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rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 07 Dec 2012 16:25:41 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/07/t1354915574tgo2yi49km6j1gs.htm/, Retrieved Thu, 25 Apr 2024 13:47:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197512, Retrieved Thu, 25 Apr 2024 13:47:20 +0000

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Estimated Impact

104

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [] [2012-12-07 21:25:41] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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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	4 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197512&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197512&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	4 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	246.24	NA	NA	0.995925625983787	NA
2	247.57	NA	NA	0.99962516234586	NA
3	247.84	NA	NA	1.00295847369832	NA
4	248.27	NA	NA	1.0040549854012	NA
5	248.3	NA	NA	1.00274854069997	NA
6	248.31	NA	NA	1.00180465386442	NA
7	248.31	248.048777902092	248.22375	0.999295103317439	1.00105310778032
8	248.38	248.140460231857	248.344166666667	0.999179741414731	1.00096533942074
9	248.37	247.991671738858	248.372083333333	0.998468380224663	1.0015255684132
10	248.41	248.27440486014	248.367083333333	0.999626848808024	1.00054615029663
11	248.68	247.942864817592	248.26375	0.998707482737984	1.00297300421591
12	248.75	247.486264441763	248.080416666667	0.997605001503597	1.00510628564008
13	248.75	246.876268704023	247.88625	0.995925625983787	1.00758975865041
14	247.95	247.608402244522	247.70125	0.99962516234586	1.00137958870693
15	248.13	248.25980359836	247.5275	1.00295847369832	0.999477146132885
16	247.86	248.356765845181	247.35375	1.0040549854012	0.997999789361522
17	246.23	247.861473349679	247.182083333333	1.00274854069997	0.993417801776004
18	245.98	247.462028830138	247.01625	1.00180465386442	0.994011085914294
19	245.98	246.678078118708	246.852083333333	0.999295103317439	0.997170084492176
20	246.27	246.565919489344	246.768333333333	0.999179741414731	0.998799836206248
21	246.31	246.382889561222	246.760833333333	0.998468380224663	0.999704161432024
22	246.3	246.693744905462	246.785833333333	0.999626848808024	0.998403912082922
23	246.67	246.59960325331	246.91875	0.998707482737984	1.00028546982948
24	246.78	246.544359052843	247.13625	0.997605001503597	1.00095577505023
25	246.78	246.359217316534	247.367083333333	0.995925625983787	1.00170800462857
26	247.91	247.504691133929	247.5975	0.99962516234586	1.00163758054126
27	247.99	248.559855341742	247.826666666667	1.00295847369832	0.997707371767825
28	248.6	249.083032284622	248.077083333333	1.0040549854012	0.998060757972186
29	248.68	249.007531369321	248.325	1.00274854069997	0.998684652759217
30	248.75	248.99687704358	248.548333333333	1.00180465386442	0.999008513494182
31	248.75	248.596308344118	248.771666666667	0.999295103317439	1.00061823788497
32	249.03	248.800335186083	249.004583333333	0.999179741414731	1.0009230888445
33	249.05	249.002204945344	249.384166666667	0.998468380224663	1.00019194631094
34	249.57	249.823409964605	249.916666666667	0.999626848808024	0.998985643640677
35	249.35	250.200359856698	250.524166666667	0.998707482737984	0.996601284437861
