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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 26 May 2010 13:02:37 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/May/26/t1274879063y6os1qlz90a4qy3.htm/, Retrieved Thu, 31 Oct 2024 23:48:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=76481, Retrieved Thu, 31 Oct 2024 23:48:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W52
Estimated Impact184
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [opgave 9 2] [2010-01-12 18:42:00] [acb4d9171c10fb50d016574efb6916c7]
-    D    [Classical Decomposition] [Werkloosheid cijf...] [2010-05-26 13:02:37] [26ddb8a30b965ed6738d4d4bc4c527d5] [Current]
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Dataseries X:
580
575
558
564
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590
593
597
595
612
628
629
621
569
567
573
584
589
591
595
594
611
613
611
594
543
537
544
555
561
562




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76481&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76481&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76481&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1580NANA0.99948551451067NA
2575NANA0.994839120116967NA
3558NANA0.989801169879415NA
4564NANA1.01675939712162NA
5581NANA1.04390985124311NA
6597NANA1.05992158038544NA
7587580.320000294003556.8333333333331.042178988854841.01151089003069
8536536.275538691632552.2083333333330.9711471311098750.999486199403567
9524521.28065884185547.4166666666670.9522557323949151.0052166546217
10537522.528377393316542.6666666666670.9628901303316641.02769538121332
11536524.424391996947537.6250.9754464394270121.02207297787766
12533527.777912394454532.3750.9913649446244731.00989447925521
13528527.020382755522527.2916666666670.999485514510671.00185878435926
14516519.720537001105522.4166666666670.9948391201169670.992841273845798
15502512.428313989655517.7083333333330.9898011698794150.979649223696359
16506522.063585447071513.4583333333331.016759397121620.969230595860627
17518532.089550427375509.7083333333331.043909851243110.973520339920116
18534537.247751057871506.8751.059921580385440.99395483545259
19528526.691206492514505.3751.042178988854841.00248493517900
20478490.267443355302504.8333333333330.9711471311098750.974978058360666
21469480.968499503798505.0833333333330.9522557323949150.975115834995128
22490487.503248902502506.2916666666670.9628901303316641.00512150658097
23493495.689365635493508.1666666666670.9754464394270120.994574493983656
24508506.050497358101510.4583333333330.9913649446244731.00385238756226
25517512.611133254659512.8750.999485514510671.00856178584627
26514512.217791970223514.8750.9948391201169671.00347939501071
27510512.222105412597517.50.9898011698794150.995661832261598
28527529.477456051083520.751.016759397121620.99532094138708
29542546.878273319986523.8751.043909851243110.99107978217827
30565558.799489859041527.2083333333331.059921580385441.01109612706075
31555553.136498334706530.751.042178988854841.00336897252469
32499518.956748186839534.3750.9711471311098750.961544486594374
33511512.789711894661538.50.9522557323949150.99650985218083
