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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 16 Dec 2009 15:54:54 -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/16/t1261004128s2wc7p0lsydbbys.htm/, Retrieved Tue, 30 Apr 2024 15:12:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68625, Retrieved Tue, 30 Apr 2024 15:12:55 +0000

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No (this computation is public)

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Estimated Impact

149

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-    D    [Classical Decomposition] [Klassiek decompos...] [2009-12-01 19:46:49] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-    D      [Classical Decomposition] [Ad hoc forecasting] [2009-12-04 16:11:06] [34d27ebe78dc2d31581e8710befe8733]
-   PD          [Classical Decomposition] [Ad hoc forecasting] [2009-12-16 22:54:54] [371dc2189c569d90e2c1567f632c3ec0] [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	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=68625&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=68625&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68625&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	441	NA	NA	1.02722122831291	NA
2	449	NA	NA	1.03098213453975	NA
3	452	NA	NA	1.01238961586729	NA
4	462	NA	NA	0.99453947276264	NA
5	455	NA	NA	0.982206122008657	NA
6	461	NA	NA	0.996438253502204	NA
7	461	460.996653135373	457.375	1.00791834519896	1.00000726006275
8	463	461.568071596403	459.625	1.00422751503161	1.00310231251188
9	462	458.517910164968	461.375	0.993807445494377	1.00759422861754
10	456	458.434911569309	462.291666666667	0.99165731209224	0.994688642797788
11	455	453.300801766383	462.583333333333	0.979933277102612	1.00374850039311
12	456	453.04694914766	462.916666666667	0.978679278086754	1.00651820050416
13	472	475.988636669495	463.375	1.02722122831291	0.991620311154056
14	472	478.203880070689	463.833333333333	1.03098213453975	0.987026704865356
15	471	469.790964663081	464.041666666667	1.01238961586729	1.00257356021691
16	465	461.714950230055	464.25	0.99453947276264	1.00711488715778
17	459	456.43936994844	464.708333333333	0.982206122008657	1.00561001136219
18	465	463.551379181338	465.208333333333	0.996438253502204	1.00312504909644
19	468	469.269982885547	465.583333333333	1.00791834519896	0.997293705261653
20	467	467.886336378477	465.916666666667	1.00422751503161	0.998105658768885
21	463	463.197086887504	466.083333333333	0.993807445494377	0.999574507497815
22	460	461.699116888279	465.583333333333	0.99165731209224	0.996319861082406
23	462	455.097346107738	464.416666666667	0.979933277102612	1.01516742286304
24	461	452.924614237899	462.791666666667	0.978679278086754	1.01782942571070
25	476	473.3777827142	460.833333333333	1.02722122831291	1.0055393754873
26	476	472.834181453294	458.625	1.03098213453975	1.00669540966132
27	471	461.56529903416	455.916666666667	1.01238961586729	1.02044066351085
28	453	450.443502872079	452.916666666667	0.99453947276264	1.00567551116094
29	443	441.501651842892	449.5	0.982206122008657	1.00339375436276
30	442	443.705650632419	445.291666666667	0.996438253502204	0.996155896076627
