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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 04 Dec 2009 09:11:06 -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/t12599431349ag01q36s7b6xgl.htm/, Retrieved Sat, 27 Apr 2024 15:57:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63831, Retrieved Sat, 27 Apr 2024 15:57:47 +0000

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Original text written by user:

Techniek 1: Klassieke decompositie van de tijdreeks met moving averages

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No (this computation is public)

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Estimated Impact

132

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] [371dc2189c569d90e2c1567f632c3ec0] [Current]
-   PD          [Classical Decomposition] [Ad hoc forecasting] [2009-12-16 22:54:54] [34d27ebe78dc2d31581e8710befe8733] 

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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=63831&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=63831&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63831&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	462	NA	NA	0.995153115548232	NA
2	455	NA	NA	0.98281215496888	NA
3	461	NA	NA	0.997053067858292	NA
4	461	NA	NA	1.00854024290934	NA
5	463	NA	NA	1.00454702802969	NA
6	462	NA	NA	0.994374210406462	NA
7	456	458.921048847984	462.291666666667	0.992708893407086	0.993634964324873
8	455	453.580493799053	462.583333333333	0.980537907690261	1.00312955742223
9	456	453.326484550219	462.916666666667	0.979283134941967	1.00589754964887
10	472	472.388348902558	463.375	1.01945152177514	0.99917790330041
11	472	478.615859396863	463.833333333333	1.03187034005792	0.986177099511077
12	471	470.384365619323	464.041666666667	1.01366838240673	1.00130879005697
13	465	461.999833893267	464.25	0.995153115548232	1.00649386836669
14	459	456.720998515330	464.708333333333	0.98281215496888	1.00498992052496
15	465	463.837395943243	465.208333333333	0.997053067858292	1.00250649056528
16	468	469.559528094541	465.583333333333	1.00854024290934	0.996678742520955
17	467	468.0352028095	465.916666666667	1.00454702802969	0.997788194556123
18	463	463.461246566945	466.083333333333	0.994374210406462	0.99900477856485
19	460	462.188715622116	465.583333333333	0.992708893407086	0.995264454652101
20	462	455.378146629819	464.416666666667	0.980537907690261	1.01454143862456
21	461	453.204074158351	462.791666666667	0.979283134941967	1.01720179999733
22	476	469.797242951379	460.833333333333	1.01945152177514	1.01320305119216
23	476	473.241534709061	458.625	1.03187034005792	1.00582887402864
24	471	462.148310012268	455.916666666667	1.01366838240673	1.01915335357928
25	453	450.721431917054	452.916666666667	0.995153115548232	1.00505537993446
26	443	441.774063658511	449.5	0.98281215496888	1.00277503013947
27	442	443.979422341732	445.291666666667	0.997053067858292	0.995541634944945
28	444	444.892314653383	441.125	1.00854024290934	0.997994313176486
29	438	439.489324762989	437.5	1.00454702802969	0.996611237909379
30	427	431.102652469968	433.541666666667	0.994374210406462	0.990483351363156