34526523.210424568968543.3750.9628901303316641.00533165109111
35532535.682669652549.1666666666670.9754464394270120.993125277593182
36549550.16623739389554.9583333333330.9913649446244730.997880209081143
37561559.920114274831560.2083333333330.999485514510671.00192864249317
38557563.0789419862035660.9948391201169670.98920410348723
39566565.836335447732571.6666666666670.9898011698794151.00028924362402
40588585.907602591333576.251.016759397121621.00357120713132
41620605.728691183816580.251.043909851243111.0235605627138
42626618.950039545915583.9583333333331.059921580385441.01139019307480
43620611.759066457795871.042178988854841.01347088093018
44573572.9768073548265900.9711471311098751.00004047745891
45573564.568617343635592.8750.9522557323949151.01493420356242
46574572.999868391534595.0833333333330.9628901303316641.00174543078216
47580581.772513914927596.4166666666670.9754464394270120.996953252564307
48590591.720951322732596.8750.9913649446244730.9970916167175
49593596.734497392641597.0416666666670.999485514510670.993741777274553
50597593.836051449819596.9166666666670.9948391201169671.00532798327494
51595590.416397833071596.50.9898011698794151.00776333818598
52612606.200425558885596.2083333333331.016759397121621.00956709067924
53628622.51824129131596.3333333333331.043909851243111.00880578004802
54629632.199059300733596.4583333333331.059921580385440.994939791109035
55621621.486070353769596.3333333333331.042178988854840.9992178901878
56569578.96554799667596.1666666666670.9711471311098750.982787321229816
57567567.584093829552596.0416666666670.9522557323949150.99897091226498
58573573.842397255575595.9583333333330.9628901303316640.998532005896387
59584580.675136670571595.2916666666670.9754464394270121.00572585791858
60589588.788163361551593.9166666666670.9913649446244731.00035978413227
61591591.737069820087592.0416666666670.999485514510670.998754396407324
62595586.789274348991589.8333333333330.9948391201169671.0139926307619
63594581.508187304156587.50.9898011698794151.02148174861261
64611594.846612291027585.0416666666671.016759397121621.02715555132231
65613608.207977080519582.6251.043909851243111.00787892152037
66611615.019497018652580.251.059921580385440.993464439683397
67594602.24918318449577.8751.042178988854840.986302707558902
68543NANA0.971147131109875NA
69537NANA0.952255732394915NA
70544NANA0.962890130331664NA
71555NANA0.975446439427012NA
72561NANA0.991364944624473NA
73562NANANANA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 580 & NA & NA & 0.99948551451067 & NA \tabularnewline
2 & 575 & NA & NA & 0.994839120116967 & NA \tabularnewline
3 & 558 & NA & NA & 0.989801169879415 & NA \tabularnewline
4 & 564 & NA & NA & 1.01675939712162 & NA \tabularnewline
5 & 581 & NA & NA & 1.04390985124311 & NA \tabularnewline
6 & 597 & NA & NA & 1.05992158038544 & NA \tabularnewline
7 & 587 & 580.320000294003 & 556.833333333333 & 1.04217898885484 & 1.01151089003069 \tabularnewline
8 & 536 & 536.275538691632 & 552.208333333333 & 0.971147131109875 & 0.999486199403567 \tabularnewline
9 & 524 & 521.28065884185 & 547.416666666667 & 0.952255732394915 & 1.0052166546217 \tabularnewline