36	249.46	250.588400327689	251.19	0.997605001503597	0.995496996963096
37	249.46	250.828848532147	251.855	0.995925625983787	0.994542698975189
38	250.82	252.44117339398	252.535833333333	0.99962516234586	0.993578015138401
39	254.19	253.997143967279	253.247916666667	1.00295847369832	1.00075928425694
40	255.18	255.020762454538	253.990833333333	1.0040549854012	1.00062441012226
41	256.68	255.460218228725	254.76	1.00274854069997	1.00477484040268
42	256.73	256.004918015967	255.54375	1.00180465386442	1.00283229708887
43	256.73	256.150562952238	256.33125	0.999295103317439	1.00226209554679
44	257.39	256.954058200919	257.165	0.999179741414731	1.00169657487464
45	257.78	257.552838536493	257.947916666667	0.998468380224663	1.0008819994561
46	258.67	258.510583791934	258.607083333333	0.999626848808024	1.00061667188139
47	258.71	258.861650500743	259.196666666667	0.998707482737984	0.999414163896237
48	258.91	259.10212767802	259.724166666667	0.997605001503597	0.999258486683447
49	258.91	259.172215463826	260.2325	0.995925625983787	0.998988257813993
50	261.38	260.626437431656	260.724166666667	0.99962516234586	1.00289135122196
51	262.42	261.976932323641	261.204166666667	1.00295847369832	1.00169124690647
52	262.77	262.800096810178	261.73875	1.0040549854012	0.999885476411375
53	263.24	263.058963107771	262.337916666667	1.00274854069997	1.0006881989121
54	262.83	263.426620826679	262.952083333333	1.00180465386442	0.997735153627196
55	262.83	263.38046302474	263.56625	0.999295103317439	0.997910008136449
56	263.09	263.979957082634	264.196666666667	0.999179741414731	0.996628694494577
57	263.6	264.470144268991	264.875833333333	0.998468380224663	0.996709858228435
58	265.68	265.557536564844	265.656666666667	0.999626848808024	1.00046115593909
59	266.08	266.149302227905	266.49375	0.998707482737984	0.999739611461216
60	266.28	266.761240077064	267.401666666667	0.997605001503597	0.998195989503853
61	266.28	267.299798509875	268.393333333333	0.995925625983787	0.99618481377255
62	269.14	269.267363939167	269.368333333333	0.99962516234586	0.999526998232152
63	270.96	271.128510496774	270.32875	1.00295847369832	0.999378484776589
64	272.97	272.304732315732	271.205	1.0040549854012	1.00244309997337
65	273.13	272.735068713634	271.9875	1.00274854069997	1.00144803999071
66	274.73	273.247228364791	272.755	1.00180465386442	1.00542648371617
67	274.73	NA	NA	0.999295103317439	NA
68	274.59	NA	NA	0.999179741414731	NA
69	275.15	NA	NA	0.998468380224663	NA
70	275.16	NA	NA	0.999626848808024	NA
71	275.38	NA	NA	0.998707482737984	NA
72	275.4	NA	NA	0.997605001503597	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 246.24 & NA & NA & 0.995925625983787 & NA \tabularnewline
2 & 247.57 & NA & NA & 0.99962516234586 & NA \tabularnewline
3 & 247.84 & NA & NA & 1.00295847369832 & NA \tabularnewline
4 & 248.27 & NA & NA & 1.0040549854012 & NA \tabularnewline
5 & 248.3 & NA & NA & 1.00274854069997 & NA \tabularnewline
6 & 248.31 & NA & NA & 1.00180465386442 & NA \tabularnewline
7 & 248.31 & 248.048777902092 & 248.22375 & 0.999295103317439 & 1.00105310778032 \tabularnewline
8 & 248.38 & 248.140460231857 & 248.344166666667 & 0.999179741414731 & 1.00096533942074 \tabularnewline
9 & 248.37 & 247.991671738858 & 248.372083333333 & 0.998468380224663 & 1.0015255684132 \tabularnewline
10 & 248.41 & 248.27440486014 & 248.367083333333 & 0.999626848808024 & 1.00054615029663 \tabularnewline