31	424	426.492558330019	429.625	0.992708893407086	0.994155681543943
32	416	417.995138899127	426.291666666667	0.980537907690261	0.995226884924112
33	406	414.522390328143	423.291666666667	0.979283134941967	0.979440458399854
34	431	428.764319199929	420.583333333333	1.01945152177514	1.00521424171732
35	434	431.235812949204	417.916666666667	1.03187034005792	1.00640991997370
36	418	421.052504342195	415.375	1.01366838240673	0.992750299996519
37	412	411.039701434568	413.041666666667	0.995153115548232	1.00233626718315
38	404	403.567241134096	410.625	0.98281215496888	1.00107233398005
39	409	407.462353731422	408.666666666667	0.997053067858292	1.00377371370507
40	412	410.728013924829	407.25	1.00854024290934	1.0030969060596
41	406	407.469388244543	405.625	1.00454702802969	0.996393868381442
42	398	401.768613262978	404.041666666667	0.994374210406462	0.990619941084072
43	397	399.772143949145	402.708333333333	0.992708893407086	0.993065690065945
44	385	393.971960160716	401.791666666667	0.980537907690261	0.977226906815764
45	390	393.182178679200	401.5	0.979283134941967	0.991906604999521
46	413	409.607126019905	401.791666666667	1.01945152177514	1.00828323963273
47	413	415.67176865333	402.833333333333	1.03187034005792	0.9935724077149
48	401	410.366750144324	404.833333333333	1.01366838240673	0.97717468547091
49	397	405.483429872757	407.458333333333	0.995153115548232	0.97907823292454
50	397	403.403439108268	410.458333333333	0.98281215496888	0.984126463764357
51	409	412.655338459850	413.875	0.997053067858292	0.991141909193534
52	419	421.023528904529	417.458333333333	1.00854024290934	0.995193786651797
53	424	423.081723305171	421.166666666667	1.00454702802969	1.00217044756189
54	428	422.567607163979	424.958333333333	0.994374210406462	1.01285567739676
55	430	425.541212307171	428.666666666667	0.992708893407086	1.01047792214685
56	424	NA	NA	0.980537907690261	NA
57	433	NA	NA	0.979283134941967	NA
58	456	NA	NA	1.01945152177514	NA
59	459	NA	NA	1.03187034005792	NA
60	446	NA	NA	1.01366838240673	NA
61	441	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 462 & NA & NA & 0.995153115548232 & NA \tabularnewline
2 & 455 & NA & NA & 0.98281215496888 & NA \tabularnewline
3 & 461 & NA & NA & 0.997053067858292 & NA \tabularnewline
4 & 461 & NA & NA & 1.00854024290934 & NA \tabularnewline
5 & 463 & NA & NA & 1.00454702802969 & NA \tabularnewline
6 & 462 & NA & NA & 0.994374210406462 & NA \tabularnewline
7 & 456 & 458.921048847984 & 462.291666666667 & 0.992708893407086 & 0.993634964324873 \tabularnewline
8 & 455 & 453.580493799053 & 462.583333333333 & 0.980537907690261 & 1.00312955742223 \tabularnewline
9 & 456 & 453.326484550219 & 462.916666666667 & 0.979283134941967 & 1.00589754964887 \tabularnewline
10 & 472 & 472.388348902558 & 463.375 & 1.01945152177514 & 0.99917790330041 \tabularnewline
11 & 472 & 478.615859396863 & 463.833333333333 & 1.03187034005792 & 0.986177099511077 \tabularnewline
12 & 471 & 470.384365619323 & 464.041666666667 & 1.01366838240673 & 1.00130879005697 \tabularnewline
13 & 465 & 461.999833893267 & 464.25 & 0.995153115548232 & 1.00649386836669 \tabularnewline
14 & 459 & 456.720998515330 & 464.708333333333 & 0.98281215496888 & 1.00498992052496 \tabularnewline
