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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 04 Dec 2009 06:37:30 -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/t12599339058jp37bon1odx174.htm/, Retrieved Sun, 28 Apr 2024 06:14:06 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63498, Retrieved Sun, 28 Apr 2024 06:14:06 +0000

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User-defined keywords

Workshop 9 - Populaire technieken 1

Estimated Impact

139

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] [BBWS9-populartheory1] [2009-12-01 20:46:35] [408e92805dcb18620260f240a7fb9d53]
-   PD        [Classical Decomposition] [shw-ws9] [2009-12-04 13:37:30] [5b5bced41faf164488f2c271c918b21f] [Current]
-   PD          [Classical Decomposition] [ws 9 theorie 1] [2009-12-04 19:29:39] [134dc66689e3d457a82860db6471d419] 

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	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=63498&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=63498&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63498&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	1178	NA	NA	0.424259949027869	NA
2	2141	NA	NA	0.613554786370274	NA
3	2238	NA	NA	0.653872748010061	NA
4	2685	NA	NA	0.95446001479855	NA
5	4341	NA	NA	1.30971983361023	NA
6	5376	NA	NA	1.4188127052466	NA
7	4478	4950.17061981218	3378.375	1.46525196871637	0.904615283779836
8	6404	5732.85731800846	3388.5	1.69185696267034	1.11706948991793
9	4617	4773.69957207458	3400.375	1.40387444681089	0.967174395935755
10	3024	3029.1050536394	3424.20833333333	0.88461470762519	0.998314666032045
11	1897	1909.89655703624	3456.75	0.552512202802124	0.993247510191727
12	2075	2169.15239113342	3458.41666666667	0.627209674311489	0.956594847130944
13	1351	1462.65385177145	3447.54166666667	0.424259949027869	0.923663516397794
14	2211	2114.87221905280	3446.91666666667	0.613554786370274	1.04545323357184
15	2453	2255.39782077153	3449.29166666667	0.653872748010061	1.08761300441483
16	3042	3305.33480041466	3463.04166666667	0.95446001479855	0.920330370048557
17	4765	4544.01839105098	3469.45833333333	1.30971983361023	1.04863131922710
18	4992	4933.21177614243	3477	1.4188127052466	1.01191682549326
19	4601	5119.46827436428	3493.91666666667	1.46525196871637	0.89872614760394
20	6266	5945.46734298403	3514.16666666667	1.69185696267034	1.05391210455377
21	4812	4934.32620669719	3514.79166666667	1.40387444681089	0.975209136653519
22	3159	3121.32613690933	3528.45833333333	0.88461470762519	1.01206982591315
23	1916	1960.93487177009	3549.125	0.552512202802124	0.977084974918352
24	2237	2224.03323763568	3545.91666666667	0.627209674311489	1.00583029162734
25	1595	1524.48973934227	3593.29166666667	0.424259949027869	1.04625171218808
26	2453	2214.44704792415	3609.20833333333	0.613554786370274	1.10772574232447
27	2226	2344.13380161607	3585	0.653872748010061	0.949604497177327
28	3597	3431.99959821189	3595.75	0.95446001479855	1.04807704577649
29	4706	4717.93827062247	3602.25	1.30971983361023	0.997469600080017
30	4974	5119.43094370605	3608.25	1.4188127052466	0.971592361474307
