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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 02 Dec 2009 13:02:57 -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/02/t1259784396ewiujhg40ml5kb2.htm/, Retrieved Sun, 28 Apr 2024 15:22:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62561, Retrieved Sun, 28 Apr 2024 15:22:22 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

ws 8 Ad hoc forecasting link 1

Estimated Impact

160

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]
-   PD      [Classical Decomposition] [ws 8 Ad hoc forec...] [2009-12-02 20:02:57] [88e98f4c87ea17c4967db8279bda8533] [Current]
-   PD        [Classical Decomposition] [Workshop 9] [2009-12-04 12:04:03] [4fe1472705bb0a32f118ba3ca90ffa8e] 
-   PD          [Classical Decomposition] [WS9] [2009-12-11 12:41:48] [4fe1472705bb0a32f118ba3ca90ffa8e] 
-   PD        [Classical Decomposition] [ws9: classical de...] [2009-12-04 17:14:02] [bd8e774728cf1f2f4e6868fd314defe3] 

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Dataseries X:

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Histogram

Boxplots

8.2
8.0
7.5
6.8
6.5
6.6
7.6
8.0
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7.0
7.1
7.2
7.1
6.9
7.0
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8.0
8.1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62561&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]3 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=62561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62561&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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.2	NA	NA	1.04719037696786	NA
2	8	NA	NA	1.04798979186281	NA
3	7.5	NA	NA	1.02767691179036	NA
4	6.8	NA	NA	1.01399383174475	NA
5	6.5	NA	NA	0.990039435715469	NA
6	6.6	NA	NA	0.957980648057883	NA
7	7.6	7.60186047960396	7.49166666666667	1.01470885156004	0.999755259964458
8	8	7.50513183142118	7.46666666666667	1.00515158456534	1.06593730525918
9	8.1	7.38266074585126	7.47083333333333	0.988197757392248	1.09716540944291
10	7.7	7.2421107924289	7.5125	0.964008092170236	1.06322593242426
11	7.5	7.22832576067654	7.58333333333333	0.953185814594709	1.03758467013225
12	7.6	7.56843382527575	7.64583333333333	0.9898769035783	1.00417076709039
13	7.8	8.02409626351622	7.6625	1.04719037696786	0.972072086854799
14	7.8	8.0040220353522	7.6375	1.04798979186281	0.974510060760568
15	7.8	7.8060625424743	7.59583333333333	1.02767691179036	0.99922335461171
16	7.5	7.68100327546647	7.575	1.01399383174475	0.97643494359069
17	7.5	7.50779905417564	7.58333333333333	0.990039435715469	0.998961206324335
18	7.1	7.28464451127349	7.60416666666667	0.957980648057883	0.974652913949646
19	7.5	7.74138294669347	7.62916666666667	1.01470885156004	0.9688191440269
20	7.5	7.69778588512953	7.65833333333333	1.00515158456534	0.974306133207522
21	7.6	7.60088775060871	7.69166666666667	0.988197757392248	0.999883204352197
22	7.7	7.4590126131672	7.7375	0.964008092170236	1.03230821548785
23	7.7	7.41896292359548	7.78333333333333	0.953185814594709	1.03788091129431