11 & 248.68 & 247.942864817592 & 248.26375 & 0.998707482737984 & 1.00297300421591 \tabularnewline
12 & 248.75 & 247.486264441763 & 248.080416666667 & 0.997605001503597 & 1.00510628564008 \tabularnewline
13 & 248.75 & 246.876268704023 & 247.88625 & 0.995925625983787 & 1.00758975865041 \tabularnewline
14 & 247.95 & 247.608402244522 & 247.70125 & 0.99962516234586 & 1.00137958870693 \tabularnewline
15 & 248.13 & 248.25980359836 & 247.5275 & 1.00295847369832 & 0.999477146132885 \tabularnewline
16 & 247.86 & 248.356765845181 & 247.35375 & 1.0040549854012 & 0.997999789361522 \tabularnewline
17 & 246.23 & 247.861473349679 & 247.182083333333 & 1.00274854069997 & 0.993417801776004 \tabularnewline
18 & 245.98 & 247.462028830138 & 247.01625 & 1.00180465386442 & 0.994011085914294 \tabularnewline
19 & 245.98 & 246.678078118708 & 246.852083333333 & 0.999295103317439 & 0.997170084492176 \tabularnewline
20 & 246.27 & 246.565919489344 & 246.768333333333 & 0.999179741414731 & 0.998799836206248 \tabularnewline
21 & 246.31 & 246.382889561222 & 246.760833333333 & 0.998468380224663 & 0.999704161432024 \tabularnewline
22 & 246.3 & 246.693744905462 & 246.785833333333 & 0.999626848808024 & 0.998403912082922 \tabularnewline
23 & 246.67 & 246.59960325331 & 246.91875 & 0.998707482737984 & 1.00028546982948 \tabularnewline
24 & 246.78 & 246.544359052843 & 247.13625 & 0.997605001503597 & 1.00095577505023 \tabularnewline
25 & 246.78 & 246.359217316534 & 247.367083333333 & 0.995925625983787 & 1.00170800462857 \tabularnewline
26 & 247.91 & 247.504691133929 & 247.5975 & 0.99962516234586 & 1.00163758054126 \tabularnewline
27 & 247.99 & 248.559855341742 & 247.826666666667 & 1.00295847369832 & 0.997707371767825 \tabularnewline
28 & 248.6 & 249.083032284622 & 248.077083333333 & 1.0040549854012 & 0.998060757972186 \tabularnewline
29 & 248.68 & 249.007531369321 & 248.325 & 1.00274854069997 & 0.998684652759217 \tabularnewline
30 & 248.75 & 248.99687704358 & 248.548333333333 & 1.00180465386442 & 0.999008513494182 \tabularnewline
31 & 248.75 & 248.596308344118 & 248.771666666667 & 0.999295103317439 & 1.00061823788497 \tabularnewline
32 & 249.03 & 248.800335186083 & 249.004583333333 & 0.999179741414731 & 1.0009230888445 \tabularnewline
33 & 249.05 & 249.002204945344 & 249.384166666667 & 0.998468380224663 & 1.00019194631094 \tabularnewline
34 & 249.57 & 249.823409964605 & 249.916666666667 & 0.999626848808024 & 0.998985643640677 \tabularnewline
35 & 249.35 & 250.200359856698 & 250.524166666667 & 0.998707482737984 & 0.996601284437861 \tabularnewline
36 & 249.46 & 250.588400327689 & 251.19 & 0.997605001503597 & 0.995496996963096 \tabularnewline
37 & 249.46 & 250.828848532147 & 251.855 & 0.995925625983787 & 0.994542698975189 \tabularnewline
38 & 250.82 & 252.44117339398 & 252.535833333333 & 0.99962516234586 & 0.993578015138401 \tabularnewline
39 & 254.19 & 253.997143967279 & 253.247916666667 & 1.00295847369832 & 1.00075928425694 \tabularnewline
40 & 255.18 & 255.020762454538 & 253.990833333333 & 1.0040549854012 & 1.00062441012226 \tabularnewline
41 & 256.68 & 255.460218228725 & 254.76 & 1.00274854069997 & 1.00477484040268 \tabularnewline
42 & 256.73 & 256.004918015967 & 255.54375 & 1.00180465386442 & 1.00283229708887 \tabularnewline