31	5756	5289.86486789293	3610.20833333333	1.46525196871637	1.08811853303405
32	5493	6082.930721201	3595.41666666667	1.69185696267034	0.903018668428214
33	5004	5025.11008759096	3579.45833333333	1.40387444681089	0.99579907957776
34	3225	3164.93027020602	3577.75	0.88461470762519	1.01897979565599
35	2006	1975.73759453683	3575.91666666667	0.552512202802124	1.01531701656478
36	2291	2239.53054333846	3570.625	0.627209674311489	1.02298225260407
37	1588	1514.46659804648	3569.66666666667	0.424259949027869	1.04855399389354
38	2105	2194.58321171541	3576.83333333333	0.613554786370274	0.95917985190209
39	2191	2350.83599728317	3595.25	0.653872748010061	0.93200886941161
40	3591	3439.19781749016	3603.29166666667	0.95446001479855	1.04413883427637
41	4668	4711.71710141282	3597.5	1.30971983361023	0.990721620065069
42	4885	5105.00634786937	3598.08333333333	1.4188127052466	0.956903805230096
43	5822	5268.191349189	3595.41666666667	1.46525196871637	1.10512310850217
44	5599	6068.83191317875	3587.08333333333	1.69185696267034	0.922582810020082
45	5340	5045.34927753248	3593.875	1.40387444681089	1.05840046075296
46	3082	3186.45589475823	3602.08333333333	0.88461470762519	0.967218785318803
47	2010	1988.26120446701	3598.58333333333	0.552512202802124	1.01093357124514
48	2301	2275.56896587494	3628.08333333333	0.627209674311489	1.01117568155764
49	1514	1547.87706903243	3648.41666666667	0.424259949027869	0.978113850440588
50	1979	2238.12003676493	3647.79166666667	0.613554786370274	0.8842242451216
51	2480	2413.96196216397	3691.79166666667	0.653872748010061	1.02735670191623
52	3499	3555.76124679743	3725.41666666667	0.95446001479855	0.984036822818586
53	4676	4872.04863771061	3719.91666666667	1.30971983361023	0.959760533547808
54	5585	5287.97406965013	3727.04166666667	1.4188127052466	1.05617008072234
55	5610	NA	NA	1.46525196871637	NA
56	5796	NA	NA	1.69185696267034	NA
57	6199	NA	NA	1.40387444681089	NA
58	3030	NA	NA	0.88461470762519	NA
59	1930	NA	NA	0.552512202802124	NA
60	2552	NA	NA	0.627209674311489	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1178 & NA & NA & 0.424259949027869 & NA \tabularnewline
2 & 2141 & NA & NA & 0.613554786370274 & NA \tabularnewline
3 & 2238 & NA & NA & 0.653872748010061 & NA \tabularnewline
4 & 2685 & NA & NA & 0.95446001479855 & NA \tabularnewline
5 & 4341 & NA & NA & 1.30971983361023 & NA \tabularnewline
6 & 5376 & NA & NA & 1.4188127052466 & NA \tabularnewline
7 & 4478 & 4950.17061981218 & 3378.375 & 1.46525196871637 & 0.904615283779836 \tabularnewline
8 & 6404 & 5732.85731800846 & 3388.5 & 1.69185696267034 & 1.11706948991793 \tabularnewline
9 & 4617 & 4773.69957207458 & 3400.375 & 1.40387444681089 & 0.967174395935755 \tabularnewline
10 & 3024 & 3029.1050536394 & 3424.20833333333 & 0.88461470762519 & 0.998314666032045 \tabularnewline
11 & 1897 & 1909.89655703624 & 3456.75 & 0.552512202802124 & 0.993247510191727 \tabularnewline
12 & 2075 & 2169.15239113342 & 3458.41666666667 & 0.627209674311489 & 0.956594847130944 \tabularnewline
13 & 1351 & 1462.65385177145 & 3447.54166666667 & 0.424259949027869 & 0.923663516397794 \tabularnewline
14 & 2211 & 2114.87221905280 & 3446.91666666667 & 0.613554786370274 & 1.04545323357184 \tabularnewline