10 & 537 & 522.528377393316 & 542.666666666667 & 0.962890130331664 & 1.02769538121332 \tabularnewline
11 & 536 & 524.424391996947 & 537.625 & 0.975446439427012 & 1.02207297787766 \tabularnewline
12 & 533 & 527.777912394454 & 532.375 & 0.991364944624473 & 1.00989447925521 \tabularnewline
13 & 528 & 527.020382755522 & 527.291666666667 & 0.99948551451067 & 1.00185878435926 \tabularnewline
14 & 516 & 519.720537001105 & 522.416666666667 & 0.994839120116967 & 0.992841273845798 \tabularnewline
15 & 502 & 512.428313989655 & 517.708333333333 & 0.989801169879415 & 0.979649223696359 \tabularnewline
16 & 506 & 522.063585447071 & 513.458333333333 & 1.01675939712162 & 0.969230595860627 \tabularnewline
17 & 518 & 532.089550427375 & 509.708333333333 & 1.04390985124311 & 0.973520339920116 \tabularnewline
18 & 534 & 537.247751057871 & 506.875 & 1.05992158038544 & 0.99395483545259 \tabularnewline
19 & 528 & 526.691206492514 & 505.375 & 1.04217898885484 & 1.00248493517900 \tabularnewline
20 & 478 & 490.267443355302 & 504.833333333333 & 0.971147131109875 & 0.974978058360666 \tabularnewline
21 & 469 & 480.968499503798 & 505.083333333333 & 0.952255732394915 & 0.975115834995128 \tabularnewline
22 & 490 & 487.503248902502 & 506.291666666667 & 0.962890130331664 & 1.00512150658097 \tabularnewline
23 & 493 & 495.689365635493 & 508.166666666667 & 0.975446439427012 & 0.994574493983656 \tabularnewline
24 & 508 & 506.050497358101 & 510.458333333333 & 0.991364944624473 & 1.00385238756226 \tabularnewline
25 & 517 & 512.611133254659 & 512.875 & 0.99948551451067 & 1.00856178584627 \tabularnewline
26 & 514 & 512.217791970223 & 514.875 & 0.994839120116967 & 1.00347939501071 \tabularnewline
27 & 510 & 512.222105412597 & 517.5 & 0.989801169879415 & 0.995661832261598 \tabularnewline
28 & 527 & 529.477456051083 & 520.75 & 1.01675939712162 & 0.99532094138708 \tabularnewline
29 & 542 & 546.878273319986 & 523.875 & 1.04390985124311 & 0.99107978217827 \tabularnewline
30 & 565 & 558.799489859041 & 527.208333333333 & 1.05992158038544 & 1.01109612706075 \tabularnewline
31 & 555 & 553.136498334706 & 530.75 & 1.04217898885484 & 1.00336897252469 \tabularnewline
32 & 499 & 518.956748186839 & 534.375 & 0.971147131109875 & 0.961544486594374 \tabularnewline
33 & 511 & 512.789711894661 & 538.5 & 0.952255732394915 & 0.99650985218083 \tabularnewline
34 & 526 & 523.210424568968 & 543.375 & 0.962890130331664 & 1.00533165109111 \tabularnewline
35 & 532 & 535.682669652 & 549.166666666667 & 0.975446439427012 & 0.993125277593182 \tabularnewline
36 & 549 & 550.16623739389 & 554.958333333333 & 0.991364944624473 & 0.997880209081143 \tabularnewline
37 & 561 & 559.920114274831 & 560.208333333333 & 0.99948551451067 & 1.00192864249317 \tabularnewline
38 & 557 & 563.078941986203 & 566 & 0.994839120116967 & 0.98920410348723 \tabularnewline
39 & 566 & 565.836335447732 & 571.666666666667 & 0.989801169879415 & 1.00028924362402 \tabularnewline
40 & 588 & 585.907602591333 & 576.25 & 1.01675939712162 & 1.00357120713132 \tabularnewline