31	444	444.61798002589	441.125	1.00791834519896	0.99861008764006
32	438	439.349537826329	437.5	1.00422751503161	0.99692832765227
33	427	430.856936265375	433.541666666667	0.993807445494377	0.991048220555978
34	424	426.040772707629	429.625	0.99165731209224	0.995209912200048
35	416	417.737389918201	426.291666666667	0.979933277102612	0.995840951851255
36	406	414.266782753472	423.291666666667	0.978679278086754	0.980044784912452
37	431	432.032128274605	420.583333333333	1.02722122831291	0.997610991852094
38	434	430.864617059738	417.916666666667	1.03098213453975	1.00727695618558
39	418	420.521336690874	415.375	1.01238961586729	0.994004259782121
40	412	410.786241395668	413.041666666667	0.99453947276264	1.00295472068443
41	404	403.318388849805	410.625	0.982206122008657	1.00169000761939
42	409	407.211099597900	408.666666666667	0.996438253502204	1.00439305412811
43	412	410.474746082275	407.25	1.00791834519896	1.00371582888419
44	406	407.339785784696	405.625	1.00422751503161	0.996710888964319
45	398	401.539616623291	404.041666666667	0.993807445494377	0.991184888173534
46	397	399.34866339048	402.708333333333	0.99165731209224	0.994118764864419
47	385	393.729024629187	401.791666666667	0.979933277102612	0.97782986754048
48	390	392.939730151832	401.5	0.978679278086754	0.99251862327412
49	413	412.728929359225	401.791666666667	1.02722122831291	1.00065677644937
50	413	415.313969863764	402.833333333333	1.03098213453975	0.994428384230555
51	401	409.849062823606	404.833333333333	1.01238961586729	0.978408971432943
52	397	405.233396006077	407.458333333333	0.99453947276264	0.979682335939673
53	397	403.15468782947	410.458333333333	0.982206122008657	0.98473368159848
54	409	412.400882168225	413.875	0.996438253502204	0.991753455641646
55	419	420.763912522848	417.458333333333	1.00791834519896	0.99580783315691
56	424	NA	NA	1.00422751503161	NA
57	428	NA	NA	0.993807445494377	NA
58	430	NA	NA	0.99165731209224	NA
59	424	NA	NA	0.979933277102612	NA
60	433	NA	NA	0.978679278086754	NA
61	456	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 441 & NA & NA & 1.02722122831291 & NA \tabularnewline
2 & 449 & NA & NA & 1.03098213453975 & NA \tabularnewline
3 & 452 & NA & NA & 1.01238961586729 & NA \tabularnewline
4 & 462 & NA & NA & 0.99453947276264 & NA \tabularnewline
5 & 455 & NA & NA & 0.982206122008657 & NA \tabularnewline
6 & 461 & NA & NA & 0.996438253502204 & NA \tabularnewline
7 & 461 & 460.996653135373 & 457.375 & 1.00791834519896 & 1.00000726006275 \tabularnewline
8 & 463 & 461.568071596403 & 459.625 & 1.00422751503161 & 1.00310231251188 \tabularnewline
9 & 462 & 458.517910164968 & 461.375 & 0.993807445494377 & 1.00759422861754 \tabularnewline
10 & 456 & 458.434911569309 & 462.291666666667 & 0.99165731209224 & 0.994688642797788 \tabularnewline
11 & 455 & 453.300801766383 & 462.583333333333 & 0.979933277102612 & 1.00374850039311 \tabularnewline
12 & 456 & 453.04694914766 & 462.916666666667 & 0.978679278086754 & 1.00651820050416 \tabularnewline
13 & 472 & 475.988636669495 & 463.375 & 1.02722122831291 & 0.991620311154056 \tabularnewline
14 & 472 & 478.203880070689 & 463.833333333333 & 1.03098213453975 & 0.987026704865356 \tabularnewline
