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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 16 Dec 2009 13:36:18 -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/16/t1260995834z49ns9wgp79srex.htm/, Retrieved Tue, 10 Feb 2026 11:42:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68593, Retrieved Tue, 10 Feb 2026 11:42:22 +0000

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Estimated Impact

367

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]
- R  D    [Classical Decomposition] [] [2009-12-02 20:37:38] [80b559301b076f6db87527dfd2199d75]
- R           [Classical Decomposition] [] [2009-12-16 20:36:18] [cf272a759dc2b193d9a85354803ede7b] [Current]
- R             [Classical Decomposition] [decompositie van ...] [2012-12-10 23:28:58] [da21a4ad0d643c5ab6ae91160bdaaba7] 

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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=68593&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=68593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68593&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	519	NA	NA	1.00038941125041	NA
2	517	NA	NA	0.9919493997656	NA
3	510	NA	NA	0.974412888622656	NA
4	509	NA	NA	0.963273968430398	NA
5	501	NA	NA	0.946208433180536	NA
6	507	NA	NA	0.949311983527773	NA
7	569	563.701301874927	539.875	1.04413299722144	1.00939983304535
8	580	577.615334963959	543.5	1.06276970554546	1.0041284655924
9	578	575.676085573907	547.208333333333	1.05202360875457	1.00403684378130
10	565	564.319985769068	550.541666666667	1.02502684163003	1.00120501532478
11	547	549.975026006866	553.5	0.99363148330057	0.9945906161804
12	555	554.757753635811	556.5	0.99686927877055	1.00043667053340
13	562	559.259363781113	559.041666666667	1.00038941125041	1.00490047444241
14	561	556.855594293413	561.375	0.9919493997656	1.00744251426951
15	555	549.690670794256	564.125	0.974412888622656	1.00965875807583
16	544	546.657977084251	567.5	0.963273968430398	0.99513776950914
17	537	540.639843508528	571.375	0.946208433180536	0.993267526335263
18	543	545.854390528469	575	0.949311983527773	0.994770783970968
19	594	603.378355769341	577.875	1.04413299722144	0.98445692378643
20	611	616.672121642755	580.25	1.06276970554546	0.990802046267885
21	613	612.935255050631	582.625	1.05202360875457	1.00010563097625
22	611	599.683411805304	585.041666666667	1.02502684163003	1.01887093751789
23	594	583.758496439085	587.5	0.99363148330057	1.01754407622910
24	595	587.98672959483	589.833333333333	0.99686927877055	1.01192759981165
25	591	592.272214352377	592.041666666667	1.00038941125041	0.99785197697689
26	589	589.135281010786	593.916666666667	0.9919493997656	0.999770373604932
27	584	580.059872489662	595.291666666667	0.974412888622656	1.00679262210197
28	573	574.071148769166	595.958333333333	0.963273968430398	0.998134118442526
29	567	563.979651526982	596.041666666667	0.946208433180536	1.00535542100649
30	569	565.948160846474	596.166666666667	0.949311983527773	1.00539243585307
31	621	622.651310676387	596.333333333333	1.04413299722144	0.997347936721448
32	629	633.897847286804	596.458333333333	1.06276970554546	0.992273443887264
33	628	627.356745353975	596.333333333333	1.05202360875457	1.00102534108510
