	8.6	8.47938755547264	8.40833333333333	1.00845045258347	1.01422419293119
21	8.5	8.33546159429869	8.3625	0.996766707838408	1.01973956737007
22	8.3	8.04503242311182	8.32083333333333	0.966854172031466	1.03169254808168
23	8	7.9192430478752	8.275	0.957008223308181	1.01019755949358
24	8.2	8.32864243447969	8.22083333333333	1.01311413293215	0.984554213307666
25	8.1	8.44995756669374	8.1625	1.0352168535	0.958584695374906
26	8.1	8.1996791879644	8.10416666666667	1.01178560674111	0.987843525864926
27	8	7.91724830663867	8.05416666666667	0.983000307083953	1.01045207755982
28	7.9	7.75774391259057	8.00833333333333	0.968708917284983	1.01833730128402
29	7.9	7.8799560352624	7.95	0.991189438397787	1.00254366453923
30	8	8.1406815993143	7.8875	1.03209909341544	0.982718695283924
31	8	8.10518269245994	7.825	1.03580609488306	0.98702278573464
32	7.9	7.8112891306361	7.74583333333333	1.00845045258347	1.01135675147601
33	8	7.63357170419581	7.65833333333333	0.996766707838408	1.04800220787902
34	7.7	7.32794891218848	7.57916666666667	0.966854172031466	1.05077151768794
35	7.2	7.18952427760271	7.5125	0.957008223308181	1.00145708144139
36	7.5	7.55192159923171	7.45416666666667	1.01311413293215	0.993124716861866
37	7.3	7.64766450523124	7.3875	1.0352168535	0.954539780740456
38	7	7.3902507025715	7.30416666666667	1.01178560674111	0.947193847911585
39	7	7.06941054177876	7.19166666666667	0.983000307083953	0.990181565864855
40	7	6.83747044116983	7.05833333333333	0.968708917284983	1.02377042215079
41	7.2	6.9011564648446	6.9625	0.991189438397787	1.04330339946323
42	7.3	7.16448787345887	6.94166666666667	1.03209909341544	1.01891441913708
43	7.1	7.22474751180934	6.975	1.03580609488306	0.982733304990184
44	6.8	7.08016255251308	7.02083333333333	1.00845045258347	0.960429926511554
45	6.4	7.0147457064128	7.0375	0.996766707838408	0.912363793052283
46	6.1	6.78409344042078	7.01666666666667	0.966854172031466	0.899162143559987
47	6.5	6.68709496036592	6.9875	0.957008223308181	0.97202148893132
48	7.7	7.0833563127506	6.99166666666667	1.01311413293215	1.08705529695568
49	7.9	7.29396541361874	7.04583333333333	1.0352168535	1.08308712093009
50	7.5	7.21740399475323	7.13333333333333	1.01178560674111	1.03915479935060
51	6.9	7.11446472252011	7.2375	0.983000307083953	0.969855114771848
52	6.6	7.11193796773391	7.34166666666667	0.968708917284983	0.92801709322318
53	6.9	7.3637115360969	7.42916666666667	0.991189438397787	0.937027471293005
54	7.7	7.7235415490589	7.48333333333333	1.03209909341544	0.99695197482795
55	8	7.78580914653767	7.51666666666667	1.03580609488306	1.02751041663506
56	8	NA	NA	1.00845045258347	NA
57	7.7	NA	NA	0.996766707838408	NA
58	7.3	NA	NA	0.966854172031466	NA
59	7.4	NA	NA	0.957008223308181	NA
60	8.1	NA	NA	1.01311413293215	NA
61	8.3	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