43 & 256.73 & 256.150562952238 & 256.33125 & 0.999295103317439 & 1.00226209554679 \tabularnewline
44 & 257.39 & 256.954058200919 & 257.165 & 0.999179741414731 & 1.00169657487464 \tabularnewline
45 & 257.78 & 257.552838536493 & 257.947916666667 & 0.998468380224663 & 1.0008819994561 \tabularnewline
46 & 258.67 & 258.510583791934 & 258.607083333333 & 0.999626848808024 & 1.00061667188139 \tabularnewline
47 & 258.71 & 258.861650500743 & 259.196666666667 & 0.998707482737984 & 0.999414163896237 \tabularnewline
48 & 258.91 & 259.10212767802 & 259.724166666667 & 0.997605001503597 & 0.999258486683447 \tabularnewline
49 & 258.91 & 259.172215463826 & 260.2325 & 0.995925625983787 & 0.998988257813993 \tabularnewline
50 & 261.38 & 260.626437431656 & 260.724166666667 & 0.99962516234586 & 1.00289135122196 \tabularnewline
51 & 262.42 & 261.976932323641 & 261.204166666667 & 1.00295847369832 & 1.00169124690647 \tabularnewline
52 & 262.77 & 262.800096810178 & 261.73875 & 1.0040549854012 & 0.999885476411375 \tabularnewline
53 & 263.24 & 263.058963107771 & 262.337916666667 & 1.00274854069997 & 1.0006881989121 \tabularnewline
54 & 262.83 & 263.426620826679 & 262.952083333333 & 1.00180465386442 & 0.997735153627196 \tabularnewline
55 & 262.83 & 263.38046302474 & 263.56625 & 0.999295103317439 & 0.997910008136449 \tabularnewline
56 & 263.09 & 263.979957082634 & 264.196666666667 & 0.999179741414731 & 0.996628694494577 \tabularnewline
57 & 263.6 & 264.470144268991 & 264.875833333333 & 0.998468380224663 & 0.996709858228435 \tabularnewline
58 & 265.68 & 265.557536564844 & 265.656666666667 & 0.999626848808024 & 1.00046115593909 \tabularnewline
59 & 266.08 & 266.149302227905 & 266.49375 & 0.998707482737984 & 0.999739611461216 \tabularnewline
60 & 266.28 & 266.761240077064 & 267.401666666667 & 0.997605001503597 & 0.998195989503853 \tabularnewline
61 & 266.28 & 267.299798509875 & 268.393333333333 & 0.995925625983787 & 0.99618481377255 \tabularnewline
62 & 269.14 & 269.267363939167 & 269.368333333333 & 0.99962516234586 & 0.999526998232152 \tabularnewline
63 & 270.96 & 271.128510496774 & 270.32875 & 1.00295847369832 & 0.999378484776589 \tabularnewline
64 & 272.97 & 272.304732315732 & 271.205 & 1.0040549854012 & 1.00244309997337 \tabularnewline
65 & 273.13 & 272.735068713634 & 271.9875 & 1.00274854069997 & 1.00144803999071 \tabularnewline
66 & 274.73 & 273.247228364791 & 272.755 & 1.00180465386442 & 1.00542648371617 \tabularnewline
67 & 274.73 & NA & NA & 0.999295103317439 & NA \tabularnewline
68 & 274.59 & NA & NA & 0.999179741414731 & NA \tabularnewline
69 & 275.15 & NA & NA & 0.998468380224663 & NA \tabularnewline
70 & 275.16 & NA & NA & 0.999626848808024 & NA \tabularnewline
71 & 275.38 & NA & NA & 0.998707482737984 & NA \tabularnewline
72 & 275.4 & NA & NA & 0.997605001503597 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197512&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]246.24[/C][C]NA[/C][C]NA[/C][C]0.995925625983787[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]247.57[/C][C]NA[/C][C]NA[/C][C]0.99962516234586[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]247.84[/C][C]NA[/C][C]NA[/C][C]1.00295847369832[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]248.27[/C][C]NA[/C][C]NA[/C][C]1.0040549854012[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]248.3[/C][C]NA[/C][C]NA[/C][C]1.00274854069997[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]248.31[/C][C]NA[/C][C]NA[/C][C]1.00180465386442[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]248.31[/C][C]248.048777902092[/C][C]248.22375[/C][C]0.999295103317439[/C][C]1.00105310778032[/C][/ROW]