34	612	611.129544870173	596.208333333333	1.02502684163003	1.00142433815732
35	595	592.70117978879	596.5	0.99363148330057	1.00387854839774
36	597	595.047886986121	596.916666666667	0.99686927877055	1.00328059817802
37	593	597.274161408629	597.041666666667	1.00038941125041	0.992843886970519
38	590	592.069797985092	596.875	0.9919493997656	0.996504131789637
39	580	581.156086989362	596.416666666667	0.974412888622656	0.99801071172574
40	574	573.22828404679	595.083333333333	0.963273968430398	1.00134626286715
41	573	560.98332482191	592.875	0.946208433180536	1.02142073506713
42	573	560.094070281386	590	0.949311983527773	1.02304243234021
43	620	612.906069368987	587	1.04413299722144	1.01157425417294
44	626	620.613225967486	583.958333333333	1.06276970554546	1.00867976028728
45	620	610.436698979839	580.25	1.05202360875457	1.01566632713292
46	588	590.671717489307	576.25	1.02502684163003	0.995476814937638
47	566	568.025997953493	571.666666666667	0.99363148330057	0.996433265447722
48	557	564.228011784132	566	0.99686927877055	0.98718955522737
49	561	560.426484760905	560.208333333333	1.00038941125041	1.00102335498890
50	549	550.490585644918	554.958333333333	0.9919493997656	0.997292259515807
51	532	535.115078001942	549.166666666667	0.974412888622656	0.99417867645671
52	526	523.418992595868	543.375	0.963273968430398	1.00493105416625
53	511	509.533241267718	538.5	0.946208433180536	1.00287863207635
54	499	507.288591197653	534.375	0.949311983527773	0.983660994271358
55	555	554.173588275281	530.75	1.04413299722144	1.00149125065179
56	565	560.301045177781	527.208333333333	1.06276970554546	1.00838648234313
57	542	551.1288680363	523.875	1.05202360875457	0.983436055402384
58	527	533.78272777884	520.75	1.02502684163003	0.98729309244032
59	510	514.204292608045	517.5	0.99363148330057	0.991823692122987
60	514	513.263069906987	514.875	0.99686927877055	1.00143577462752
61	517	513.074719295053	512.875	1.00038941125041	1.00765050499923
62	508	506.348837355348	510.458333333333	0.9919493997656	1.00326091919807
63	493	495.164149568413	508.166666666667	0.974412888622656	0.995629430017704
64	490	487.69758293324	506.291666666667	0.963273968430398	1.00472099339290
65	469	477.914109458935	505.083333333333	0.946208433180536	0.98134788389272
66	478	479.244333017604	504.833333333333	0.949311983527773	0.997403551942349
67	528	NA	NA	1.04413299722144	NA
68	534	NA	NA	1.06276970554546	NA
69	518	NA	NA	1.05202360875457	NA
70	506	NA	NA	1.02502684163003	NA
71	502	NA	NA	0.99363148330057	NA
72	516	NA	NA	0.99686927877055	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 519 & NA & NA & 1.00038941125041 & NA \tabularnewline
2 & 517 & NA & NA & 0.9919493997656 & NA \tabularnewline
3 & 510 & NA & NA & 0.974412888622656 & NA \tabularnewline
4 & 509 & NA & NA & 0.963273968430398 & NA \tabularnewline
5 & 501 & NA & NA & 0.946208433180536 & NA \tabularnewline
6 & 507 & NA & NA & 0.949311983527773 & NA \tabularnewline
7 & 569 & 563.701301874927 & 539.875 & 1.04413299722144 & 1.00939983304535 \tabularnewline
8 & 580 & 577.615334963959 & 543.5 & 1.06276970554546 & 1.0041284655924 \tabularnewline