15 & 2453 & 2255.39782077153 & 3449.29166666667 & 0.653872748010061 & 1.08761300441483 \tabularnewline
16 & 3042 & 3305.33480041466 & 3463.04166666667 & 0.95446001479855 & 0.920330370048557 \tabularnewline
17 & 4765 & 4544.01839105098 & 3469.45833333333 & 1.30971983361023 & 1.04863131922710 \tabularnewline
18 & 4992 & 4933.21177614243 & 3477 & 1.4188127052466 & 1.01191682549326 \tabularnewline
19 & 4601 & 5119.46827436428 & 3493.91666666667 & 1.46525196871637 & 0.89872614760394 \tabularnewline
20 & 6266 & 5945.46734298403 & 3514.16666666667 & 1.69185696267034 & 1.05391210455377 \tabularnewline
21 & 4812 & 4934.32620669719 & 3514.79166666667 & 1.40387444681089 & 0.975209136653519 \tabularnewline
22 & 3159 & 3121.32613690933 & 3528.45833333333 & 0.88461470762519 & 1.01206982591315 \tabularnewline
23 & 1916 & 1960.93487177009 & 3549.125 & 0.552512202802124 & 0.977084974918352 \tabularnewline
24 & 2237 & 2224.03323763568 & 3545.91666666667 & 0.627209674311489 & 1.00583029162734 \tabularnewline
25 & 1595 & 1524.48973934227 & 3593.29166666667 & 0.424259949027869 & 1.04625171218808 \tabularnewline
26 & 2453 & 2214.44704792415 & 3609.20833333333 & 0.613554786370274 & 1.10772574232447 \tabularnewline
27 & 2226 & 2344.13380161607 & 3585 & 0.653872748010061 & 0.949604497177327 \tabularnewline
28 & 3597 & 3431.99959821189 & 3595.75 & 0.95446001479855 & 1.04807704577649 \tabularnewline
29 & 4706 & 4717.93827062247 & 3602.25 & 1.30971983361023 & 0.997469600080017 \tabularnewline
30 & 4974 & 5119.43094370605 & 3608.25 & 1.4188127052466 & 0.971592361474307 \tabularnewline
31 & 5756 & 5289.86486789293 & 3610.20833333333 & 1.46525196871637 & 1.08811853303405 \tabularnewline
32 & 5493 & 6082.930721201 & 3595.41666666667 & 1.69185696267034 & 0.903018668428214 \tabularnewline
33 & 5004 & 5025.11008759096 & 3579.45833333333 & 1.40387444681089 & 0.99579907957776 \tabularnewline
34 & 3225 & 3164.93027020602 & 3577.75 & 0.88461470762519 & 1.01897979565599 \tabularnewline
35 & 2006 & 1975.73759453683 & 3575.91666666667 & 0.552512202802124 & 1.01531701656478 \tabularnewline
36 & 2291 & 2239.53054333846 & 3570.625 & 0.627209674311489 & 1.02298225260407 \tabularnewline
37 & 1588 & 1514.46659804648 & 3569.66666666667 & 0.424259949027869 & 1.04855399389354 \tabularnewline
38 & 2105 & 2194.58321171541 & 3576.83333333333 & 0.613554786370274 & 0.95917985190209 \tabularnewline
39 & 2191 & 2350.83599728317 & 3595.25 & 0.653872748010061 & 0.93200886941161 \tabularnewline
40 & 3591 & 3439.19781749016 & 3603.29166666667 & 0.95446001479855 & 1.04413883427637 \tabularnewline
41 & 4668 & 4711.71710141282 & 3597.5 & 1.30971983361023 & 0.990721620065069 \tabularnewline
42 & 4885 & 5105.00634786937 & 3598.08333333333 & 1.4188127052466 & 0.956903805230096 \tabularnewline
43 & 5822 & 5268.191349189 & 3595.41666666667 & 1.46525196871637 & 1.10512310850217 \tabularnewline
44 & 5599 & 6068.83191317875 & 3587.08333333333 & 1.69185696267034 & 0.922582810020082 \tabularnewline
45 & 5340 & 5045.34927753248 & 3593.875 & 1.40387444681089 & 1.05840046075296 \tabularnewline