15 & 471 & 469.790964663081 & 464.041666666667 & 1.01238961586729 & 1.00257356021691 \tabularnewline
16 & 465 & 461.714950230055 & 464.25 & 0.99453947276264 & 1.00711488715778 \tabularnewline
17 & 459 & 456.43936994844 & 464.708333333333 & 0.982206122008657 & 1.00561001136219 \tabularnewline
18 & 465 & 463.551379181338 & 465.208333333333 & 0.996438253502204 & 1.00312504909644 \tabularnewline
19 & 468 & 469.269982885547 & 465.583333333333 & 1.00791834519896 & 0.997293705261653 \tabularnewline
20 & 467 & 467.886336378477 & 465.916666666667 & 1.00422751503161 & 0.998105658768885 \tabularnewline
21 & 463 & 463.197086887504 & 466.083333333333 & 0.993807445494377 & 0.999574507497815 \tabularnewline
22 & 460 & 461.699116888279 & 465.583333333333 & 0.99165731209224 & 0.996319861082406 \tabularnewline
23 & 462 & 455.097346107738 & 464.416666666667 & 0.979933277102612 & 1.01516742286304 \tabularnewline
24 & 461 & 452.924614237899 & 462.791666666667 & 0.978679278086754 & 1.01782942571070 \tabularnewline
25 & 476 & 473.3777827142 & 460.833333333333 & 1.02722122831291 & 1.0055393754873 \tabularnewline
26 & 476 & 472.834181453294 & 458.625 & 1.03098213453975 & 1.00669540966132 \tabularnewline
27 & 471 & 461.56529903416 & 455.916666666667 & 1.01238961586729 & 1.02044066351085 \tabularnewline
28 & 453 & 450.443502872079 & 452.916666666667 & 0.99453947276264 & 1.00567551116094 \tabularnewline
29 & 443 & 441.501651842892 & 449.5 & 0.982206122008657 & 1.00339375436276 \tabularnewline
30 & 442 & 443.705650632419 & 445.291666666667 & 0.996438253502204 & 0.996155896076627 \tabularnewline
31 & 444 & 444.61798002589 & 441.125 & 1.00791834519896 & 0.99861008764006 \tabularnewline
32 & 438 & 439.349537826329 & 437.5 & 1.00422751503161 & 0.99692832765227 \tabularnewline
33 & 427 & 430.856936265375 & 433.541666666667 & 0.993807445494377 & 0.991048220555978 \tabularnewline
34 & 424 & 426.040772707629 & 429.625 & 0.99165731209224 & 0.995209912200048 \tabularnewline
35 & 416 & 417.737389918201 & 426.291666666667 & 0.979933277102612 & 0.995840951851255 \tabularnewline
36 & 406 & 414.266782753472 & 423.291666666667 & 0.978679278086754 & 0.980044784912452 \tabularnewline
37 & 431 & 432.032128274605 & 420.583333333333 & 1.02722122831291 & 0.997610991852094 \tabularnewline
38 & 434 & 430.864617059738 & 417.916666666667 & 1.03098213453975 & 1.00727695618558 \tabularnewline
39 & 418 & 420.521336690874 & 415.375 & 1.01238961586729 & 0.994004259782121 \tabularnewline
40 & 412 & 410.786241395668 & 413.041666666667 & 0.99453947276264 & 1.00295472068443 \tabularnewline
41 & 404 & 403.318388849805 & 410.625 & 0.982206122008657 & 1.00169000761939 \tabularnewline
42 & 409 & 407.211099597900 & 408.666666666667 & 0.996438253502204 & 1.00439305412811 \tabularnewline
43 & 412 & 410.474746082275 & 407.25 & 1.00791834519896 & 1.00371582888419 \tabularnewline
44 & 406 & 407.339785784696 & 405.625 & 1.00422751503161 & 0.996710888964319 \tabularnewline
45 & 398 & 401.539616623291 & 404.041666666667 & 0.993807445494377 & 0.991184888173534 \tabularnewline
46 & 397 & 399.34866339048 & 402.708333333333 & 0.99165731209224 & 0.994118764864419 \tabularnewline