24	7.9	7.72928882210722	7.80833333333333	0.9898769035783	1.02208627233653
25	8.1	8.15935835387457	7.79166666666667	1.04719037696786	0.992725119880734
26	8.2	8.10008776627296	7.72916666666667	1.04798979186281	1.0123347100192
27	8.2	7.86601036232875	7.65416666666667	1.02767691179036	1.04245985223599
28	8.2	7.68945322406434	7.58333333333333	1.01399383174475	1.06639571905293
29	7.9	7.44592158944342	7.52083333333333	0.990039435715469	1.06098350689059
30	7.3	7.14493900009838	7.45833333333333	0.957980648057883	1.02170221465844
31	6.9	7.49616164089979	7.3875	1.01470885156004	0.920471079806087
32	6.6	7.34179469892931	7.30416666666667	1.00515158456534	0.898962756471862
33	6.7	7.11914134387999	7.20416666666667	0.988197757392248	0.941124733498892
34	6.9	6.84445745440867	7.1	0.964008092170236	1.00811496688544
35	7	6.67627230972377	7.00416666666667	0.953185814594709	1.04848928792265
36	7.1	6.85077307018148	6.92083333333333	0.9898769035783	1.03637938773703
37	7.2	7.19943384165403	6.875	1.04719037696786	1.00007863928726
38	7.1	7.19619657079129	6.86666666666667	1.04798979186281	0.986632303628039
39	6.9	7.04386883289645	6.85416666666667	1.02767691179036	0.979575310626945
40	7	6.91205795306003	6.81666666666667	1.01399383174475	1.01272299039406
41	6.8	6.69101651971038	6.75833333333333	0.990039435715469	1.01628803037156
42	6.4	6.41847034198782	6.7	0.957980648057883	0.99712231404
43	6.7	6.7562697699706	6.65833333333333	1.01470885156004	0.991671473773784
44	6.6	6.6633173793477	6.62916666666667	1.00515158456534	0.9904976191673
45	6.4	6.51798770813304	6.59583333333333	0.988197757392248	0.981898138901702
46	6.3	6.30220290256292	6.5375	0.964008092170236	0.999650455150846
47	6.2	6.1559917192575	6.45833333333333	0.953185814594709	1.00714885314170
48	6.5	6.33933666999936	6.40416666666667	0.9898769035783	1.02534387087548
49	6.8	6.7151082923064	6.4125	1.04719037696786	1.01264189704742
50	6.8	6.7726340299134	6.4625	1.04798979186281	1.00404066866240
51	6.4	6.69274588803475	6.5125	1.02767691179036	0.956259225595564
52	6.1	6.61630975213448	6.525	1.01399383174475	0.921964090032526
53	5.8	6.43525633215055	6.5	0.990039435715469	0.901284999483734
54	6.1	6.19893311014122	6.47083333333333	0.957980648057883	0.984040300422121
55	7.2	6.56601186030309	6.47083333333333	1.01470885156004	1.09655604546344
56	7.3	6.55442595768646	6.52083333333333	1.00515158456534	1.11375123422352
57	6.9	6.54269265206784	6.62083333333333	0.988197757392248	1.05461166631742
58	6.1	6.50705462214909	6.75	0.964008092170236	0.937444105546074
59	5.8	6.56109569046024	6.88333333333333	0.953185814594709	0.883998690711543
60	6.2	6.93738729924458	7.00833333333333	0.9898769035783	0.893708212121172
61	7.1	NA	7.1	NA	NA
62	7.7	NA	7.16666666666667	NA	NA
63	7.9	NA	NA	NA	NA
64	7.7	NA	NA	NA	NA
65	7.4	NA	NA	NA	NA
66	7.5	NA	NA	NA	NA
67	8	NA	NA	NA	NA
68	8.1	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.2 & NA & NA & 1.04719037696786 & NA \tabularnewline
2 & 8 & NA & NA & 1.04798979186281 & NA \tabularnewline