46 & 3082 & 3186.45589475823 & 3602.08333333333 & 0.88461470762519 & 0.967218785318803 \tabularnewline
47 & 2010 & 1988.26120446701 & 3598.58333333333 & 0.552512202802124 & 1.01093357124514 \tabularnewline
48 & 2301 & 2275.56896587494 & 3628.08333333333 & 0.627209674311489 & 1.01117568155764 \tabularnewline
49 & 1514 & 1547.87706903243 & 3648.41666666667 & 0.424259949027869 & 0.978113850440588 \tabularnewline
50 & 1979 & 2238.12003676493 & 3647.79166666667 & 0.613554786370274 & 0.8842242451216 \tabularnewline
51 & 2480 & 2413.96196216397 & 3691.79166666667 & 0.653872748010061 & 1.02735670191623 \tabularnewline
52 & 3499 & 3555.76124679743 & 3725.41666666667 & 0.95446001479855 & 0.984036822818586 \tabularnewline
53 & 4676 & 4872.04863771061 & 3719.91666666667 & 1.30971983361023 & 0.959760533547808 \tabularnewline
54 & 5585 & 5287.97406965013 & 3727.04166666667 & 1.4188127052466 & 1.05617008072234 \tabularnewline
55 & 5610 & NA & NA & 1.46525196871637 & NA \tabularnewline
56 & 5796 & NA & NA & 1.69185696267034 & NA \tabularnewline
57 & 6199 & NA & NA & 1.40387444681089 & NA \tabularnewline
58 & 3030 & NA & NA & 0.88461470762519 & NA \tabularnewline
59 & 1930 & NA & NA & 0.552512202802124 & NA \tabularnewline
60 & 2552 & NA & NA & 0.627209674311489 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63498&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]1178[/C][C]NA[/C][C]NA[/C][C]0.424259949027869[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2141[/C][C]NA[/C][C]NA[/C][C]0.613554786370274[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2238[/C][C]NA[/C][C]NA[/C][C]0.653872748010061[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2685[/C][C]NA[/C][C]NA[/C][C]0.95446001479855[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]4341[/C][C]NA[/C][C]NA[/C][C]1.30971983361023[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5376[/C][C]NA[/C][C]NA[/C][C]1.4188127052466[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]4478[/C][C]4950.17061981218[/C][C]3378.375[/C][C]1.46525196871637[/C][C]0.904615283779836[/C][/ROW]
[ROW][C]8[/C][C]6404[/C][C]5732.85731800846[/C][C]3388.5[/C][C]1.69185696267034[/C][C]1.11706948991793[/C][/ROW]
[ROW][C]9[/C][C]4617[/C][C]4773.69957207458[/C][C]3400.375[/C][C]1.40387444681089[/C][C]0.967174395935755[/C][/ROW]
[ROW][C]10[/C][C]3024[/C][C]3029.1050536394[/C][C]3424.20833333333[/C][C]0.88461470762519[/C][C]0.998314666032045[/C][/ROW]
[ROW][C]11[/C][C]1897[/C][C]1909.89655703624[/C][C]3456.75[/C][C]0.552512202802124[/C][C]0.993247510191727[/C][/ROW]
[ROW][C]12[/C][C]2075[/C][C]2169.15239113342[/C][C]3458.41666666667[/C][C]0.627209674311489[/C][C]0.956594847130944[/C][/ROW]
[ROW][C]13[/C][C]1351[/C][C]1462.65385177145[/C][C]3447.54166666667[/C][C]0.424259949027869[/C][C]0.923663516397794[/C][/ROW]
[ROW][C]14[/C][C]2211[/C][C]2114.87221905280[/C][C]3446.91666666667[/C][C]0.613554786370274[/C][C]1.04545323357184[/C][/ROW]
[ROW][C]15[/C][C]2453[/C][C]2255.39782077153[/C][C]3449.29166666667[/C][C]0.653872748010061[/C][C]1.08761300441483[/C][/ROW]
[ROW][C]16[/C][C]3042[/C][C]3305.33480041466[/C][C]3463.04166666667[/C][C]0.95446001479855[/C][C]0.920330370048557[/C][/ROW]