15 & 465 & 463.837395943243 & 465.208333333333 & 0.997053067858292 & 1.00250649056528 \tabularnewline
16 & 468 & 469.559528094541 & 465.583333333333 & 1.00854024290934 & 0.996678742520955 \tabularnewline
17 & 467 & 468.0352028095 & 465.916666666667 & 1.00454702802969 & 0.997788194556123 \tabularnewline
18 & 463 & 463.461246566945 & 466.083333333333 & 0.994374210406462 & 0.99900477856485 \tabularnewline
19 & 460 & 462.188715622116 & 465.583333333333 & 0.992708893407086 & 0.995264454652101 \tabularnewline
20 & 462 & 455.378146629819 & 464.416666666667 & 0.980537907690261 & 1.01454143862456 \tabularnewline
21 & 461 & 453.204074158351 & 462.791666666667 & 0.979283134941967 & 1.01720179999733 \tabularnewline
22 & 476 & 469.797242951379 & 460.833333333333 & 1.01945152177514 & 1.01320305119216 \tabularnewline
23 & 476 & 473.241534709061 & 458.625 & 1.03187034005792 & 1.00582887402864 \tabularnewline
24 & 471 & 462.148310012268 & 455.916666666667 & 1.01366838240673 & 1.01915335357928 \tabularnewline
25 & 453 & 450.721431917054 & 452.916666666667 & 0.995153115548232 & 1.00505537993446 \tabularnewline
26 & 443 & 441.774063658511 & 449.5 & 0.98281215496888 & 1.00277503013947 \tabularnewline
27 & 442 & 443.979422341732 & 445.291666666667 & 0.997053067858292 & 0.995541634944945 \tabularnewline
28 & 444 & 444.892314653383 & 441.125 & 1.00854024290934 & 0.997994313176486 \tabularnewline
29 & 438 & 439.489324762989 & 437.5 & 1.00454702802969 & 0.996611237909379 \tabularnewline
30 & 427 & 431.102652469968 & 433.541666666667 & 0.994374210406462 & 0.990483351363156 \tabularnewline
31 & 424 & 426.492558330019 & 429.625 & 0.992708893407086 & 0.994155681543943 \tabularnewline
32 & 416 & 417.995138899127 & 426.291666666667 & 0.980537907690261 & 0.995226884924112 \tabularnewline
33 & 406 & 414.522390328143 & 423.291666666667 & 0.979283134941967 & 0.979440458399854 \tabularnewline
34 & 431 & 428.764319199929 & 420.583333333333 & 1.01945152177514 & 1.00521424171732 \tabularnewline
35 & 434 & 431.235812949204 & 417.916666666667 & 1.03187034005792 & 1.00640991997370 \tabularnewline
36 & 418 & 421.052504342195 & 415.375 & 1.01366838240673 & 0.992750299996519 \tabularnewline
37 & 412 & 411.039701434568 & 413.041666666667 & 0.995153115548232 & 1.00233626718315 \tabularnewline
38 & 404 & 403.567241134096 & 410.625 & 0.98281215496888 & 1.00107233398005 \tabularnewline
39 & 409 & 407.462353731422 & 408.666666666667 & 0.997053067858292 & 1.00377371370507 \tabularnewline
40 & 412 & 410.728013924829 & 407.25 & 1.00854024290934 & 1.0030969060596 \tabularnewline
41 & 406 & 407.469388244543 & 405.625 & 1.00454702802969 & 0.996393868381442 \tabularnewline
42 & 398 & 401.768613262978 & 404.041666666667 & 0.994374210406462 & 0.990619941084072 \tabularnewline
43 & 397 & 399.772143949145 & 402.708333333333 & 0.992708893407086 & 0.993065690065945 \tabularnewline
44 & 385 & 393.971960160716 & 401.791666666667 & 0.980537907690261 & 0.977226906815764 \tabularnewline
45 & 390 & 393.182178679200 & 401.5 & 0.979283134941967 & 0.991906604999521 \tabularnewline