3 & 7.5 & NA & NA & 1.02767691179036 & NA \tabularnewline
4 & 6.8 & NA & NA & 1.01399383174475 & NA \tabularnewline
5 & 6.5 & NA & NA & 0.990039435715469 & NA \tabularnewline
6 & 6.6 & NA & NA & 0.957980648057883 & NA \tabularnewline
7 & 7.6 & 7.60186047960396 & 7.49166666666667 & 1.01470885156004 & 0.999755259964458 \tabularnewline
8 & 8 & 7.50513183142118 & 7.46666666666667 & 1.00515158456534 & 1.06593730525918 \tabularnewline
9 & 8.1 & 7.38266074585126 & 7.47083333333333 & 0.988197757392248 & 1.09716540944291 \tabularnewline
10 & 7.7 & 7.2421107924289 & 7.5125 & 0.964008092170236 & 1.06322593242426 \tabularnewline
11 & 7.5 & 7.22832576067654 & 7.58333333333333 & 0.953185814594709 & 1.03758467013225 \tabularnewline
12 & 7.6 & 7.56843382527575 & 7.64583333333333 & 0.9898769035783 & 1.00417076709039 \tabularnewline
13 & 7.8 & 8.02409626351622 & 7.6625 & 1.04719037696786 & 0.972072086854799 \tabularnewline
14 & 7.8 & 8.0040220353522 & 7.6375 & 1.04798979186281 & 0.974510060760568 \tabularnewline
15 & 7.8 & 7.8060625424743 & 7.59583333333333 & 1.02767691179036 & 0.99922335461171 \tabularnewline
16 & 7.5 & 7.68100327546647 & 7.575 & 1.01399383174475 & 0.97643494359069 \tabularnewline
17 & 7.5 & 7.50779905417564 & 7.58333333333333 & 0.990039435715469 & 0.998961206324335 \tabularnewline
18 & 7.1 & 7.28464451127349 & 7.60416666666667 & 0.957980648057883 & 0.974652913949646 \tabularnewline
19 & 7.5 & 7.74138294669347 & 7.62916666666667 & 1.01470885156004 & 0.9688191440269 \tabularnewline
20 & 7.5 & 7.69778588512953 & 7.65833333333333 & 1.00515158456534 & 0.974306133207522 \tabularnewline
21 & 7.6 & 7.60088775060871 & 7.69166666666667 & 0.988197757392248 & 0.999883204352197 \tabularnewline
22 & 7.7 & 7.4590126131672 & 7.7375 & 0.964008092170236 & 1.03230821548785 \tabularnewline
23 & 7.7 & 7.41896292359548 & 7.78333333333333 & 0.953185814594709 & 1.03788091129431 \tabularnewline
24 & 7.9 & 7.72928882210722 & 7.80833333333333 & 0.9898769035783 & 1.02208627233653 \tabularnewline
25 & 8.1 & 8.15935835387457 & 7.79166666666667 & 1.04719037696786 & 0.992725119880734 \tabularnewline
26 & 8.2 & 8.10008776627296 & 7.72916666666667 & 1.04798979186281 & 1.0123347100192 \tabularnewline
27 & 8.2 & 7.86601036232875 & 7.65416666666667 & 1.02767691179036 & 1.04245985223599 \tabularnewline
28 & 8.2 & 7.68945322406434 & 7.58333333333333 & 1.01399383174475 & 1.06639571905293 \tabularnewline
29 & 7.9 & 7.44592158944342 & 7.52083333333333 & 0.990039435715469 & 1.06098350689059 \tabularnewline
30 & 7.3 & 7.14493900009838 & 7.45833333333333 & 0.957980648057883 & 1.02170221465844 \tabularnewline
31 & 6.9 & 7.49616164089979 & 7.3875 & 1.01470885156004 & 0.920471079806087 \tabularnewline
32 & 6.6 & 7.34179469892931 & 7.30416666666667 & 1.00515158456534 & 0.898962756471862 \tabularnewline
33 & 6.7 & 7.11914134387999 & 7.20416666666667 & 0.988197757392248 & 0.941124733498892 \tabularnewline
34 & 6.9 & 6.84445745440867 & 7.1 & 0.964008092170236 & 1.00811496688544 \tabularnewline