[ROW][C]17[/C][C]4765[/C][C]4544.01839105098[/C][C]3469.45833333333[/C][C]1.30971983361023[/C][C]1.04863131922710[/C][/ROW]
[ROW][C]18[/C][C]4992[/C][C]4933.21177614243[/C][C]3477[/C][C]1.4188127052466[/C][C]1.01191682549326[/C][/ROW]
[ROW][C]19[/C][C]4601[/C][C]5119.46827436428[/C][C]3493.91666666667[/C][C]1.46525196871637[/C][C]0.89872614760394[/C][/ROW]
[ROW][C]20[/C][C]6266[/C][C]5945.46734298403[/C][C]3514.16666666667[/C][C]1.69185696267034[/C][C]1.05391210455377[/C][/ROW]
[ROW][C]21[/C][C]4812[/C][C]4934.32620669719[/C][C]3514.79166666667[/C][C]1.40387444681089[/C][C]0.975209136653519[/C][/ROW]
[ROW][C]22[/C][C]3159[/C][C]3121.32613690933[/C][C]3528.45833333333[/C][C]0.88461470762519[/C][C]1.01206982591315[/C][/ROW]
[ROW][C]23[/C][C]1916[/C][C]1960.93487177009[/C][C]3549.125[/C][C]0.552512202802124[/C][C]0.977084974918352[/C][/ROW]
[ROW][C]24[/C][C]2237[/C][C]2224.03323763568[/C][C]3545.91666666667[/C][C]0.627209674311489[/C][C]1.00583029162734[/C][/ROW]
[ROW][C]25[/C][C]1595[/C][C]1524.48973934227[/C][C]3593.29166666667[/C][C]0.424259949027869[/C][C]1.04625171218808[/C][/ROW]
[ROW][C]26[/C][C]2453[/C][C]2214.44704792415[/C][C]3609.20833333333[/C][C]0.613554786370274[/C][C]1.10772574232447[/C][/ROW]
[ROW][C]27[/C][C]2226[/C][C]2344.13380161607[/C][C]3585[/C][C]0.653872748010061[/C][C]0.949604497177327[/C][/ROW]
[ROW][C]28[/C][C]3597[/C][C]3431.99959821189[/C][C]3595.75[/C][C]0.95446001479855[/C][C]1.04807704577649[/C][/ROW]
[ROW][C]29[/C][C]4706[/C][C]4717.93827062247[/C][C]3602.25[/C][C]1.30971983361023[/C][C]0.997469600080017[/C][/ROW]
[ROW][C]30[/C][C]4974[/C][C]5119.43094370605[/C][C]3608.25[/C][C]1.4188127052466[/C][C]0.971592361474307[/C][/ROW]
[ROW][C]31[/C][C]5756[/C][C]5289.86486789293[/C][C]3610.20833333333[/C][C]1.46525196871637[/C][C]1.08811853303405[/C][/ROW]
[ROW][C]32[/C][C]5493[/C][C]6082.930721201[/C][C]3595.41666666667[/C][C]1.69185696267034[/C][C]0.903018668428214[/C][/ROW]
[ROW][C]33[/C][C]5004[/C][C]5025.11008759096[/C][C]3579.45833333333[/C][C]1.40387444681089[/C][C]0.99579907957776[/C][/ROW]
[ROW][C]34[/C][C]3225[/C][C]3164.93027020602[/C][C]3577.75[/C][C]0.88461470762519[/C][C]1.01897979565599[/C][/ROW]
[ROW][C]35[/C][C]2006[/C][C]1975.73759453683[/C][C]3575.91666666667[/C][C]0.552512202802124[/C][C]1.01531701656478[/C][/ROW]
[ROW][C]36[/C][C]2291[/C][C]2239.53054333846[/C][C]3570.625[/C][C]0.627209674311489[/C][C]1.02298225260407[/C][/ROW]
[ROW][C]37[/C][C]1588[/C][C]1514.46659804648[/C][C]3569.66666666667[/C][C]0.424259949027869[/C][C]1.04855399389354[/C][/ROW]
[ROW][C]38[/C][C]2105[/C][C]2194.58321171541[/C][C]3576.83333333333[/C][C]0.613554786370274[/C][C]0.95917985190209[/C][/ROW]
[ROW][C]39[/C][C]2191[/C][C]2350.83599728317[/C][C]3595.25[/C][C]0.653872748010061[/C][C]0.93200886941161[/C][/ROW]
[ROW][C]40[/C][C]3591[/C][C]3439.19781749016[/C][C]3603.29166666667[/C][C]0.95446001479855[/C][C]1.04413883427637[/C][/ROW]
[ROW][C]41[/C][C]4668[/C][C]4711.71710141282[/C][C]3597.5[/C][C]1.30971983361023[/C][C]0.990721620065069[/C][/ROW]
[ROW][C]42[/C][C]4885[/C][C]5105.00634786937[/C][C]3598.08333333333[/C][C]1.4188127052466[/C][C]0.956903805230096[/C][/ROW]