9 & 578 & 575.676085573907 & 547.208333333333 & 1.05202360875457 & 1.00403684378130 \tabularnewline
10 & 565 & 564.319985769068 & 550.541666666667 & 1.02502684163003 & 1.00120501532478 \tabularnewline
11 & 547 & 549.975026006866 & 553.5 & 0.99363148330057 & 0.9945906161804 \tabularnewline
12 & 555 & 554.757753635811 & 556.5 & 0.99686927877055 & 1.00043667053340 \tabularnewline
13 & 562 & 559.259363781113 & 559.041666666667 & 1.00038941125041 & 1.00490047444241 \tabularnewline
14 & 561 & 556.855594293413 & 561.375 & 0.9919493997656 & 1.00744251426951 \tabularnewline
15 & 555 & 549.690670794256 & 564.125 & 0.974412888622656 & 1.00965875807583 \tabularnewline
16 & 544 & 546.657977084251 & 567.5 & 0.963273968430398 & 0.99513776950914 \tabularnewline
17 & 537 & 540.639843508528 & 571.375 & 0.946208433180536 & 0.993267526335263 \tabularnewline
18 & 543 & 545.854390528469 & 575 & 0.949311983527773 & 0.994770783970968 \tabularnewline
19 & 594 & 603.378355769341 & 577.875 & 1.04413299722144 & 0.98445692378643 \tabularnewline
20 & 611 & 616.672121642755 & 580.25 & 1.06276970554546 & 0.990802046267885 \tabularnewline
21 & 613 & 612.935255050631 & 582.625 & 1.05202360875457 & 1.00010563097625 \tabularnewline
22 & 611 & 599.683411805304 & 585.041666666667 & 1.02502684163003 & 1.01887093751789 \tabularnewline
23 & 594 & 583.758496439085 & 587.5 & 0.99363148330057 & 1.01754407622910 \tabularnewline
24 & 595 & 587.98672959483 & 589.833333333333 & 0.99686927877055 & 1.01192759981165 \tabularnewline
25 & 591 & 592.272214352377 & 592.041666666667 & 1.00038941125041 & 0.99785197697689 \tabularnewline
26 & 589 & 589.135281010786 & 593.916666666667 & 0.9919493997656 & 0.999770373604932 \tabularnewline
27 & 584 & 580.059872489662 & 595.291666666667 & 0.974412888622656 & 1.00679262210197 \tabularnewline
28 & 573 & 574.071148769166 & 595.958333333333 & 0.963273968430398 & 0.998134118442526 \tabularnewline
29 & 567 & 563.979651526982 & 596.041666666667 & 0.946208433180536 & 1.00535542100649 \tabularnewline
30 & 569 & 565.948160846474 & 596.166666666667 & 0.949311983527773 & 1.00539243585307 \tabularnewline
31 & 621 & 622.651310676387 & 596.333333333333 & 1.04413299722144 & 0.997347936721448 \tabularnewline
32 & 629 & 633.897847286804 & 596.458333333333 & 1.06276970554546 & 0.992273443887264 \tabularnewline
33 & 628 & 627.356745353975 & 596.333333333333 & 1.05202360875457 & 1.00102534108510 \tabularnewline
34 & 612 & 611.129544870173 & 596.208333333333 & 1.02502684163003 & 1.00142433815732 \tabularnewline
35 & 595 & 592.70117978879 & 596.5 & 0.99363148330057 & 1.00387854839774 \tabularnewline
36 & 597 & 595.047886986121 & 596.916666666667 & 0.99686927877055 & 1.00328059817802 \tabularnewline
37 & 593 & 597.274161408629 & 597.041666666667 & 1.00038941125041 & 0.992843886970519 \tabularnewline
38 & 590 & 592.069797985092 & 596.875 & 0.9919493997656 & 0.996504131789637 \tabularnewline
39 & 580 & 581.156086989362 & 596.416666666667 & 0.974412888622656 & 0.99801071172574 \tabularnewline
40 & 574 & 573.22828404679 & 595.083333333333 & 0.963273968430398 & 1.00134626286715 \tabularnewline
41 & 573 & 560.98332482191 & 592.875 & 0.946208433180536 & 1.02142073506713 \tabularnewline