41 & 620 & 605.728691183816 & 580.25 & 1.04390985124311 & 1.0235605627138 \tabularnewline
42 & 626 & 618.950039545915 & 583.958333333333 & 1.05992158038544 & 1.01139019307480 \tabularnewline
43 & 620 & 611.75906645779 & 587 & 1.04217898885484 & 1.01347088093018 \tabularnewline
44 & 573 & 572.976807354826 & 590 & 0.971147131109875 & 1.00004047745891 \tabularnewline
45 & 573 & 564.568617343635 & 592.875 & 0.952255732394915 & 1.01493420356242 \tabularnewline
46 & 574 & 572.999868391534 & 595.083333333333 & 0.962890130331664 & 1.00174543078216 \tabularnewline
47 & 580 & 581.772513914927 & 596.416666666667 & 0.975446439427012 & 0.996953252564307 \tabularnewline
48 & 590 & 591.720951322732 & 596.875 & 0.991364944624473 & 0.9970916167175 \tabularnewline
49 & 593 & 596.734497392641 & 597.041666666667 & 0.99948551451067 & 0.993741777274553 \tabularnewline
50 & 597 & 593.836051449819 & 596.916666666667 & 0.994839120116967 & 1.00532798327494 \tabularnewline
51 & 595 & 590.416397833071 & 596.5 & 0.989801169879415 & 1.00776333818598 \tabularnewline
52 & 612 & 606.200425558885 & 596.208333333333 & 1.01675939712162 & 1.00956709067924 \tabularnewline
53 & 628 & 622.51824129131 & 596.333333333333 & 1.04390985124311 & 1.00880578004802 \tabularnewline
54 & 629 & 632.199059300733 & 596.458333333333 & 1.05992158038544 & 0.994939791109035 \tabularnewline
55 & 621 & 621.486070353769 & 596.333333333333 & 1.04217898885484 & 0.9992178901878 \tabularnewline
56 & 569 & 578.96554799667 & 596.166666666667 & 0.971147131109875 & 0.982787321229816 \tabularnewline
57 & 567 & 567.584093829552 & 596.041666666667 & 0.952255732394915 & 0.99897091226498 \tabularnewline
58 & 573 & 573.842397255575 & 595.958333333333 & 0.962890130331664 & 0.998532005896387 \tabularnewline
59 & 584 & 580.675136670571 & 595.291666666667 & 0.975446439427012 & 1.00572585791858 \tabularnewline
60 & 589 & 588.788163361551 & 593.916666666667 & 0.991364944624473 & 1.00035978413227 \tabularnewline
61 & 591 & 591.737069820087 & 592.041666666667 & 0.99948551451067 & 0.998754396407324 \tabularnewline
62 & 595 & 586.789274348991 & 589.833333333333 & 0.994839120116967 & 1.0139926307619 \tabularnewline
63 & 594 & 581.508187304156 & 587.5 & 0.989801169879415 & 1.02148174861261 \tabularnewline
64 & 611 & 594.846612291027 & 585.041666666667 & 1.01675939712162 & 1.02715555132231 \tabularnewline
65 & 613 & 608.207977080519 & 582.625 & 1.04390985124311 & 1.00787892152037 \tabularnewline
66 & 611 & 615.019497018652 & 580.25 & 1.05992158038544 & 0.993464439683397 \tabularnewline
67 & 594 & 602.24918318449 & 577.875 & 1.04217898885484 & 0.986302707558902 \tabularnewline
68 & 543 & NA & NA & 0.971147131109875 & NA \tabularnewline
69 & 537 & NA & NA & 0.952255732394915 & NA \tabularnewline
70 & 544 & NA & NA & 0.962890130331664 & NA \tabularnewline
71 & 555 & NA & NA & 0.975446439427012 & NA \tabularnewline
72 & 561 & NA & NA & 0.991364944624473 & NA \tabularnewline