47 & 385 & 393.729024629187 & 401.791666666667 & 0.979933277102612 & 0.97782986754048 \tabularnewline
48 & 390 & 392.939730151832 & 401.5 & 0.978679278086754 & 0.99251862327412 \tabularnewline
49 & 413 & 412.728929359225 & 401.791666666667 & 1.02722122831291 & 1.00065677644937 \tabularnewline
50 & 413 & 415.313969863764 & 402.833333333333 & 1.03098213453975 & 0.994428384230555 \tabularnewline
51 & 401 & 409.849062823606 & 404.833333333333 & 1.01238961586729 & 0.978408971432943 \tabularnewline
52 & 397 & 405.233396006077 & 407.458333333333 & 0.99453947276264 & 0.979682335939673 \tabularnewline
53 & 397 & 403.15468782947 & 410.458333333333 & 0.982206122008657 & 0.98473368159848 \tabularnewline
54 & 409 & 412.400882168225 & 413.875 & 0.996438253502204 & 0.991753455641646 \tabularnewline
55 & 419 & 420.763912522848 & 417.458333333333 & 1.00791834519896 & 0.99580783315691 \tabularnewline
56 & 424 & NA & NA & 1.00422751503161 & NA \tabularnewline
57 & 428 & NA & NA & 0.993807445494377 & NA \tabularnewline
58 & 430 & NA & NA & 0.99165731209224 & NA \tabularnewline
59 & 424 & NA & NA & 0.979933277102612 & NA \tabularnewline
60 & 433 & NA & NA & 0.978679278086754 & NA \tabularnewline
61 & 456 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68625&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]441[/C][C]NA[/C][C]NA[/C][C]1.02722122831291[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]449[/C][C]NA[/C][C]NA[/C][C]1.03098213453975[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]452[/C][C]NA[/C][C]NA[/C][C]1.01238961586729[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]462[/C][C]NA[/C][C]NA[/C][C]0.99453947276264[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]455[/C][C]NA[/C][C]NA[/C][C]0.982206122008657[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]461[/C][C]NA[/C][C]NA[/C][C]0.996438253502204[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]461[/C][C]460.996653135373[/C][C]457.375[/C][C]1.00791834519896[/C][C]1.00000726006275[/C][/ROW]
[ROW][C]8[/C][C]463[/C][C]461.568071596403[/C][C]459.625[/C][C]1.00422751503161[/C][C]1.00310231251188[/C][/ROW]
[ROW][C]9[/C][C]462[/C][C]458.517910164968[/C][C]461.375[/C][C]0.993807445494377[/C][C]1.00759422861754[/C][/ROW]
[ROW][C]10[/C][C]456[/C][C]458.434911569309[/C][C]462.291666666667[/C][C]0.99165731209224[/C][C]0.994688642797788[/C][/ROW]
[ROW][C]11[/C][C]455[/C][C]453.300801766383[/C][C]462.583333333333[/C][C]0.979933277102612[/C][C]1.00374850039311[/C][/ROW]
[ROW][C]12[/C][C]456[/C][C]453.04694914766[/C][C]462.916666666667[/C][C]0.978679278086754[/C][C]1.00651820050416[/C][/ROW]
[ROW][C]13[/C][C]472[/C][C]475.988636669495[/C][C]463.375[/C][C]1.02722122831291[/C][C]0.991620311154056[/C][/ROW]
[ROW][C]14[/C][C]472[/C][C]478.203880070689[/C][C]463.833333333333[/C][C]1.03098213453975[/C][C]0.987026704865356[/C][/ROW]
[ROW][C]15[/C][C]471[/C][C]469.790964663081[/C][C]464.041666666667[/C][C]1.01238961586729[/C][C]1.00257356021691[/C][/ROW]
[ROW][C]16[/C][C]465[/C][C]461.714950230055[/C][C]464.25[/C][C]0.99453947276264[/C][C]1.00711488715778[/C][/ROW]