46 & 413 & 409.607126019905 & 401.791666666667 & 1.01945152177514 & 1.00828323963273 \tabularnewline
47 & 413 & 415.67176865333 & 402.833333333333 & 1.03187034005792 & 0.9935724077149 \tabularnewline
48 & 401 & 410.366750144324 & 404.833333333333 & 1.01366838240673 & 0.97717468547091 \tabularnewline
49 & 397 & 405.483429872757 & 407.458333333333 & 0.995153115548232 & 0.97907823292454 \tabularnewline
50 & 397 & 403.403439108268 & 410.458333333333 & 0.98281215496888 & 0.984126463764357 \tabularnewline
51 & 409 & 412.655338459850 & 413.875 & 0.997053067858292 & 0.991141909193534 \tabularnewline
52 & 419 & 421.023528904529 & 417.458333333333 & 1.00854024290934 & 0.995193786651797 \tabularnewline
53 & 424 & 423.081723305171 & 421.166666666667 & 1.00454702802969 & 1.00217044756189 \tabularnewline
54 & 428 & 422.567607163979 & 424.958333333333 & 0.994374210406462 & 1.01285567739676 \tabularnewline
55 & 430 & 425.541212307171 & 428.666666666667 & 0.992708893407086 & 1.01047792214685 \tabularnewline
56 & 424 & NA & NA & 0.980537907690261 & NA \tabularnewline
57 & 433 & NA & NA & 0.979283134941967 & NA \tabularnewline
58 & 456 & NA & NA & 1.01945152177514 & NA \tabularnewline
59 & 459 & NA & NA & 1.03187034005792 & NA \tabularnewline
60 & 446 & NA & NA & 1.01366838240673 & NA \tabularnewline
61 & 441 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63831&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]462[/C][C]NA[/C][C]NA[/C][C]0.995153115548232[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]455[/C][C]NA[/C][C]NA[/C][C]0.98281215496888[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]461[/C][C]NA[/C][C]NA[/C][C]0.997053067858292[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]461[/C][C]NA[/C][C]NA[/C][C]1.00854024290934[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]463[/C][C]NA[/C][C]NA[/C][C]1.00454702802969[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]462[/C][C]NA[/C][C]NA[/C][C]0.994374210406462[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]456[/C][C]458.921048847984[/C][C]462.291666666667[/C][C]0.992708893407086[/C][C]0.993634964324873[/C][/ROW]
[ROW][C]8[/C][C]455[/C][C]453.580493799053[/C][C]462.583333333333[/C][C]0.980537907690261[/C][C]1.00312955742223[/C][/ROW]
[ROW][C]9[/C][C]456[/C][C]453.326484550219[/C][C]462.916666666667[/C][C]0.979283134941967[/C][C]1.00589754964887[/C][/ROW]
[ROW][C]10[/C][C]472[/C][C]472.388348902558[/C][C]463.375[/C][C]1.01945152177514[/C][C]0.99917790330041[/C][/ROW]
[ROW][C]11[/C][C]472[/C][C]478.615859396863[/C][C]463.833333333333[/C][C]1.03187034005792[/C][C]0.986177099511077[/C][/ROW]
[ROW][C]12[/C][C]471[/C][C]470.384365619323[/C][C]464.041666666667[/C][C]1.01366838240673[/C][C]1.00130879005697[/C][/ROW]
[ROW][C]13[/C][C]465[/C][C]461.999833893267[/C][C]464.25[/C][C]0.995153115548232[/C][C]1.00649386836669[/C][/ROW]
[ROW][C]14[/C][C]459[/C][C]456.720998515330[/C][C]464.708333333333[/C][C]0.98281215496888[/C][C]1.00498992052496[/C][/ROW]
[ROW][C]15[/C][C]465[/C][C]463.837395943243[/C][C]465.208333333333[/C][C]0.997053067858292[/C][C]1.00250649056528[/C][/ROW]
[ROW][C]16[/C][C]468[/C][C]469.559528094541[/C][C]465.583333333333[/C][C]1.00854024290934[/C][C]0.996678742520955[/C][/ROW]