42 & 573 & 560.094070281386 & 590 & 0.949311983527773 & 1.02304243234021 \tabularnewline
43 & 620 & 612.906069368987 & 587 & 1.04413299722144 & 1.01157425417294 \tabularnewline
44 & 626 & 620.613225967486 & 583.958333333333 & 1.06276970554546 & 1.00867976028728 \tabularnewline
45 & 620 & 610.436698979839 & 580.25 & 1.05202360875457 & 1.01566632713292 \tabularnewline
46 & 588 & 590.671717489307 & 576.25 & 1.02502684163003 & 0.995476814937638 \tabularnewline
47 & 566 & 568.025997953493 & 571.666666666667 & 0.99363148330057 & 0.996433265447722 \tabularnewline
48 & 557 & 564.228011784132 & 566 & 0.99686927877055 & 0.98718955522737 \tabularnewline
49 & 561 & 560.426484760905 & 560.208333333333 & 1.00038941125041 & 1.00102335498890 \tabularnewline
50 & 549 & 550.490585644918 & 554.958333333333 & 0.9919493997656 & 0.997292259515807 \tabularnewline
51 & 532 & 535.115078001942 & 549.166666666667 & 0.974412888622656 & 0.99417867645671 \tabularnewline
52 & 526 & 523.418992595868 & 543.375 & 0.963273968430398 & 1.00493105416625 \tabularnewline
53 & 511 & 509.533241267718 & 538.5 & 0.946208433180536 & 1.00287863207635 \tabularnewline
54 & 499 & 507.288591197653 & 534.375 & 0.949311983527773 & 0.983660994271358 \tabularnewline
55 & 555 & 554.173588275281 & 530.75 & 1.04413299722144 & 1.00149125065179 \tabularnewline
56 & 565 & 560.301045177781 & 527.208333333333 & 1.06276970554546 & 1.00838648234313 \tabularnewline
57 & 542 & 551.1288680363 & 523.875 & 1.05202360875457 & 0.983436055402384 \tabularnewline
58 & 527 & 533.78272777884 & 520.75 & 1.02502684163003 & 0.98729309244032 \tabularnewline
59 & 510 & 514.204292608045 & 517.5 & 0.99363148330057 & 0.991823692122987 \tabularnewline
60 & 514 & 513.263069906987 & 514.875 & 0.99686927877055 & 1.00143577462752 \tabularnewline
61 & 517 & 513.074719295053 & 512.875 & 1.00038941125041 & 1.00765050499923 \tabularnewline
62 & 508 & 506.348837355348 & 510.458333333333 & 0.9919493997656 & 1.00326091919807 \tabularnewline
63 & 493 & 495.164149568413 & 508.166666666667 & 0.974412888622656 & 0.995629430017704 \tabularnewline
64 & 490 & 487.69758293324 & 506.291666666667 & 0.963273968430398 & 1.00472099339290 \tabularnewline
65 & 469 & 477.914109458935 & 505.083333333333 & 0.946208433180536 & 0.98134788389272 \tabularnewline
66 & 478 & 479.244333017604 & 504.833333333333 & 0.949311983527773 & 0.997403551942349 \tabularnewline
67 & 528 & NA & NA & 1.04413299722144 & NA \tabularnewline
68 & 534 & NA & NA & 1.06276970554546 & NA \tabularnewline
69 & 518 & NA & NA & 1.05202360875457 & NA \tabularnewline
70 & 506 & NA & NA & 1.02502684163003 & NA \tabularnewline
71 & 502 & NA & NA & 0.99363148330057 & NA \tabularnewline
72 & 516 & NA & NA & 0.99686927877055 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68593&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]519[/C][C]NA[/C][C]NA[/C][C]1.00038941125041[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]517[/C][C]NA[/C][C]NA[/C][C]0.9919493997656[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]510[/C][C]NA[/C][C]NA[/C][C]0.974412888622656[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]509[/C][C]NA[/C][C]NA[/C][C]0.963273968430398[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]501[/C][C]NA[/C][C]NA[/C][C]0.946208433180536[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]507[/C][C]NA[/C][C]NA[/C][C]0.949311983527773[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]569[/C][C]563.701301874927[/C][C]539.875[/C][C]1.04413299722144[/C][C]1.00939983304535[/C][/ROW]