[ROW][C]17[/C][C]459[/C][C]456.43936994844[/C][C]464.708333333333[/C][C]0.982206122008657[/C][C]1.00561001136219[/C][/ROW]
[ROW][C]18[/C][C]465[/C][C]463.551379181338[/C][C]465.208333333333[/C][C]0.996438253502204[/C][C]1.00312504909644[/C][/ROW]
[ROW][C]19[/C][C]468[/C][C]469.269982885547[/C][C]465.583333333333[/C][C]1.00791834519896[/C][C]0.997293705261653[/C][/ROW]
[ROW][C]20[/C][C]467[/C][C]467.886336378477[/C][C]465.916666666667[/C][C]1.00422751503161[/C][C]0.998105658768885[/C][/ROW]
[ROW][C]21[/C][C]463[/C][C]463.197086887504[/C][C]466.083333333333[/C][C]0.993807445494377[/C][C]0.999574507497815[/C][/ROW]
[ROW][C]22[/C][C]460[/C][C]461.699116888279[/C][C]465.583333333333[/C][C]0.99165731209224[/C][C]0.996319861082406[/C][/ROW]
[ROW][C]23[/C][C]462[/C][C]455.097346107738[/C][C]464.416666666667[/C][C]0.979933277102612[/C][C]1.01516742286304[/C][/ROW]
[ROW][C]24[/C][C]461[/C][C]452.924614237899[/C][C]462.791666666667[/C][C]0.978679278086754[/C][C]1.01782942571070[/C][/ROW]
[ROW][C]25[/C][C]476[/C][C]473.3777827142[/C][C]460.833333333333[/C][C]1.02722122831291[/C][C]1.0055393754873[/C][/ROW]
[ROW][C]26[/C][C]476[/C][C]472.834181453294[/C][C]458.625[/C][C]1.03098213453975[/C][C]1.00669540966132[/C][/ROW]
[ROW][C]27[/C][C]471[/C][C]461.56529903416[/C][C]455.916666666667[/C][C]1.01238961586729[/C][C]1.02044066351085[/C][/ROW]
[ROW][C]28[/C][C]453[/C][C]450.443502872079[/C][C]452.916666666667[/C][C]0.99453947276264[/C][C]1.00567551116094[/C][/ROW]
[ROW][C]29[/C][C]443[/C][C]441.501651842892[/C][C]449.5[/C][C]0.982206122008657[/C][C]1.00339375436276[/C][/ROW]
[ROW][C]30[/C][C]442[/C][C]443.705650632419[/C][C]445.291666666667[/C][C]0.996438253502204[/C][C]0.996155896076627[/C][/ROW]
[ROW][C]31[/C][C]444[/C][C]444.61798002589[/C][C]441.125[/C][C]1.00791834519896[/C][C]0.99861008764006[/C][/ROW]
[ROW][C]32[/C][C]438[/C][C]439.349537826329[/C][C]437.5[/C][C]1.00422751503161[/C][C]0.99692832765227[/C][/ROW]
[ROW][C]33[/C][C]427[/C][C]430.856936265375[/C][C]433.541666666667[/C][C]0.993807445494377[/C][C]0.991048220555978[/C][/ROW]
[ROW][C]34[/C][C]424[/C][C]426.040772707629[/C][C]429.625[/C][C]0.99165731209224[/C][C]0.995209912200048[/C][/ROW]
[ROW][C]35[/C][C]416[/C][C]417.737389918201[/C][C]426.291666666667[/C][C]0.979933277102612[/C][C]0.995840951851255[/C][/ROW]
[ROW][C]36[/C][C]406[/C][C]414.266782753472[/C][C]423.291666666667[/C][C]0.978679278086754[/C][C]0.980044784912452[/C][/ROW]
[ROW][C]37[/C][C]431[/C][C]432.032128274605[/C][C]420.583333333333[/C][C]1.02722122831291[/C][C]0.997610991852094[/C][/ROW]
[ROW][C]38[/C][C]434[/C][C]430.864617059738[/C][C]417.916666666667[/C][C]1.03098213453975[/C][C]1.00727695618558[/C][/ROW]
[ROW][C]39[/C][C]418[/C][C]420.521336690874[/C][C]415.375[/C][C]1.01238961586729[/C][C]0.994004259782121[/C][/ROW]
[ROW][C]40[/C][C]412[/C][C]410.786241395668[/C][C]413.041666666667[/C][C]0.99453947276264[/C][C]1.00295472068443[/C][/ROW]
[ROW][C]41[/C][C]404[/C][C]403.318388849805[/C][C]410.625[/C][C]0.982206122008657[/C][C]1.00169000761939[/C][/ROW]
[ROW][C]42[/C][C]409[/C][C]407.211099597900[/C][C]408.666666666667[/C][C]0.996438253502204[/C][C]1.00439305412811[/C][/ROW]