[ROW][C]17[/C][C]467[/C][C]468.0352028095[/C][C]465.916666666667[/C][C]1.00454702802969[/C][C]0.997788194556123[/C][/ROW]
[ROW][C]18[/C][C]463[/C][C]463.461246566945[/C][C]466.083333333333[/C][C]0.994374210406462[/C][C]0.99900477856485[/C][/ROW]
[ROW][C]19[/C][C]460[/C][C]462.188715622116[/C][C]465.583333333333[/C][C]0.992708893407086[/C][C]0.995264454652101[/C][/ROW]
[ROW][C]20[/C][C]462[/C][C]455.378146629819[/C][C]464.416666666667[/C][C]0.980537907690261[/C][C]1.01454143862456[/C][/ROW]
[ROW][C]21[/C][C]461[/C][C]453.204074158351[/C][C]462.791666666667[/C][C]0.979283134941967[/C][C]1.01720179999733[/C][/ROW]
[ROW][C]22[/C][C]476[/C][C]469.797242951379[/C][C]460.833333333333[/C][C]1.01945152177514[/C][C]1.01320305119216[/C][/ROW]
[ROW][C]23[/C][C]476[/C][C]473.241534709061[/C][C]458.625[/C][C]1.03187034005792[/C][C]1.00582887402864[/C][/ROW]
[ROW][C]24[/C][C]471[/C][C]462.148310012268[/C][C]455.916666666667[/C][C]1.01366838240673[/C][C]1.01915335357928[/C][/ROW]
[ROW][C]25[/C][C]453[/C][C]450.721431917054[/C][C]452.916666666667[/C][C]0.995153115548232[/C][C]1.00505537993446[/C][/ROW]
[ROW][C]26[/C][C]443[/C][C]441.774063658511[/C][C]449.5[/C][C]0.98281215496888[/C][C]1.00277503013947[/C][/ROW]
[ROW][C]27[/C][C]442[/C][C]443.979422341732[/C][C]445.291666666667[/C][C]0.997053067858292[/C][C]0.995541634944945[/C][/ROW]
[ROW][C]28[/C][C]444[/C][C]444.892314653383[/C][C]441.125[/C][C]1.00854024290934[/C][C]0.997994313176486[/C][/ROW]
[ROW][C]29[/C][C]438[/C][C]439.489324762989[/C][C]437.5[/C][C]1.00454702802969[/C][C]0.996611237909379[/C][/ROW]
[ROW][C]30[/C][C]427[/C][C]431.102652469968[/C][C]433.541666666667[/C][C]0.994374210406462[/C][C]0.990483351363156[/C][/ROW]
[ROW][C]31[/C][C]424[/C][C]426.492558330019[/C][C]429.625[/C][C]0.992708893407086[/C][C]0.994155681543943[/C][/ROW]
[ROW][C]32[/C][C]416[/C][C]417.995138899127[/C][C]426.291666666667[/C][C]0.980537907690261[/C][C]0.995226884924112[/C][/ROW]
[ROW][C]33[/C][C]406[/C][C]414.522390328143[/C][C]423.291666666667[/C][C]0.979283134941967[/C][C]0.979440458399854[/C][/ROW]
[ROW][C]34[/C][C]431[/C][C]428.764319199929[/C][C]420.583333333333[/C][C]1.01945152177514[/C][C]1.00521424171732[/C][/ROW]
[ROW][C]35[/C][C]434[/C][C]431.235812949204[/C][C]417.916666666667[/C][C]1.03187034005792[/C][C]1.00640991997370[/C][/ROW]
[ROW][C]36[/C][C]418[/C][C]421.052504342195[/C][C]415.375[/C][C]1.01366838240673[/C][C]0.992750299996519[/C][/ROW]
[ROW][C]37[/C][C]412[/C][C]411.039701434568[/C][C]413.041666666667[/C][C]0.995153115548232[/C][C]1.00233626718315[/C][/ROW]
[ROW][C]38[/C][C]404[/C][C]403.567241134096[/C][C]410.625[/C][C]0.98281215496888[/C][C]1.00107233398005[/C][/ROW]
[ROW][C]39[/C][C]409[/C][C]407.462353731422[/C][C]408.666666666667[/C][C]0.997053067858292[/C][C]1.00377371370507[/C][/ROW]
[ROW][C]40[/C][C]412[/C][C]410.728013924829[/C][C]407.25[/C][C]1.00854024290934[/C][C]1.0030969060596[/C][/ROW]
[ROW][C]41[/C][C]406[/C][C]407.469388244543[/C][C]405.625[/C][C]1.00454702802969[/C][C]0.996393868381442[/C][/ROW]
[ROW][C]42[/C][C]398[/C][C]401.768613262978[/C][C]404.041666666667[/C][C]0.994374210406462[/C][C]0.990619941084072[/C][/ROW]