[ROW][C]8[/C][C]580[/C][C]577.615334963959[/C][C]543.5[/C][C]1.06276970554546[/C][C]1.0041284655924[/C][/ROW]
[ROW][C]9[/C][C]578[/C][C]575.676085573907[/C][C]547.208333333333[/C][C]1.05202360875457[/C][C]1.00403684378130[/C][/ROW]
[ROW][C]10[/C][C]565[/C][C]564.319985769068[/C][C]550.541666666667[/C][C]1.02502684163003[/C][C]1.00120501532478[/C][/ROW]
[ROW][C]11[/C][C]547[/C][C]549.975026006866[/C][C]553.5[/C][C]0.99363148330057[/C][C]0.9945906161804[/C][/ROW]
[ROW][C]12[/C][C]555[/C][C]554.757753635811[/C][C]556.5[/C][C]0.99686927877055[/C][C]1.00043667053340[/C][/ROW]
[ROW][C]13[/C][C]562[/C][C]559.259363781113[/C][C]559.041666666667[/C][C]1.00038941125041[/C][C]1.00490047444241[/C][/ROW]
[ROW][C]14[/C][C]561[/C][C]556.855594293413[/C][C]561.375[/C][C]0.9919493997656[/C][C]1.00744251426951[/C][/ROW]
[ROW][C]15[/C][C]555[/C][C]549.690670794256[/C][C]564.125[/C][C]0.974412888622656[/C][C]1.00965875807583[/C][/ROW]
[ROW][C]16[/C][C]544[/C][C]546.657977084251[/C][C]567.5[/C][C]0.963273968430398[/C][C]0.99513776950914[/C][/ROW]
[ROW][C]17[/C][C]537[/C][C]540.639843508528[/C][C]571.375[/C][C]0.946208433180536[/C][C]0.993267526335263[/C][/ROW]
[ROW][C]18[/C][C]543[/C][C]545.854390528469[/C][C]575[/C][C]0.949311983527773[/C][C]0.994770783970968[/C][/ROW]
[ROW][C]19[/C][C]594[/C][C]603.378355769341[/C][C]577.875[/C][C]1.04413299722144[/C][C]0.98445692378643[/C][/ROW]
[ROW][C]20[/C][C]611[/C][C]616.672121642755[/C][C]580.25[/C][C]1.06276970554546[/C][C]0.990802046267885[/C][/ROW]
[ROW][C]21[/C][C]613[/C][C]612.935255050631[/C][C]582.625[/C][C]1.05202360875457[/C][C]1.00010563097625[/C][/ROW]
[ROW][C]22[/C][C]611[/C][C]599.683411805304[/C][C]585.041666666667[/C][C]1.02502684163003[/C][C]1.01887093751789[/C][/ROW]
[ROW][C]23[/C][C]594[/C][C]583.758496439085[/C][C]587.5[/C][C]0.99363148330057[/C][C]1.01754407622910[/C][/ROW]
[ROW][C]24[/C][C]595[/C][C]587.98672959483[/C][C]589.833333333333[/C][C]0.99686927877055[/C][C]1.01192759981165[/C][/ROW]
[ROW][C]25[/C][C]591[/C][C]592.272214352377[/C][C]592.041666666667[/C][C]1.00038941125041[/C][C]0.99785197697689[/C][/ROW]
[ROW][C]26[/C][C]589[/C][C]589.135281010786[/C][C]593.916666666667[/C][C]0.9919493997656[/C][C]0.999770373604932[/C][/ROW]
[ROW][C]27[/C][C]584[/C][C]580.059872489662[/C][C]595.291666666667[/C][C]0.974412888622656[/C][C]1.00679262210197[/C][/ROW]
[ROW][C]28[/C][C]573[/C][C]574.071148769166[/C][C]595.958333333333[/C][C]0.963273968430398[/C][C]0.998134118442526[/C][/ROW]
[ROW][C]29[/C][C]567[/C][C]563.979651526982[/C][C]596.041666666667[/C][C]0.946208433180536[/C][C]1.00535542100649[/C][/ROW]
[ROW][C]30[/C][C]569[/C][C]565.948160846474[/C][C]596.166666666667[/C][C]0.949311983527773[/C][C]1.00539243585307[/C][/ROW]
[ROW][C]31[/C][C]621[/C][C]622.651310676387[/C][C]596.333333333333[/C][C]1.04413299722144[/C][C]0.997347936721448[/C][/ROW]