[ROW][C]8[/C][C]248.38[/C][C]248.140460231857[/C][C]248.344166666667[/C][C]0.999179741414731[/C][C]1.00096533942074[/C][/ROW]
[ROW][C]9[/C][C]248.37[/C][C]247.991671738858[/C][C]248.372083333333[/C][C]0.998468380224663[/C][C]1.0015255684132[/C][/ROW]
[ROW][C]10[/C][C]248.41[/C][C]248.27440486014[/C][C]248.367083333333[/C][C]0.999626848808024[/C][C]1.00054615029663[/C][/ROW]
[ROW][C]11[/C][C]248.68[/C][C]247.942864817592[/C][C]248.26375[/C][C]0.998707482737984[/C][C]1.00297300421591[/C][/ROW]
[ROW][C]12[/C][C]248.75[/C][C]247.486264441763[/C][C]248.080416666667[/C][C]0.997605001503597[/C][C]1.00510628564008[/C][/ROW]
[ROW][C]13[/C][C]248.75[/C][C]246.876268704023[/C][C]247.88625[/C][C]0.995925625983787[/C][C]1.00758975865041[/C][/ROW]
[ROW][C]14[/C][C]247.95[/C][C]247.608402244522[/C][C]247.70125[/C][C]0.99962516234586[/C][C]1.00137958870693[/C][/ROW]
[ROW][C]15[/C][C]248.13[/C][C]248.25980359836[/C][C]247.5275[/C][C]1.00295847369832[/C][C]0.999477146132885[/C][/ROW]
[ROW][C]16[/C][C]247.86[/C][C]248.356765845181[/C][C]247.35375[/C][C]1.0040549854012[/C][C]0.997999789361522[/C][/ROW]
[ROW][C]17[/C][C]246.23[/C][C]247.861473349679[/C][C]247.182083333333[/C][C]1.00274854069997[/C][C]0.993417801776004[/C][/ROW]
[ROW][C]18[/C][C]245.98[/C][C]247.462028830138[/C][C]247.01625[/C][C]1.00180465386442[/C][C]0.994011085914294[/C][/ROW]
[ROW][C]19[/C][C]245.98[/C][C]246.678078118708[/C][C]246.852083333333[/C][C]0.999295103317439[/C][C]0.997170084492176[/C][/ROW]
[ROW][C]20[/C][C]246.27[/C][C]246.565919489344[/C][C]246.768333333333[/C][C]0.999179741414731[/C][C]0.998799836206248[/C][/ROW]
[ROW][C]21[/C][C]246.31[/C][C]246.382889561222[/C][C]246.760833333333[/C][C]0.998468380224663[/C][C]0.999704161432024[/C][/ROW]
[ROW][C]22[/C][C]246.3[/C][C]246.693744905462[/C][C]246.785833333333[/C][C]0.999626848808024[/C][C]0.998403912082922[/C][/ROW]
[ROW][C]23[/C][C]246.67[/C][C]246.59960325331[/C][C]246.91875[/C][C]0.998707482737984[/C][C]1.00028546982948[/C][/ROW]
[ROW][C]24[/C][C]246.78[/C][C]246.544359052843[/C][C]247.13625[/C][C]0.997605001503597[/C][C]1.00095577505023[/C][/ROW]
[ROW][C]25[/C][C]246.78[/C][C]246.359217316534[/C][C]247.367083333333[/C][C]0.995925625983787[/C][C]1.00170800462857[/C][/ROW]
[ROW][C]26[/C][C]247.91[/C][C]247.504691133929[/C][C]247.5975[/C][C]0.99962516234586[/C][C]1.00163758054126[/C][/ROW]
[ROW][C]27[/C][C]247.99[/C][C]248.559855341742[/C][C]247.826666666667[/C][C]1.00295847369832[/C][C]0.997707371767825[/C][/ROW]
[ROW][C]28[/C][C]248.6[/C][C]249.083032284622[/C][C]248.077083333333[/C][C]1.0040549854012[/C][C]0.998060757972186[/C][/ROW]
[ROW][C]29[/C][C]248.68[/C][C]249.007531369321[/C][C]248.325[/C][C]1.00274854069997[/C][C]0.998684652759217[/C][/ROW]
[ROW][C]30[/C][C]248.75[/C][C]248.99687704358[/C][C]248.548333333333[/C][C]1.00180465386442[/C][C]0.999008513494182[/C][/ROW]
[ROW][C]31[/C][C]248.75[/C][C]248.596308344118[/C][C]248.771666666667[/C][C]0.999295103317439[/C][C]1.00061823788497[/C][/ROW]
[ROW][C]32[/C][C]249.03[/C][C]248.800335186083[/C][C]249.004583333333[/C][C]0.999179741414731[/C][C]1.0009230888445[/C][/ROW]