[ROW][C]43[/C][C]397[/C][C]399.772143949145[/C][C]402.708333333333[/C][C]0.992708893407086[/C][C]0.993065690065945[/C][/ROW]
[ROW][C]44[/C][C]385[/C][C]393.971960160716[/C][C]401.791666666667[/C][C]0.980537907690261[/C][C]0.977226906815764[/C][/ROW]
[ROW][C]45[/C][C]390[/C][C]393.182178679200[/C][C]401.5[/C][C]0.979283134941967[/C][C]0.991906604999521[/C][/ROW]
[ROW][C]46[/C][C]413[/C][C]409.607126019905[/C][C]401.791666666667[/C][C]1.01945152177514[/C][C]1.00828323963273[/C][/ROW]
[ROW][C]47[/C][C]413[/C][C]415.67176865333[/C][C]402.833333333333[/C][C]1.03187034005792[/C][C]0.9935724077149[/C][/ROW]
[ROW][C]48[/C][C]401[/C][C]410.366750144324[/C][C]404.833333333333[/C][C]1.01366838240673[/C][C]0.97717468547091[/C][/ROW]
[ROW][C]49[/C][C]397[/C][C]405.483429872757[/C][C]407.458333333333[/C][C]0.995153115548232[/C][C]0.97907823292454[/C][/ROW]
[ROW][C]50[/C][C]397[/C][C]403.403439108268[/C][C]410.458333333333[/C][C]0.98281215496888[/C][C]0.984126463764357[/C][/ROW]
[ROW][C]51[/C][C]409[/C][C]412.655338459850[/C][C]413.875[/C][C]0.997053067858292[/C][C]0.991141909193534[/C][/ROW]
[ROW][C]52[/C][C]419[/C][C]421.023528904529[/C][C]417.458333333333[/C][C]1.00854024290934[/C][C]0.995193786651797[/C][/ROW]
[ROW][C]53[/C][C]424[/C][C]423.081723305171[/C][C]421.166666666667[/C][C]1.00454702802969[/C][C]1.00217044756189[/C][/ROW]
[ROW][C]54[/C][C]428[/C][C]422.567607163979[/C][C]424.958333333333[/C][C]0.994374210406462[/C][C]1.01285567739676[/C][/ROW]
[ROW][C]55[/C][C]430[/C][C]425.541212307171[/C][C]428.666666666667[/C][C]0.992708893407086[/C][C]1.01047792214685[/C][/ROW]
[ROW][C]56[/C][C]424[/C][C]NA[/C][C]NA[/C][C]0.980537907690261[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]433[/C][C]NA[/C][C]NA[/C][C]0.979283134941967[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]456[/C][C]NA[/C][C]NA[/C][C]1.01945152177514[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]459[/C][C]NA[/C][C]NA[/C][C]1.03187034005792[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]446[/C][C]NA[/C][C]NA[/C][C]1.01366838240673[/C][C]NA[/C][/ROW]
[ROW][C]61[/C][C]441[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63831&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63831&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	462	NA	NA	0.995153115548232	NA
2	455	NA	NA	0.98281215496888	NA
3	461	NA	NA	0.997053067858292	NA
4	461	NA	NA	1.00854024290934	NA
5	463	NA	NA	1.00454702802969	NA
6	462	NA	NA	0.994374210406462	NA
7	456	458.921048847984	462.291666666667	0.992708893407086	0.993634964324873
8	455	453.580493799053	462.583333333333	0.980537907690261	1.00312955742223
9	456	453.326484550219	462.916666666667	0.979283134941967	1.00589754964887
10	472	472.388348902558	463.375	1.01945152177514	0.99917790330041
11	472	478.615859396863	463.833333333333	1.03187034005792	0.986177099511077
12	471	470.384365619323	464.041666666667	1.01366838240673	1.00130879005697
13	465	461.999833893267	464.25	0.995153115548232	1.00649386836669
14	459	456.720998515330	464.708333333333	0.98281215496888	1.00498992052496
15	465	463.837395943243	465.208333333333	0.997053067858292	1.00250649056528