35 & 7 & 6.67627230972377 & 7.00416666666667 & 0.953185814594709 & 1.04848928792265 \tabularnewline
36 & 7.1 & 6.85077307018148 & 6.92083333333333 & 0.9898769035783 & 1.03637938773703 \tabularnewline
37 & 7.2 & 7.19943384165403 & 6.875 & 1.04719037696786 & 1.00007863928726 \tabularnewline
38 & 7.1 & 7.19619657079129 & 6.86666666666667 & 1.04798979186281 & 0.986632303628039 \tabularnewline
39 & 6.9 & 7.04386883289645 & 6.85416666666667 & 1.02767691179036 & 0.979575310626945 \tabularnewline
40 & 7 & 6.91205795306003 & 6.81666666666667 & 1.01399383174475 & 1.01272299039406 \tabularnewline
41 & 6.8 & 6.69101651971038 & 6.75833333333333 & 0.990039435715469 & 1.01628803037156 \tabularnewline
42 & 6.4 & 6.41847034198782 & 6.7 & 0.957980648057883 & 0.99712231404 \tabularnewline
43 & 6.7 & 6.7562697699706 & 6.65833333333333 & 1.01470885156004 & 0.991671473773784 \tabularnewline
44 & 6.6 & 6.6633173793477 & 6.62916666666667 & 1.00515158456534 & 0.9904976191673 \tabularnewline
45 & 6.4 & 6.51798770813304 & 6.59583333333333 & 0.988197757392248 & 0.981898138901702 \tabularnewline
46 & 6.3 & 6.30220290256292 & 6.5375 & 0.964008092170236 & 0.999650455150846 \tabularnewline
47 & 6.2 & 6.1559917192575 & 6.45833333333333 & 0.953185814594709 & 1.00714885314170 \tabularnewline
48 & 6.5 & 6.33933666999936 & 6.40416666666667 & 0.9898769035783 & 1.02534387087548 \tabularnewline
49 & 6.8 & 6.7151082923064 & 6.4125 & 1.04719037696786 & 1.01264189704742 \tabularnewline
50 & 6.8 & 6.7726340299134 & 6.4625 & 1.04798979186281 & 1.00404066866240 \tabularnewline
51 & 6.4 & 6.69274588803475 & 6.5125 & 1.02767691179036 & 0.956259225595564 \tabularnewline
52 & 6.1 & 6.61630975213448 & 6.525 & 1.01399383174475 & 0.921964090032526 \tabularnewline
53 & 5.8 & 6.43525633215055 & 6.5 & 0.990039435715469 & 0.901284999483734 \tabularnewline
54 & 6.1 & 6.19893311014122 & 6.47083333333333 & 0.957980648057883 & 0.984040300422121 \tabularnewline
55 & 7.2 & 6.56601186030309 & 6.47083333333333 & 1.01470885156004 & 1.09655604546344 \tabularnewline
56 & 7.3 & 6.55442595768646 & 6.52083333333333 & 1.00515158456534 & 1.11375123422352 \tabularnewline
57 & 6.9 & 6.54269265206784 & 6.62083333333333 & 0.988197757392248 & 1.05461166631742 \tabularnewline
58 & 6.1 & 6.50705462214909 & 6.75 & 0.964008092170236 & 0.937444105546074 \tabularnewline
59 & 5.8 & 6.56109569046024 & 6.88333333333333 & 0.953185814594709 & 0.883998690711543 \tabularnewline
60 & 6.2 & 6.93738729924458 & 7.00833333333333 & 0.9898769035783 & 0.893708212121172 \tabularnewline
61 & 7.1 & NA & 7.1 & NA & NA \tabularnewline
62 & 7.7 & NA & 7.16666666666667 & NA & NA \tabularnewline
63 & 7.9 & NA & NA & NA & NA \tabularnewline
64 & 7.7 & NA & NA & NA & NA \tabularnewline
65 & 7.4 & NA & NA & NA & NA \tabularnewline
66 & 7.5 & NA & NA & NA & NA \tabularnewline
67 & 8 & NA & NA & NA & NA \tabularnewline