[ROW][C]43[/C][C]5822[/C][C]5268.191349189[/C][C]3595.41666666667[/C][C]1.46525196871637[/C][C]1.10512310850217[/C][/ROW]
[ROW][C]44[/C][C]5599[/C][C]6068.83191317875[/C][C]3587.08333333333[/C][C]1.69185696267034[/C][C]0.922582810020082[/C][/ROW]
[ROW][C]45[/C][C]5340[/C][C]5045.34927753248[/C][C]3593.875[/C][C]1.40387444681089[/C][C]1.05840046075296[/C][/ROW]
[ROW][C]46[/C][C]3082[/C][C]3186.45589475823[/C][C]3602.08333333333[/C][C]0.88461470762519[/C][C]0.967218785318803[/C][/ROW]
[ROW][C]47[/C][C]2010[/C][C]1988.26120446701[/C][C]3598.58333333333[/C][C]0.552512202802124[/C][C]1.01093357124514[/C][/ROW]
[ROW][C]48[/C][C]2301[/C][C]2275.56896587494[/C][C]3628.08333333333[/C][C]0.627209674311489[/C][C]1.01117568155764[/C][/ROW]
[ROW][C]49[/C][C]1514[/C][C]1547.87706903243[/C][C]3648.41666666667[/C][C]0.424259949027869[/C][C]0.978113850440588[/C][/ROW]
[ROW][C]50[/C][C]1979[/C][C]2238.12003676493[/C][C]3647.79166666667[/C][C]0.613554786370274[/C][C]0.8842242451216[/C][/ROW]
[ROW][C]51[/C][C]2480[/C][C]2413.96196216397[/C][C]3691.79166666667[/C][C]0.653872748010061[/C][C]1.02735670191623[/C][/ROW]
[ROW][C]52[/C][C]3499[/C][C]3555.76124679743[/C][C]3725.41666666667[/C][C]0.95446001479855[/C][C]0.984036822818586[/C][/ROW]
[ROW][C]53[/C][C]4676[/C][C]4872.04863771061[/C][C]3719.91666666667[/C][C]1.30971983361023[/C][C]0.959760533547808[/C][/ROW]
[ROW][C]54[/C][C]5585[/C][C]5287.97406965013[/C][C]3727.04166666667[/C][C]1.4188127052466[/C][C]1.05617008072234[/C][/ROW]
[ROW][C]55[/C][C]5610[/C][C]NA[/C][C]NA[/C][C]1.46525196871637[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]5796[/C][C]NA[/C][C]NA[/C][C]1.69185696267034[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]6199[/C][C]NA[/C][C]NA[/C][C]1.40387444681089[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]3030[/C][C]NA[/C][C]NA[/C][C]0.88461470762519[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]1930[/C][C]NA[/C][C]NA[/C][C]0.552512202802124[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]2552[/C][C]NA[/C][C]NA[/C][C]0.627209674311489[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63498&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63498&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	1178	NA	NA	0.424259949027869	NA
2	2141	NA	NA	0.613554786370274	NA
3	2238	NA	NA	0.653872748010061	NA
4	2685	NA	NA	0.95446001479855	NA
5	4341	NA	NA	1.30971983361023	NA
6	5376	NA	NA	1.4188127052466	NA
7	4478	4950.17061981218	3378.375	1.46525196871637	0.904615283779836
8	6404	5732.85731800846	3388.5	1.69185696267034	1.11706948991793
9	4617	4773.69957207458	3400.375	1.40387444681089	0.967174395935755
10	3024	3029.1050536394	3424.20833333333	0.88461470762519	0.998314666032045
11	1897	1909.89655703624	3456.75	0.552512202802124	0.993247510191727
12	2075	2169.15239113342	3458.41666666667	0.627209674311489	0.956594847130944
13	1351	1462.65385177145	3447.54166666667	0.424259949027869	0.923663516397794
14	2211	2114.87221905280	3446.91666666667	0.613554786370274	1.04545323357184
15	2453	2255.39782077153	3449.29166666667	0.653872748010061	1.08761300441483