[ROW][C]32[/C][C]629[/C][C]633.897847286804[/C][C]596.458333333333[/C][C]1.06276970554546[/C][C]0.992273443887264[/C][/ROW]
[ROW][C]33[/C][C]628[/C][C]627.356745353975[/C][C]596.333333333333[/C][C]1.05202360875457[/C][C]1.00102534108510[/C][/ROW]
[ROW][C]34[/C][C]612[/C][C]611.129544870173[/C][C]596.208333333333[/C][C]1.02502684163003[/C][C]1.00142433815732[/C][/ROW]
[ROW][C]35[/C][C]595[/C][C]592.70117978879[/C][C]596.5[/C][C]0.99363148330057[/C][C]1.00387854839774[/C][/ROW]
[ROW][C]36[/C][C]597[/C][C]595.047886986121[/C][C]596.916666666667[/C][C]0.99686927877055[/C][C]1.00328059817802[/C][/ROW]
[ROW][C]37[/C][C]593[/C][C]597.274161408629[/C][C]597.041666666667[/C][C]1.00038941125041[/C][C]0.992843886970519[/C][/ROW]
[ROW][C]38[/C][C]590[/C][C]592.069797985092[/C][C]596.875[/C][C]0.9919493997656[/C][C]0.996504131789637[/C][/ROW]
[ROW][C]39[/C][C]580[/C][C]581.156086989362[/C][C]596.416666666667[/C][C]0.974412888622656[/C][C]0.99801071172574[/C][/ROW]
[ROW][C]40[/C][C]574[/C][C]573.22828404679[/C][C]595.083333333333[/C][C]0.963273968430398[/C][C]1.00134626286715[/C][/ROW]
[ROW][C]41[/C][C]573[/C][C]560.98332482191[/C][C]592.875[/C][C]0.946208433180536[/C][C]1.02142073506713[/C][/ROW]
[ROW][C]42[/C][C]573[/C][C]560.094070281386[/C][C]590[/C][C]0.949311983527773[/C][C]1.02304243234021[/C][/ROW]
[ROW][C]43[/C][C]620[/C][C]612.906069368987[/C][C]587[/C][C]1.04413299722144[/C][C]1.01157425417294[/C][/ROW]
[ROW][C]44[/C][C]626[/C][C]620.613225967486[/C][C]583.958333333333[/C][C]1.06276970554546[/C][C]1.00867976028728[/C][/ROW]
[ROW][C]45[/C][C]620[/C][C]610.436698979839[/C][C]580.25[/C][C]1.05202360875457[/C][C]1.01566632713292[/C][/ROW]
[ROW][C]46[/C][C]588[/C][C]590.671717489307[/C][C]576.25[/C][C]1.02502684163003[/C][C]0.995476814937638[/C][/ROW]
[ROW][C]47[/C][C]566[/C][C]568.025997953493[/C][C]571.666666666667[/C][C]0.99363148330057[/C][C]0.996433265447722[/C][/ROW]
[ROW][C]48[/C][C]557[/C][C]564.228011784132[/C][C]566[/C][C]0.99686927877055[/C][C]0.98718955522737[/C][/ROW]
[ROW][C]49[/C][C]561[/C][C]560.426484760905[/C][C]560.208333333333[/C][C]1.00038941125041[/C][C]1.00102335498890[/C][/ROW]
[ROW][C]50[/C][C]549[/C][C]550.490585644918[/C][C]554.958333333333[/C][C]0.9919493997656[/C][C]0.997292259515807[/C][/ROW]
[ROW][C]51[/C][C]532[/C][C]535.115078001942[/C][C]549.166666666667[/C][C]0.974412888622656[/C][C]0.99417867645671[/C][/ROW]
[ROW][C]52[/C][C]526[/C][C]523.418992595868[/C][C]543.375[/C][C]0.963273968430398[/C][C]1.00493105416625[/C][/ROW]
[ROW][C]53[/C][C]511[/C][C]509.533241267718[/C][C]538.5[/C][C]0.946208433180536[/C][C]1.00287863207635[/C][/ROW]
[ROW][C]54[/C][C]499[/C][C]507.288591197653[/C][C]534.375[/C][C]0.949311983527773[/C][C]0.983660994271358[/C][/ROW]
[ROW][C]55[/C][C]555[/C][C]554.173588275281[/C][C]530.75[/C][C]1.04413299722144[/C][C]1.00149125065179[/C][/ROW]
[ROW][C]56[/C][C]565[/C][C]560.301045177781[/C][C]527.208333333333[/C][C]1.06276970554546[/C][C]1.00838648234313[/C][/ROW]
[ROW][C]57[/C][C]542[/C][C]551.1288680363[/C][C]523.875[/C][C]1.05202360875457[/C][C]0.983436055402384[/C][/ROW]
[ROW][C]58[/C][C]527[/C][C]533.78272777884[/C][C]520.75[/C][C]1.02502684163003[/C][C]0.98729309244032[/C][/ROW]