[ROW][C]33[/C][C]249.05[/C][C]249.002204945344[/C][C]249.384166666667[/C][C]0.998468380224663[/C][C]1.00019194631094[/C][/ROW]
[ROW][C]34[/C][C]249.57[/C][C]249.823409964605[/C][C]249.916666666667[/C][C]0.999626848808024[/C][C]0.998985643640677[/C][/ROW]
[ROW][C]35[/C][C]249.35[/C][C]250.200359856698[/C][C]250.524166666667[/C][C]0.998707482737984[/C][C]0.996601284437861[/C][/ROW]
[ROW][C]36[/C][C]249.46[/C][C]250.588400327689[/C][C]251.19[/C][C]0.997605001503597[/C][C]0.995496996963096[/C][/ROW]
[ROW][C]37[/C][C]249.46[/C][C]250.828848532147[/C][C]251.855[/C][C]0.995925625983787[/C][C]0.994542698975189[/C][/ROW]
[ROW][C]38[/C][C]250.82[/C][C]252.44117339398[/C][C]252.535833333333[/C][C]0.99962516234586[/C][C]0.993578015138401[/C][/ROW]
[ROW][C]39[/C][C]254.19[/C][C]253.997143967279[/C][C]253.247916666667[/C][C]1.00295847369832[/C][C]1.00075928425694[/C][/ROW]
[ROW][C]40[/C][C]255.18[/C][C]255.020762454538[/C][C]253.990833333333[/C][C]1.0040549854012[/C][C]1.00062441012226[/C][/ROW]
[ROW][C]41[/C][C]256.68[/C][C]255.460218228725[/C][C]254.76[/C][C]1.00274854069997[/C][C]1.00477484040268[/C][/ROW]
[ROW][C]42[/C][C]256.73[/C][C]256.004918015967[/C][C]255.54375[/C][C]1.00180465386442[/C][C]1.00283229708887[/C][/ROW]
[ROW][C]43[/C][C]256.73[/C][C]256.150562952238[/C][C]256.33125[/C][C]0.999295103317439[/C][C]1.00226209554679[/C][/ROW]
[ROW][C]44[/C][C]257.39[/C][C]256.954058200919[/C][C]257.165[/C][C]0.999179741414731[/C][C]1.00169657487464[/C][/ROW]
[ROW][C]45[/C][C]257.78[/C][C]257.552838536493[/C][C]257.947916666667[/C][C]0.998468380224663[/C][C]1.0008819994561[/C][/ROW]
[ROW][C]46[/C][C]258.67[/C][C]258.510583791934[/C][C]258.607083333333[/C][C]0.999626848808024[/C][C]1.00061667188139[/C][/ROW]
[ROW][C]47[/C][C]258.71[/C][C]258.861650500743[/C][C]259.196666666667[/C][C]0.998707482737984[/C][C]0.999414163896237[/C][/ROW]
[ROW][C]48[/C][C]258.91[/C][C]259.10212767802[/C][C]259.724166666667[/C][C]0.997605001503597[/C][C]0.999258486683447[/C][/ROW]
[ROW][C]49[/C][C]258.91[/C][C]259.172215463826[/C][C]260.2325[/C][C]0.995925625983787[/C][C]0.998988257813993[/C][/ROW]
[ROW][C]50[/C][C]261.38[/C][C]260.626437431656[/C][C]260.724166666667[/C][C]0.99962516234586[/C][C]1.00289135122196[/C][/ROW]
[ROW][C]51[/C][C]262.42[/C][C]261.976932323641[/C][C]261.204166666667[/C][C]1.00295847369832[/C][C]1.00169124690647[/C][/ROW]
[ROW][C]52[/C][C]262.77[/C][C]262.800096810178[/C][C]261.73875[/C][C]1.0040549854012[/C][C]0.999885476411375[/C][/ROW]
[ROW][C]53[/C][C]263.24[/C][C]263.058963107771[/C][C]262.337916666667[/C][C]1.00274854069997[/C][C]1.0006881989121[/C][/ROW]
[ROW][C]54[/C][C]262.83[/C][C]263.426620826679[/C][C]262.952083333333[/C][C]1.00180465386442[/C][C]0.997735153627196[/C][/ROW]
[ROW][C]55[/C][C]262.83[/C][C]263.38046302474[/C][C]263.56625[/C][C]0.999295103317439[/C][C]0.997910008136449[/C][/ROW]
[ROW][C]56[/C][C]263.09[/C][C]263.979957082634[/C][C]264.196666666667[/C][C]0.999179741414731[/C][C]0.996628694494577[/C][/ROW]
[ROW][C]57[/C][C]263.6[/C][C]264.470144268991[/C][C]264.875833333333[/C][C]0.998468380224663[/C][C]0.996709858228435[/C][/ROW]
[ROW][C]58[/C][C]265.68[/C][C]265.557536564844[/C][C]265.656666666667[/C][C]0.999626848808024[/C][C]1.00046115593909[/C][/ROW]