16	468	469.559528094541	465.583333333333	1.00854024290934	0.996678742520955
17	467	468.0352028095	465.916666666667	1.00454702802969	0.997788194556123
18	463	463.461246566945	466.083333333333	0.994374210406462	0.99900477856485
19	460	462.188715622116	465.583333333333	0.992708893407086	0.995264454652101
20	462	455.378146629819	464.416666666667	0.980537907690261	1.01454143862456
21	461	453.204074158351	462.791666666667	0.979283134941967	1.01720179999733
22	476	469.797242951379	460.833333333333	1.01945152177514	1.01320305119216
23	476	473.241534709061	458.625	1.03187034005792	1.00582887402864
24	471	462.148310012268	455.916666666667	1.01366838240673	1.01915335357928
25	453	450.721431917054	452.916666666667	0.995153115548232	1.00505537993446
26	443	441.774063658511	449.5	0.98281215496888	1.00277503013947
27	442	443.979422341732	445.291666666667	0.997053067858292	0.995541634944945
28	444	444.892314653383	441.125	1.00854024290934	0.997994313176486
29	438	439.489324762989	437.5	1.00454702802969	0.996611237909379
30	427	431.102652469968	433.541666666667	0.994374210406462	0.990483351363156
31	424	426.492558330019	429.625	0.992708893407086	0.994155681543943
32	416	417.995138899127	426.291666666667	0.980537907690261	0.995226884924112
33	406	414.522390328143	423.291666666667	0.979283134941967	0.979440458399854
34	431	428.764319199929	420.583333333333	1.01945152177514	1.00521424171732
35	434	431.235812949204	417.916666666667	1.03187034005792	1.00640991997370
36	418	421.052504342195	415.375	1.01366838240673	0.992750299996519
37	412	411.039701434568	413.041666666667	0.995153115548232	1.00233626718315
38	404	403.567241134096	410.625	0.98281215496888	1.00107233398005
39	409	407.462353731422	408.666666666667	0.997053067858292	1.00377371370507
40	412	410.728013924829	407.25	1.00854024290934	1.0030969060596
41	406	407.469388244543	405.625	1.00454702802969	0.996393868381442
42	398	401.768613262978	404.041666666667	0.994374210406462	0.990619941084072
43	397	399.772143949145	402.708333333333	0.992708893407086	0.993065690065945
44	385	393.971960160716	401.791666666667	0.980537907690261	0.977226906815764
45	390	393.182178679200	401.5	0.979283134941967	0.991906604999521
46	413	409.607126019905	401.791666666667	1.01945152177514	1.00828323963273
47	413	415.67176865333	402.833333333333	1.03187034005792	0.9935724077149
48	401	410.366750144324	404.833333333333	1.01366838240673	0.97717468547091
49	397	405.483429872757	407.458333333333	0.995153115548232	0.97907823292454
50	397	403.403439108268	410.458333333333	0.98281215496888	0.984126463764357
51	409	412.655338459850	413.875	0.997053067858292	0.991141909193534
52	419	421.023528904529	417.458333333333	1.00854024290934	0.995193786651797
53	424	423.081723305171	421.166666666667	1.00454702802969	1.00217044756189
54	428	422.567607163979	424.958333333333	0.994374210406462	1.01285567739676
55	430	425.541212307171	428.666666666667	0.992708893407086	1.01047792214685
56	424	NA	NA	0.980537907690261	NA
57	433	NA	NA	0.979283134941967	NA
58	456	NA	NA	1.01945152177514	NA
59	459	NA	NA	1.03187034005792	NA
60	446	NA	NA	1.01366838240673	NA
61	441	NA	NA	NA	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code