[ROW][C]43[/C][C]412[/C][C]410.474746082275[/C][C]407.25[/C][C]1.00791834519896[/C][C]1.00371582888419[/C][/ROW]
[ROW][C]44[/C][C]406[/C][C]407.339785784696[/C][C]405.625[/C][C]1.00422751503161[/C][C]0.996710888964319[/C][/ROW]
[ROW][C]45[/C][C]398[/C][C]401.539616623291[/C][C]404.041666666667[/C][C]0.993807445494377[/C][C]0.991184888173534[/C][/ROW]
[ROW][C]46[/C][C]397[/C][C]399.34866339048[/C][C]402.708333333333[/C][C]0.99165731209224[/C][C]0.994118764864419[/C][/ROW]
[ROW][C]47[/C][C]385[/C][C]393.729024629187[/C][C]401.791666666667[/C][C]0.979933277102612[/C][C]0.97782986754048[/C][/ROW]
[ROW][C]48[/C][C]390[/C][C]392.939730151832[/C][C]401.5[/C][C]0.978679278086754[/C][C]0.99251862327412[/C][/ROW]
[ROW][C]49[/C][C]413[/C][C]412.728929359225[/C][C]401.791666666667[/C][C]1.02722122831291[/C][C]1.00065677644937[/C][/ROW]
[ROW][C]50[/C][C]413[/C][C]415.313969863764[/C][C]402.833333333333[/C][C]1.03098213453975[/C][C]0.994428384230555[/C][/ROW]
[ROW][C]51[/C][C]401[/C][C]409.849062823606[/C][C]404.833333333333[/C][C]1.01238961586729[/C][C]0.978408971432943[/C][/ROW]
[ROW][C]52[/C][C]397[/C][C]405.233396006077[/C][C]407.458333333333[/C][C]0.99453947276264[/C][C]0.979682335939673[/C][/ROW]
[ROW][C]53[/C][C]397[/C][C]403.15468782947[/C][C]410.458333333333[/C][C]0.982206122008657[/C][C]0.98473368159848[/C][/ROW]
[ROW][C]54[/C][C]409[/C][C]412.400882168225[/C][C]413.875[/C][C]0.996438253502204[/C][C]0.991753455641646[/C][/ROW]
[ROW][C]55[/C][C]419[/C][C]420.763912522848[/C][C]417.458333333333[/C][C]1.00791834519896[/C][C]0.99580783315691[/C][/ROW]
[ROW][C]56[/C][C]424[/C][C]NA[/C][C]NA[/C][C]1.00422751503161[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]428[/C][C]NA[/C][C]NA[/C][C]0.993807445494377[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]430[/C][C]NA[/C][C]NA[/C][C]0.99165731209224[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]424[/C][C]NA[/C][C]NA[/C][C]0.979933277102612[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]433[/C][C]NA[/C][C]NA[/C][C]0.978679278086754[/C][C]NA[/C][/ROW]
[ROW][C]61[/C][C]456[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68625&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68625&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	441	NA	NA	1.02722122831291	NA
2	449	NA	NA	1.03098213453975	NA
3	452	NA	NA	1.01238961586729	NA
4	462	NA	NA	0.99453947276264	NA
5	455	NA	NA	0.982206122008657	NA
6	461	NA	NA	0.996438253502204	NA
7	461	460.996653135373	457.375	1.00791834519896	1.00000726006275
8	463	461.568071596403	459.625	1.00422751503161	1.00310231251188
9	462	458.517910164968	461.375	0.993807445494377	1.00759422861754
10	456	458.434911569309	462.291666666667	0.99165731209224	0.994688642797788
11	455	453.300801766383	462.583333333333	0.979933277102612	1.00374850039311
12	456	453.04694914766	462.916666666667	0.978679278086754	1.00651820050416
13	472	475.988636669495	463.375	1.02722122831291	0.991620311154056
14	472	478.203880070689	463.833333333333	1.03098213453975	0.987026704865356
15	471	469.790964663081	464.041666666667	1.01238961586729	1.00257356021691
16	465	461.714950230055	464.25	0.99453947276264	1.00711488715778