73 & 562 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=76481&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]580[/C][C]NA[/C][C]NA[/C][C]0.99948551451067[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]575[/C][C]NA[/C][C]NA[/C][C]0.994839120116967[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]558[/C][C]NA[/C][C]NA[/C][C]0.989801169879415[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]564[/C][C]NA[/C][C]NA[/C][C]1.01675939712162[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]581[/C][C]NA[/C][C]NA[/C][C]1.04390985124311[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]597[/C][C]NA[/C][C]NA[/C][C]1.05992158038544[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]587[/C][C]580.320000294003[/C][C]556.833333333333[/C][C]1.04217898885484[/C][C]1.01151089003069[/C][/ROW]
[ROW][C]8[/C][C]536[/C][C]536.275538691632[/C][C]552.208333333333[/C][C]0.971147131109875[/C][C]0.999486199403567[/C][/ROW]
[ROW][C]9[/C][C]524[/C][C]521.28065884185[/C][C]547.416666666667[/C][C]0.952255732394915[/C][C]1.0052166546217[/C][/ROW]
[ROW][C]10[/C][C]537[/C][C]522.528377393316[/C][C]542.666666666667[/C][C]0.962890130331664[/C][C]1.02769538121332[/C][/ROW]
[ROW][C]11[/C][C]536[/C][C]524.424391996947[/C][C]537.625[/C][C]0.975446439427012[/C][C]1.02207297787766[/C][/ROW]
[ROW][C]12[/C][C]533[/C][C]527.777912394454[/C][C]532.375[/C][C]0.991364944624473[/C][C]1.00989447925521[/C][/ROW]
[ROW][C]13[/C][C]528[/C][C]527.020382755522[/C][C]527.291666666667[/C][C]0.99948551451067[/C][C]1.00185878435926[/C][/ROW]
[ROW][C]14[/C][C]516[/C][C]519.720537001105[/C][C]522.416666666667[/C][C]0.994839120116967[/C][C]0.992841273845798[/C][/ROW]
[ROW][C]15[/C][C]502[/C][C]512.428313989655[/C][C]517.708333333333[/C][C]0.989801169879415[/C][C]0.979649223696359[/C][/ROW]
[ROW][C]16[/C][C]506[/C][C]522.063585447071[/C][C]513.458333333333[/C][C]1.01675939712162[/C][C]0.969230595860627[/C][/ROW]
[ROW][C]17[/C][C]518[/C][C]532.089550427375[/C][C]509.708333333333[/C][C]1.04390985124311[/C][C]0.973520339920116[/C][/ROW]
[ROW][C]18[/C][C]534[/C][C]537.247751057871[/C][C]506.875[/C][C]1.05992158038544[/C][C]0.99395483545259[/C][/ROW]
[ROW][C]19[/C][C]528[/C][C]526.691206492514[/C][C]505.375[/C][C]1.04217898885484[/C][C]1.00248493517900[/C][/ROW]
[ROW][C]20[/C][C]478[/C][C]490.267443355302[/C][C]504.833333333333[/C][C]0.971147131109875[/C][C]0.974978058360666[/C][/ROW]
[ROW][C]21[/C][C]469[/C][C]480.968499503798[/C][C]505.083333333333[/C][C]0.952255732394915[/C][C]0.975115834995128[/C][/ROW]
[ROW][C]22[/C][C]490[/C][C]487.503248902502[/C][C]506.291666666667[/C][C]0.962890130331664[/C][C]1.00512150658097[/C][/ROW]
[ROW][C]23[/C][C]493[/C][C]495.689365635493[/C][C]508.166666666667[/C][C]0.975446439427012[/C][C]0.994574493983656[/C][/ROW]
[ROW][C]24[/C][C]508[/C][C]506.050497358101[/C][C]510.458333333333[/C][C]0.991364944624473[/C][C]1.00385238756226[/C][/ROW]
[ROW][C]25[/C][C]517[/C][C]512.611133254659[/C][C]512.875[/C][C]0.99948551451067[/C][C]1.00856178584627[/C][/ROW]
[ROW][C]26[/C][C]514[/C][C]512.217791970223[/C][C]514.875[/C][C]0.994839120116967[/C][C]1.00347939501071[/C][/ROW]
[ROW][C]27[/C][C]510[/C][C]512.222105412597[/C][C]517.5[/C][C]0.989801169879415[/C][C]0.995661832261598[/C][/ROW]