68 & 8.1 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62561&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]8.2[/C][C]NA[/C][C]NA[/C][C]1.04719037696786[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]8[/C][C]NA[/C][C]NA[/C][C]1.04798979186281[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]7.5[/C][C]NA[/C][C]NA[/C][C]1.02767691179036[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]6.8[/C][C]NA[/C][C]NA[/C][C]1.01399383174475[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]6.5[/C][C]NA[/C][C]NA[/C][C]0.990039435715469[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]6.6[/C][C]NA[/C][C]NA[/C][C]0.957980648057883[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]7.6[/C][C]7.60186047960396[/C][C]7.49166666666667[/C][C]1.01470885156004[/C][C]0.999755259964458[/C][/ROW]
[ROW][C]8[/C][C]8[/C][C]7.50513183142118[/C][C]7.46666666666667[/C][C]1.00515158456534[/C][C]1.06593730525918[/C][/ROW]
[ROW][C]9[/C][C]8.1[/C][C]7.38266074585126[/C][C]7.47083333333333[/C][C]0.988197757392248[/C][C]1.09716540944291[/C][/ROW]
[ROW][C]10[/C][C]7.7[/C][C]7.2421107924289[/C][C]7.5125[/C][C]0.964008092170236[/C][C]1.06322593242426[/C][/ROW]
[ROW][C]11[/C][C]7.5[/C][C]7.22832576067654[/C][C]7.58333333333333[/C][C]0.953185814594709[/C][C]1.03758467013225[/C][/ROW]
[ROW][C]12[/C][C]7.6[/C][C]7.56843382527575[/C][C]7.64583333333333[/C][C]0.9898769035783[/C][C]1.00417076709039[/C][/ROW]
[ROW][C]13[/C][C]7.8[/C][C]8.02409626351622[/C][C]7.6625[/C][C]1.04719037696786[/C][C]0.972072086854799[/C][/ROW]
[ROW][C]14[/C][C]7.8[/C][C]8.0040220353522[/C][C]7.6375[/C][C]1.04798979186281[/C][C]0.974510060760568[/C][/ROW]
[ROW][C]15[/C][C]7.8[/C][C]7.8060625424743[/C][C]7.59583333333333[/C][C]1.02767691179036[/C][C]0.99922335461171[/C][/ROW]
[ROW][C]16[/C][C]7.5[/C][C]7.68100327546647[/C][C]7.575[/C][C]1.01399383174475[/C][C]0.97643494359069[/C][/ROW]
[ROW][C]17[/C][C]7.5[/C][C]7.50779905417564[/C][C]7.58333333333333[/C][C]0.990039435715469[/C][C]0.998961206324335[/C][/ROW]
[ROW][C]18[/C][C]7.1[/C][C]7.28464451127349[/C][C]7.60416666666667[/C][C]0.957980648057883[/C][C]0.974652913949646[/C][/ROW]
[ROW][C]19[/C][C]7.5[/C][C]7.74138294669347[/C][C]7.62916666666667[/C][C]1.01470885156004[/C][C]0.9688191440269[/C][/ROW]
[ROW][C]20[/C][C]7.5[/C][C]7.69778588512953[/C][C]7.65833333333333[/C][C]1.00515158456534[/C][C]0.974306133207522[/C][/ROW]
[ROW][C]21[/C][C]7.6[/C][C]7.60088775060871[/C][C]7.69166666666667[/C][C]0.988197757392248[/C][C]0.999883204352197[/C][/ROW]
[ROW][C]22[/C][C]7.7[/C][C]7.4590126131672[/C][C]7.7375[/C][C]0.964008092170236[/C][C]1.03230821548785[/C][/ROW]
[ROW][C]23[/C][C]7.7[/C][C]7.41896292359548[/C][C]7.78333333333333[/C][C]0.953185814594709[/C][C]1.03788091129431[/C][/ROW]
[ROW][C]24[/C][C]7.9[/C][C]7.72928882210722[/C][C]7.80833333333333[/C][C]0.9898769035783[/C][C]1.02208627233653[/C][/ROW]
[ROW][C]25[/C][C]8.1[/C][C]8.15935835387457[/C][C]7.79166666666667[/C][C]1.04719037696786[/C][C]0.992725119880734[/C][/ROW]
[ROW][C]26[/C][C]8.2[/C][C]8.10008776627296[/C][C]7.72916666666667[/C][C]1.04798979186281[/C][C]1.0123347100192[/C][/ROW]