[ROW][C]59[/C][C]510[/C][C]514.204292608045[/C][C]517.5[/C][C]0.99363148330057[/C][C]0.991823692122987[/C][/ROW]
[ROW][C]60[/C][C]514[/C][C]513.263069906987[/C][C]514.875[/C][C]0.99686927877055[/C][C]1.00143577462752[/C][/ROW]
[ROW][C]61[/C][C]517[/C][C]513.074719295053[/C][C]512.875[/C][C]1.00038941125041[/C][C]1.00765050499923[/C][/ROW]
[ROW][C]62[/C][C]508[/C][C]506.348837355348[/C][C]510.458333333333[/C][C]0.9919493997656[/C][C]1.00326091919807[/C][/ROW]
[ROW][C]63[/C][C]493[/C][C]495.164149568413[/C][C]508.166666666667[/C][C]0.974412888622656[/C][C]0.995629430017704[/C][/ROW]
[ROW][C]64[/C][C]490[/C][C]487.69758293324[/C][C]506.291666666667[/C][C]0.963273968430398[/C][C]1.00472099339290[/C][/ROW]
[ROW][C]65[/C][C]469[/C][C]477.914109458935[/C][C]505.083333333333[/C][C]0.946208433180536[/C][C]0.98134788389272[/C][/ROW]
[ROW][C]66[/C][C]478[/C][C]479.244333017604[/C][C]504.833333333333[/C][C]0.949311983527773[/C][C]0.997403551942349[/C][/ROW]
[ROW][C]67[/C][C]528[/C][C]NA[/C][C]NA[/C][C]1.04413299722144[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]534[/C][C]NA[/C][C]NA[/C][C]1.06276970554546[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]518[/C][C]NA[/C][C]NA[/C][C]1.05202360875457[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]506[/C][C]NA[/C][C]NA[/C][C]1.02502684163003[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]502[/C][C]NA[/C][C]NA[/C][C]0.99363148330057[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]516[/C][C]NA[/C][C]NA[/C][C]0.99686927877055[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68593&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	519	NA	NA	1.00038941125041	NA
2	517	NA	NA	0.9919493997656	NA
3	510	NA	NA	0.974412888622656	NA
4	509	NA	NA	0.963273968430398	NA
5	501	NA	NA	0.946208433180536	NA
6	507	NA	NA	0.949311983527773	NA
7	569	563.701301874927	539.875	1.04413299722144	1.00939983304535
8	580	577.615334963959	543.5	1.06276970554546	1.0041284655924
9	578	575.676085573907	547.208333333333	1.05202360875457	1.00403684378130
10	565	564.319985769068	550.541666666667	1.02502684163003	1.00120501532478
11	547	549.975026006866	553.5	0.99363148330057	0.9945906161804
12	555	554.757753635811	556.5	0.99686927877055	1.00043667053340
13	562	559.259363781113	559.041666666667	1.00038941125041	1.00490047444241
14	561	556.855594293413	561.375	0.9919493997656	1.00744251426951
15	555	549.690670794256	564.125	0.974412888622656	1.00965875807583
16	544	546.657977084251	567.5	0.963273968430398	0.99513776950914
17	537	540.639843508528	571.375	0.946208433180536	0.993267526335263
18	543	545.854390528469	575	0.949311983527773	0.994770783970968
19	594	603.378355769341	577.875	1.04413299722144	0.98445692378643
20	611	616.672121642755	580.25	1.06276970554546	0.990802046267885
21	613	612.935255050631	582.625	1.05202360875457	1.00010563097625
22	611	599.683411805304	585.041666666667	1.02502684163003	1.01887093751789
23	594	583.758496439085	587.5	0.99363148330057	1.01754407622910
24	595	587.98672959483	589.833333333333	0.99686927877055	1.01192759981165
25	591	592.272214352377	592.041666666667	1.00038941125041	0.99785197697689