17	459	456.43936994844	464.708333333333	0.982206122008657	1.00561001136219
18	465	463.551379181338	465.208333333333	0.996438253502204	1.00312504909644
19	468	469.269982885547	465.583333333333	1.00791834519896	0.997293705261653
20	467	467.886336378477	465.916666666667	1.00422751503161	0.998105658768885
21	463	463.197086887504	466.083333333333	0.993807445494377	0.999574507497815
22	460	461.699116888279	465.583333333333	0.99165731209224	0.996319861082406
23	462	455.097346107738	464.416666666667	0.979933277102612	1.01516742286304
24	461	452.924614237899	462.791666666667	0.978679278086754	1.01782942571070
25	476	473.3777827142	460.833333333333	1.02722122831291	1.0055393754873
26	476	472.834181453294	458.625	1.03098213453975	1.00669540966132
27	471	461.56529903416	455.916666666667	1.01238961586729	1.02044066351085
28	453	450.443502872079	452.916666666667	0.99453947276264	1.00567551116094
29	443	441.501651842892	449.5	0.982206122008657	1.00339375436276
30	442	443.705650632419	445.291666666667	0.996438253502204	0.996155896076627
31	444	444.61798002589	441.125	1.00791834519896	0.99861008764006
32	438	439.349537826329	437.5	1.00422751503161	0.99692832765227
33	427	430.856936265375	433.541666666667	0.993807445494377	0.991048220555978
34	424	426.040772707629	429.625	0.99165731209224	0.995209912200048
35	416	417.737389918201	426.291666666667	0.979933277102612	0.995840951851255
36	406	414.266782753472	423.291666666667	0.978679278086754	0.980044784912452
37	431	432.032128274605	420.583333333333	1.02722122831291	0.997610991852094
38	434	430.864617059738	417.916666666667	1.03098213453975	1.00727695618558
39	418	420.521336690874	415.375	1.01238961586729	0.994004259782121
40	412	410.786241395668	413.041666666667	0.99453947276264	1.00295472068443
41	404	403.318388849805	410.625	0.982206122008657	1.00169000761939
42	409	407.211099597900	408.666666666667	0.996438253502204	1.00439305412811
43	412	410.474746082275	407.25	1.00791834519896	1.00371582888419
44	406	407.339785784696	405.625	1.00422751503161	0.996710888964319
45	398	401.539616623291	404.041666666667	0.993807445494377	0.991184888173534
46	397	399.34866339048	402.708333333333	0.99165731209224	0.994118764864419
47	385	393.729024629187	401.791666666667	0.979933277102612	0.97782986754048
48	390	392.939730151832	401.5	0.978679278086754	0.99251862327412
49	413	412.728929359225	401.791666666667	1.02722122831291	1.00065677644937
50	413	415.313969863764	402.833333333333	1.03098213453975	0.994428384230555
51	401	409.849062823606	404.833333333333	1.01238961586729	0.978408971432943
52	397	405.233396006077	407.458333333333	0.99453947276264	0.979682335939673
53	397	403.15468782947	410.458333333333	0.982206122008657	0.98473368159848
54	409	412.400882168225	413.875	0.996438253502204	0.991753455641646
55	419	420.763912522848	417.458333333333	1.00791834519896	0.99580783315691
56	424	NA	NA	1.00422751503161	NA
57	428	NA	NA	0.993807445494377	NA
58	430	NA	NA	0.99165731209224	NA
59	424	NA	NA	0.979933277102612	NA
60	433	NA	NA	0.978679278086754	NA
61	456	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 = 1 ; par2 = 2 ; par3 = 1 ; par4 = 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