[ROW][C]27[/C][C]8.2[/C][C]7.86601036232875[/C][C]7.65416666666667[/C][C]1.02767691179036[/C][C]1.04245985223599[/C][/ROW]
[ROW][C]28[/C][C]8.2[/C][C]7.68945322406434[/C][C]7.58333333333333[/C][C]1.01399383174475[/C][C]1.06639571905293[/C][/ROW]
[ROW][C]29[/C][C]7.9[/C][C]7.44592158944342[/C][C]7.52083333333333[/C][C]0.990039435715469[/C][C]1.06098350689059[/C][/ROW]
[ROW][C]30[/C][C]7.3[/C][C]7.14493900009838[/C][C]7.45833333333333[/C][C]0.957980648057883[/C][C]1.02170221465844[/C][/ROW]
[ROW][C]31[/C][C]6.9[/C][C]7.49616164089979[/C][C]7.3875[/C][C]1.01470885156004[/C][C]0.920471079806087[/C][/ROW]
[ROW][C]32[/C][C]6.6[/C][C]7.34179469892931[/C][C]7.30416666666667[/C][C]1.00515158456534[/C][C]0.898962756471862[/C][/ROW]
[ROW][C]33[/C][C]6.7[/C][C]7.11914134387999[/C][C]7.20416666666667[/C][C]0.988197757392248[/C][C]0.941124733498892[/C][/ROW]
[ROW][C]34[/C][C]6.9[/C][C]6.84445745440867[/C][C]7.1[/C][C]0.964008092170236[/C][C]1.00811496688544[/C][/ROW]
[ROW][C]35[/C][C]7[/C][C]6.67627230972377[/C][C]7.00416666666667[/C][C]0.953185814594709[/C][C]1.04848928792265[/C][/ROW]
[ROW][C]36[/C][C]7.1[/C][C]6.85077307018148[/C][C]6.92083333333333[/C][C]0.9898769035783[/C][C]1.03637938773703[/C][/ROW]
[ROW][C]37[/C][C]7.2[/C][C]7.19943384165403[/C][C]6.875[/C][C]1.04719037696786[/C][C]1.00007863928726[/C][/ROW]
[ROW][C]38[/C][C]7.1[/C][C]7.19619657079129[/C][C]6.86666666666667[/C][C]1.04798979186281[/C][C]0.986632303628039[/C][/ROW]
[ROW][C]39[/C][C]6.9[/C][C]7.04386883289645[/C][C]6.85416666666667[/C][C]1.02767691179036[/C][C]0.979575310626945[/C][/ROW]
[ROW][C]40[/C][C]7[/C][C]6.91205795306003[/C][C]6.81666666666667[/C][C]1.01399383174475[/C][C]1.01272299039406[/C][/ROW]
[ROW][C]41[/C][C]6.8[/C][C]6.69101651971038[/C][C]6.75833333333333[/C][C]0.990039435715469[/C][C]1.01628803037156[/C][/ROW]
[ROW][C]42[/C][C]6.4[/C][C]6.41847034198782[/C][C]6.7[/C][C]0.957980648057883[/C][C]0.99712231404[/C][/ROW]
[ROW][C]43[/C][C]6.7[/C][C]6.7562697699706[/C][C]6.65833333333333[/C][C]1.01470885156004[/C][C]0.991671473773784[/C][/ROW]
[ROW][C]44[/C][C]6.6[/C][C]6.6633173793477[/C][C]6.62916666666667[/C][C]1.00515158456534[/C][C]0.9904976191673[/C][/ROW]
[ROW][C]45[/C][C]6.4[/C][C]6.51798770813304[/C][C]6.59583333333333[/C][C]0.988197757392248[/C][C]0.981898138901702[/C][/ROW]
[ROW][C]46[/C][C]6.3[/C][C]6.30220290256292[/C][C]6.5375[/C][C]0.964008092170236[/C][C]0.999650455150846[/C][/ROW]
[ROW][C]47[/C][C]6.2[/C][C]6.1559917192575[/C][C]6.45833333333333[/C][C]0.953185814594709[/C][C]1.00714885314170[/C][/ROW]
[ROW][C]48[/C][C]6.5[/C][C]6.33933666999936[/C][C]6.40416666666667[/C][C]0.9898769035783[/C][C]1.02534387087548[/C][/ROW]
[ROW][C]49[/C][C]6.8[/C][C]6.7151082923064[/C][C]6.4125[/C][C]1.04719037696786[/C][C]1.01264189704742[/C][/ROW]
[ROW][C]50[/C][C]6.8[/C][C]6.7726340299134[/C][C]6.4625[/C][C]1.04798979186281[/C][C]1.00404066866240[/C][/ROW]
[ROW][C]51[/C][C]6.4[/C][C]6.69274588803475[/C][C]6.5125[/C][C]1.02767691179036[/C][C]0.956259225595564[/C][/ROW]
[ROW][C]52[/C][C]6.1[/C][C]6.61630975213448[/C][C]6.525[/C][C]1.01399383174475[/C][C]0.921964090032526[/C][/ROW]