16	3042	3305.33480041466	3463.04166666667	0.95446001479855	0.920330370048557
17	4765	4544.01839105098	3469.45833333333	1.30971983361023	1.04863131922710
18	4992	4933.21177614243	3477	1.4188127052466	1.01191682549326
19	4601	5119.46827436428	3493.91666666667	1.46525196871637	0.89872614760394
20	6266	5945.46734298403	3514.16666666667	1.69185696267034	1.05391210455377
21	4812	4934.32620669719	3514.79166666667	1.40387444681089	0.975209136653519
22	3159	3121.32613690933	3528.45833333333	0.88461470762519	1.01206982591315
23	1916	1960.93487177009	3549.125	0.552512202802124	0.977084974918352
24	2237	2224.03323763568	3545.91666666667	0.627209674311489	1.00583029162734
25	1595	1524.48973934227	3593.29166666667	0.424259949027869	1.04625171218808
26	2453	2214.44704792415	3609.20833333333	0.613554786370274	1.10772574232447
27	2226	2344.13380161607	3585	0.653872748010061	0.949604497177327
28	3597	3431.99959821189	3595.75	0.95446001479855	1.04807704577649
29	4706	4717.93827062247	3602.25	1.30971983361023	0.997469600080017
30	4974	5119.43094370605	3608.25	1.4188127052466	0.971592361474307
31	5756	5289.86486789293	3610.20833333333	1.46525196871637	1.08811853303405
32	5493	6082.930721201	3595.41666666667	1.69185696267034	0.903018668428214
33	5004	5025.11008759096	3579.45833333333	1.40387444681089	0.99579907957776
34	3225	3164.93027020602	3577.75	0.88461470762519	1.01897979565599
35	2006	1975.73759453683	3575.91666666667	0.552512202802124	1.01531701656478
36	2291	2239.53054333846	3570.625	0.627209674311489	1.02298225260407
37	1588	1514.46659804648	3569.66666666667	0.424259949027869	1.04855399389354
38	2105	2194.58321171541	3576.83333333333	0.613554786370274	0.95917985190209
39	2191	2350.83599728317	3595.25	0.653872748010061	0.93200886941161
40	3591	3439.19781749016	3603.29166666667	0.95446001479855	1.04413883427637
41	4668	4711.71710141282	3597.5	1.30971983361023	0.990721620065069
42	4885	5105.00634786937	3598.08333333333	1.4188127052466	0.956903805230096
43	5822	5268.191349189	3595.41666666667	1.46525196871637	1.10512310850217
44	5599	6068.83191317875	3587.08333333333	1.69185696267034	0.922582810020082
45	5340	5045.34927753248	3593.875	1.40387444681089	1.05840046075296
46	3082	3186.45589475823	3602.08333333333	0.88461470762519	0.967218785318803
47	2010	1988.26120446701	3598.58333333333	0.552512202802124	1.01093357124514
48	2301	2275.56896587494	3628.08333333333	0.627209674311489	1.01117568155764
49	1514	1547.87706903243	3648.41666666667	0.424259949027869	0.978113850440588
50	1979	2238.12003676493	3647.79166666667	0.613554786370274	0.8842242451216
51	2480	2413.96196216397	3691.79166666667	0.653872748010061	1.02735670191623
52	3499	3555.76124679743	3725.41666666667	0.95446001479855	0.984036822818586
53	4676	4872.04863771061	3719.91666666667	1.30971983361023	0.959760533547808
54	5585	5287.97406965013	3727.04166666667	1.4188127052466	1.05617008072234
55	5610	NA	NA	1.46525196871637	NA
56	5796	NA	NA	1.69185696267034	NA
57	6199	NA	NA	1.40387444681089	NA
58	3030	NA	NA	0.88461470762519	NA
59	1930	NA	NA	0.552512202802124	NA
60	2552	NA	NA	0.627209674311489	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