26	589	589.135281010786	593.916666666667	0.9919493997656	0.999770373604932
27	584	580.059872489662	595.291666666667	0.974412888622656	1.00679262210197
28	573	574.071148769166	595.958333333333	0.963273968430398	0.998134118442526
29	567	563.979651526982	596.041666666667	0.946208433180536	1.00535542100649
30	569	565.948160846474	596.166666666667	0.949311983527773	1.00539243585307
31	621	622.651310676387	596.333333333333	1.04413299722144	0.997347936721448
32	629	633.897847286804	596.458333333333	1.06276970554546	0.992273443887264
33	628	627.356745353975	596.333333333333	1.05202360875457	1.00102534108510
34	612	611.129544870173	596.208333333333	1.02502684163003	1.00142433815732
35	595	592.70117978879	596.5	0.99363148330057	1.00387854839774
36	597	595.047886986121	596.916666666667	0.99686927877055	1.00328059817802
37	593	597.274161408629	597.041666666667	1.00038941125041	0.992843886970519
38	590	592.069797985092	596.875	0.9919493997656	0.996504131789637
39	580	581.156086989362	596.416666666667	0.974412888622656	0.99801071172574
40	574	573.22828404679	595.083333333333	0.963273968430398	1.00134626286715
41	573	560.98332482191	592.875	0.946208433180536	1.02142073506713
42	573	560.094070281386	590	0.949311983527773	1.02304243234021
43	620	612.906069368987	587	1.04413299722144	1.01157425417294
44	626	620.613225967486	583.958333333333	1.06276970554546	1.00867976028728
45	620	610.436698979839	580.25	1.05202360875457	1.01566632713292
46	588	590.671717489307	576.25	1.02502684163003	0.995476814937638
47	566	568.025997953493	571.666666666667	0.99363148330057	0.996433265447722
48	557	564.228011784132	566	0.99686927877055	0.98718955522737
49	561	560.426484760905	560.208333333333	1.00038941125041	1.00102335498890
50	549	550.490585644918	554.958333333333	0.9919493997656	0.997292259515807
51	532	535.115078001942	549.166666666667	0.974412888622656	0.99417867645671
52	526	523.418992595868	543.375	0.963273968430398	1.00493105416625
53	511	509.533241267718	538.5	0.946208433180536	1.00287863207635
54	499	507.288591197653	534.375	0.949311983527773	0.983660994271358
55	555	554.173588275281	530.75	1.04413299722144	1.00149125065179
56	565	560.301045177781	527.208333333333	1.06276970554546	1.00838648234313
57	542	551.1288680363	523.875	1.05202360875457	0.983436055402384
58	527	533.78272777884	520.75	1.02502684163003	0.98729309244032
59	510	514.204292608045	517.5	0.99363148330057	0.991823692122987
60	514	513.263069906987	514.875	0.99686927877055	1.00143577462752
61	517	513.074719295053	512.875	1.00038941125041	1.00765050499923
62	508	506.348837355348	510.458333333333	0.9919493997656	1.00326091919807
63	493	495.164149568413	508.166666666667	0.974412888622656	0.995629430017704
64	490	487.69758293324	506.291666666667	0.963273968430398	1.00472099339290
65	469	477.914109458935	505.083333333333	0.946208433180536	0.98134788389272
66	478	479.244333017604	504.833333333333	0.949311983527773	0.997403551942349
67	528	NA	NA	1.04413299722144	NA
68	534	NA	NA	1.06276970554546	NA
69	518	NA	NA	1.05202360875457	NA
70	506	NA	NA	1.02502684163003	NA
71	502	NA	NA	0.99363148330057	NA
72	516	NA	NA	0.99686927877055	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