[ROW][C]53[/C][C]5.8[/C][C]6.43525633215055[/C][C]6.5[/C][C]0.990039435715469[/C][C]0.901284999483734[/C][/ROW]
[ROW][C]54[/C][C]6.1[/C][C]6.19893311014122[/C][C]6.47083333333333[/C][C]0.957980648057883[/C][C]0.984040300422121[/C][/ROW]
[ROW][C]55[/C][C]7.2[/C][C]6.56601186030309[/C][C]6.47083333333333[/C][C]1.01470885156004[/C][C]1.09655604546344[/C][/ROW]
[ROW][C]56[/C][C]7.3[/C][C]6.55442595768646[/C][C]6.52083333333333[/C][C]1.00515158456534[/C][C]1.11375123422352[/C][/ROW]
[ROW][C]57[/C][C]6.9[/C][C]6.54269265206784[/C][C]6.62083333333333[/C][C]0.988197757392248[/C][C]1.05461166631742[/C][/ROW]
[ROW][C]58[/C][C]6.1[/C][C]6.50705462214909[/C][C]6.75[/C][C]0.964008092170236[/C][C]0.937444105546074[/C][/ROW]
[ROW][C]59[/C][C]5.8[/C][C]6.56109569046024[/C][C]6.88333333333333[/C][C]0.953185814594709[/C][C]0.883998690711543[/C][/ROW]
[ROW][C]60[/C][C]6.2[/C][C]6.93738729924458[/C][C]7.00833333333333[/C][C]0.9898769035783[/C][C]0.893708212121172[/C][/ROW]
[ROW][C]61[/C][C]7.1[/C][C]NA[/C][C]7.1[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]62[/C][C]7.7[/C][C]NA[/C][C]7.16666666666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]63[/C][C]7.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]64[/C][C]7.7[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]65[/C][C]7.4[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]66[/C][C]7.5[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]67[/C][C]8[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]8.1[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62561&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	8.2	NA	NA	1.04719037696786	NA
2	8	NA	NA	1.04798979186281	NA
3	7.5	NA	NA	1.02767691179036	NA
4	6.8	NA	NA	1.01399383174475	NA
5	6.5	NA	NA	0.990039435715469	NA
6	6.6	NA	NA	0.957980648057883	NA
7	7.6	7.60186047960396	7.49166666666667	1.01470885156004	0.999755259964458
8	8	7.50513183142118	7.46666666666667	1.00515158456534	1.06593730525918
9	8.1	7.38266074585126	7.47083333333333	0.988197757392248	1.09716540944291
10	7.7	7.2421107924289	7.5125	0.964008092170236	1.06322593242426
11	7.5	7.22832576067654	7.58333333333333	0.953185814594709	1.03758467013225
12	7.6	7.56843382527575	7.64583333333333	0.9898769035783	1.00417076709039
13	7.8	8.02409626351622	7.6625	1.04719037696786	0.972072086854799
14	7.8	8.0040220353522	7.6375	1.04798979186281	0.974510060760568
15	7.8	7.8060625424743	7.59583333333333	1.02767691179036	0.99922335461171
16	7.5	7.68100327546647	7.575	1.01399383174475	0.97643494359069
17	7.5	7.50779905417564	7.58333333333333	0.990039435715469	0.998961206324335
18	7.1	7.28464451127349	7.60416666666667	0.957980648057883	0.974652913949646
19	7.5	7.74138294669347	7.62916666666667	1.01470885156004	0.9688191440269
20	7.5	7.69778588512953	7.65833333333333	1.00515158456534	0.974306133207522
21	7.6	7.60088775060871	7.69166666666667	0.988197757392248	0.999883204352197
22	7.7	7.4590126131672	7.7375	0.964008092170236	1.03230821548785