[ROW][C]59[/C][C]266.08[/C][C]266.149302227905[/C][C]266.49375[/C][C]0.998707482737984[/C][C]0.999739611461216[/C][/ROW]
[ROW][C]60[/C][C]266.28[/C][C]266.761240077064[/C][C]267.401666666667[/C][C]0.997605001503597[/C][C]0.998195989503853[/C][/ROW]
[ROW][C]61[/C][C]266.28[/C][C]267.299798509875[/C][C]268.393333333333[/C][C]0.995925625983787[/C][C]0.99618481377255[/C][/ROW]
[ROW][C]62[/C][C]269.14[/C][C]269.267363939167[/C][C]269.368333333333[/C][C]0.99962516234586[/C][C]0.999526998232152[/C][/ROW]
[ROW][C]63[/C][C]270.96[/C][C]271.128510496774[/C][C]270.32875[/C][C]1.00295847369832[/C][C]0.999378484776589[/C][/ROW]
[ROW][C]64[/C][C]272.97[/C][C]272.304732315732[/C][C]271.205[/C][C]1.0040549854012[/C][C]1.00244309997337[/C][/ROW]
[ROW][C]65[/C][C]273.13[/C][C]272.735068713634[/C][C]271.9875[/C][C]1.00274854069997[/C][C]1.00144803999071[/C][/ROW]
[ROW][C]66[/C][C]274.73[/C][C]273.247228364791[/C][C]272.755[/C][C]1.00180465386442[/C][C]1.00542648371617[/C][/ROW]
[ROW][C]67[/C][C]274.73[/C][C]NA[/C][C]NA[/C][C]0.999295103317439[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]274.59[/C][C]NA[/C][C]NA[/C][C]0.999179741414731[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]275.15[/C][C]NA[/C][C]NA[/C][C]0.998468380224663[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]275.16[/C][C]NA[/C][C]NA[/C][C]0.999626848808024[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]275.38[/C][C]NA[/C][C]NA[/C][C]0.998707482737984[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]275.4[/C][C]NA[/C][C]NA[/C][C]0.997605001503597[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197512&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	246.24	NA	NA	0.995925625983787	NA
2	247.57	NA	NA	0.99962516234586	NA
3	247.84	NA	NA	1.00295847369832	NA
4	248.27	NA	NA	1.0040549854012	NA
5	248.3	NA	NA	1.00274854069997	NA
6	248.31	NA	NA	1.00180465386442	NA
7	248.31	248.048777902092	248.22375	0.999295103317439	1.00105310778032
8	248.38	248.140460231857	248.344166666667	0.999179741414731	1.00096533942074
9	248.37	247.991671738858	248.372083333333	0.998468380224663	1.0015255684132
10	248.41	248.27440486014	248.367083333333	0.999626848808024	1.00054615029663
11	248.68	247.942864817592	248.26375	0.998707482737984	1.00297300421591
12	248.75	247.486264441763	248.080416666667	0.997605001503597	1.00510628564008
13	248.75	246.876268704023	247.88625	0.995925625983787	1.00758975865041
14	247.95	247.608402244522	247.70125	0.99962516234586	1.00137958870693
15	248.13	248.25980359836	247.5275	1.00295847369832	0.999477146132885
16	247.86	248.356765845181	247.35375	1.0040549854012	0.997999789361522
17	246.23	247.861473349679	247.182083333333	1.00274854069997	0.993417801776004
18	245.98	247.462028830138	247.01625	1.00180465386442	0.994011085914294
19	245.98	246.678078118708	246.852083333333	0.999295103317439	0.997170084492176
20	246.27	246.565919489344	246.768333333333	0.999179741414731	0.998799836206248
21	246.31	246.382889561222	246.760833333333	0.998468380224663	0.999704161432024
22	246.3	246.693744905462	246.785833333333	0.999626848808024	0.998403912082922
23	246.67	246.59960325331	246.91875	0.998707482737984	1.00028546982948
24	246.78	246.544359052843	247.13625	0.997605001503597	1.00095577505023
25	246.78	246.359217316534	247.367083333333	0.995925625983787	1.00170800462857
26	247.91	247.504691133929	247.5975	0.99962516234586	1.00163758054126