23	7.7	7.41896292359548	7.78333333333333	0.953185814594709	1.03788091129431
24	7.9	7.72928882210722	7.80833333333333	0.9898769035783	1.02208627233653
25	8.1	8.15935835387457	7.79166666666667	1.04719037696786	0.992725119880734
26	8.2	8.10008776627296	7.72916666666667	1.04798979186281	1.0123347100192
27	8.2	7.86601036232875	7.65416666666667	1.02767691179036	1.04245985223599
28	8.2	7.68945322406434	7.58333333333333	1.01399383174475	1.06639571905293
29	7.9	7.44592158944342	7.52083333333333	0.990039435715469	1.06098350689059
30	7.3	7.14493900009838	7.45833333333333	0.957980648057883	1.02170221465844
31	6.9	7.49616164089979	7.3875	1.01470885156004	0.920471079806087
32	6.6	7.34179469892931	7.30416666666667	1.00515158456534	0.898962756471862
33	6.7	7.11914134387999	7.20416666666667	0.988197757392248	0.941124733498892
34	6.9	6.84445745440867	7.1	0.964008092170236	1.00811496688544
35	7	6.67627230972377	7.00416666666667	0.953185814594709	1.04848928792265
36	7.1	6.85077307018148	6.92083333333333	0.9898769035783	1.03637938773703
37	7.2	7.19943384165403	6.875	1.04719037696786	1.00007863928726
38	7.1	7.19619657079129	6.86666666666667	1.04798979186281	0.986632303628039
39	6.9	7.04386883289645	6.85416666666667	1.02767691179036	0.979575310626945
40	7	6.91205795306003	6.81666666666667	1.01399383174475	1.01272299039406
41	6.8	6.69101651971038	6.75833333333333	0.990039435715469	1.01628803037156
42	6.4	6.41847034198782	6.7	0.957980648057883	0.99712231404
43	6.7	6.7562697699706	6.65833333333333	1.01470885156004	0.991671473773784
44	6.6	6.6633173793477	6.62916666666667	1.00515158456534	0.9904976191673
45	6.4	6.51798770813304	6.59583333333333	0.988197757392248	0.981898138901702
46	6.3	6.30220290256292	6.5375	0.964008092170236	0.999650455150846
47	6.2	6.1559917192575	6.45833333333333	0.953185814594709	1.00714885314170
48	6.5	6.33933666999936	6.40416666666667	0.9898769035783	1.02534387087548
49	6.8	6.7151082923064	6.4125	1.04719037696786	1.01264189704742
50	6.8	6.7726340299134	6.4625	1.04798979186281	1.00404066866240
51	6.4	6.69274588803475	6.5125	1.02767691179036	0.956259225595564
52	6.1	6.61630975213448	6.525	1.01399383174475	0.921964090032526
53	5.8	6.43525633215055	6.5	0.990039435715469	0.901284999483734
54	6.1	6.19893311014122	6.47083333333333	0.957980648057883	0.984040300422121
55	7.2	6.56601186030309	6.47083333333333	1.01470885156004	1.09655604546344
56	7.3	6.55442595768646	6.52083333333333	1.00515158456534	1.11375123422352
57	6.9	6.54269265206784	6.62083333333333	0.988197757392248	1.05461166631742
58	6.1	6.50705462214909	6.75	0.964008092170236	0.937444105546074
59	5.8	6.56109569046024	6.88333333333333	0.953185814594709	0.883998690711543
60	6.2	6.93738729924458	7.00833333333333	0.9898769035783	0.893708212121172
61	7.1	NA	7.1	NA	NA
62	7.7	NA	7.16666666666667	NA	NA
63	7.9	NA	NA	NA	NA
64	7.7	NA	NA	NA	NA
65	7.4	NA	NA	NA	NA
66	7.5	NA	NA	NA	NA
67	8	NA	NA	NA	NA
68	8.1	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 = 0.01 ; par2 = 0.99 ; par3 = 0.005 ;

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