27	247.99	248.559855341742	247.826666666667	1.00295847369832	0.997707371767825
28	248.6	249.083032284622	248.077083333333	1.0040549854012	0.998060757972186
29	248.68	249.007531369321	248.325	1.00274854069997	0.998684652759217
30	248.75	248.99687704358	248.548333333333	1.00180465386442	0.999008513494182
31	248.75	248.596308344118	248.771666666667	0.999295103317439	1.00061823788497
32	249.03	248.800335186083	249.004583333333	0.999179741414731	1.0009230888445
33	249.05	249.002204945344	249.384166666667	0.998468380224663	1.00019194631094
34	249.57	249.823409964605	249.916666666667	0.999626848808024	0.998985643640677
35	249.35	250.200359856698	250.524166666667	0.998707482737984	0.996601284437861
36	249.46	250.588400327689	251.19	0.997605001503597	0.995496996963096
37	249.46	250.828848532147	251.855	0.995925625983787	0.994542698975189
38	250.82	252.44117339398	252.535833333333	0.99962516234586	0.993578015138401
39	254.19	253.997143967279	253.247916666667	1.00295847369832	1.00075928425694
40	255.18	255.020762454538	253.990833333333	1.0040549854012	1.00062441012226
41	256.68	255.460218228725	254.76	1.00274854069997	1.00477484040268
42	256.73	256.004918015967	255.54375	1.00180465386442	1.00283229708887
43	256.73	256.150562952238	256.33125	0.999295103317439	1.00226209554679
44	257.39	256.954058200919	257.165	0.999179741414731	1.00169657487464
45	257.78	257.552838536493	257.947916666667	0.998468380224663	1.0008819994561
46	258.67	258.510583791934	258.607083333333	0.999626848808024	1.00061667188139
47	258.71	258.861650500743	259.196666666667	0.998707482737984	0.999414163896237
48	258.91	259.10212767802	259.724166666667	0.997605001503597	0.999258486683447
49	258.91	259.172215463826	260.2325	0.995925625983787	0.998988257813993
50	261.38	260.626437431656	260.724166666667	0.99962516234586	1.00289135122196
51	262.42	261.976932323641	261.204166666667	1.00295847369832	1.00169124690647
52	262.77	262.800096810178	261.73875	1.0040549854012	0.999885476411375
53	263.24	263.058963107771	262.337916666667	1.00274854069997	1.0006881989121
54	262.83	263.426620826679	262.952083333333	1.00180465386442	0.997735153627196
55	262.83	263.38046302474	263.56625	0.999295103317439	0.997910008136449
56	263.09	263.979957082634	264.196666666667	0.999179741414731	0.996628694494577
57	263.6	264.470144268991	264.875833333333	0.998468380224663	0.996709858228435
58	265.68	265.557536564844	265.656666666667	0.999626848808024	1.00046115593909
59	266.08	266.149302227905	266.49375	0.998707482737984	0.999739611461216
60	266.28	266.761240077064	267.401666666667	0.997605001503597	0.998195989503853
61	266.28	267.299798509875	268.393333333333	0.995925625983787	0.99618481377255
62	269.14	269.267363939167	269.368333333333	0.99962516234586	0.999526998232152
63	270.96	271.128510496774	270.32875	1.00295847369832	0.999378484776589
64	272.97	272.304732315732	271.205	1.0040549854012	1.00244309997337
65	273.13	272.735068713634	271.9875	1.00274854069997	1.00144803999071
66	274.73	273.247228364791	272.755	1.00180465386442	1.00542648371617
67	274.73	NA	NA	0.999295103317439	NA
68	274.59	NA	NA	0.999179741414731	NA
69	275.15	NA	NA	0.998468380224663	NA
70	275.16	NA	NA	0.999626848808024	NA
71	275.38	NA	NA	0.998707482737984	NA
72	275.4	NA	NA	0.997605001503597	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