[ROW][C]28[/C][C]527[/C][C]529.477456051083[/C][C]520.75[/C][C]1.01675939712162[/C][C]0.99532094138708[/C][/ROW]
[ROW][C]29[/C][C]542[/C][C]546.878273319986[/C][C]523.875[/C][C]1.04390985124311[/C][C]0.99107978217827[/C][/ROW]
[ROW][C]30[/C][C]565[/C][C]558.799489859041[/C][C]527.208333333333[/C][C]1.05992158038544[/C][C]1.01109612706075[/C][/ROW]
[ROW][C]31[/C][C]555[/C][C]553.136498334706[/C][C]530.75[/C][C]1.04217898885484[/C][C]1.00336897252469[/C][/ROW]
[ROW][C]32[/C][C]499[/C][C]518.956748186839[/C][C]534.375[/C][C]0.971147131109875[/C][C]0.961544486594374[/C][/ROW]
[ROW][C]33[/C][C]511[/C][C]512.789711894661[/C][C]538.5[/C][C]0.952255732394915[/C][C]0.99650985218083[/C][/ROW]
[ROW][C]34[/C][C]526[/C][C]523.210424568968[/C][C]543.375[/C][C]0.962890130331664[/C][C]1.00533165109111[/C][/ROW]
[ROW][C]35[/C][C]532[/C][C]535.682669652[/C][C]549.166666666667[/C][C]0.975446439427012[/C][C]0.993125277593182[/C][/ROW]
[ROW][C]36[/C][C]549[/C][C]550.16623739389[/C][C]554.958333333333[/C][C]0.991364944624473[/C][C]0.997880209081143[/C][/ROW]
[ROW][C]37[/C][C]561[/C][C]559.920114274831[/C][C]560.208333333333[/C][C]0.99948551451067[/C][C]1.00192864249317[/C][/ROW]
[ROW][C]38[/C][C]557[/C][C]563.078941986203[/C][C]566[/C][C]0.994839120116967[/C][C]0.98920410348723[/C][/ROW]
[ROW][C]39[/C][C]566[/C][C]565.836335447732[/C][C]571.666666666667[/C][C]0.989801169879415[/C][C]1.00028924362402[/C][/ROW]
[ROW][C]40[/C][C]588[/C][C]585.907602591333[/C][C]576.25[/C][C]1.01675939712162[/C][C]1.00357120713132[/C][/ROW]
[ROW][C]41[/C][C]620[/C][C]605.728691183816[/C][C]580.25[/C][C]1.04390985124311[/C][C]1.0235605627138[/C][/ROW]
[ROW][C]42[/C][C]626[/C][C]618.950039545915[/C][C]583.958333333333[/C][C]1.05992158038544[/C][C]1.01139019307480[/C][/ROW]
[ROW][C]43[/C][C]620[/C][C]611.75906645779[/C][C]587[/C][C]1.04217898885484[/C][C]1.01347088093018[/C][/ROW]
[ROW][C]44[/C][C]573[/C][C]572.976807354826[/C][C]590[/C][C]0.971147131109875[/C][C]1.00004047745891[/C][/ROW]
[ROW][C]45[/C][C]573[/C][C]564.568617343635[/C][C]592.875[/C][C]0.952255732394915[/C][C]1.01493420356242[/C][/ROW]
[ROW][C]46[/C][C]574[/C][C]572.999868391534[/C][C]595.083333333333[/C][C]0.962890130331664[/C][C]1.00174543078216[/C][/ROW]
[ROW][C]47[/C][C]580[/C][C]581.772513914927[/C][C]596.416666666667[/C][C]0.975446439427012[/C][C]0.996953252564307[/C][/ROW]
[ROW][C]48[/C][C]590[/C][C]591.720951322732[/C][C]596.875[/C][C]0.991364944624473[/C][C]0.9970916167175[/C][/ROW]
[ROW][C]49[/C][C]593[/C][C]596.734497392641[/C][C]597.041666666667[/C][C]0.99948551451067[/C][C]0.993741777274553[/C][/ROW]
[ROW][C]50[/C][C]597[/C][C]593.836051449819[/C][C]596.916666666667[/C][C]0.994839120116967[/C][C]1.00532798327494[/C][/ROW]
[ROW][C]51[/C][C]595[/C][C]590.416397833071[/C][C]596.5[/C][C]0.989801169879415[/C][C]1.00776333818598[/C][/ROW]
[ROW][C]52[/C][C]612[/C][C]606.200425558885[/C][C]596.208333333333[/C][C]1.01675939712162[/C][C]1.00956709067924[/C][/ROW]
[ROW][C]53[/C][C]628[/C][C]622.51824129131[/C][C]596.333333333333[/C][C]1.04390985124311[/C][C]1.00880578004802[/C][/ROW]
[ROW][C]54[/C][C]629[/C][C]632.199059300733[/C][C]596.458333333333[/C][C]1.05992158038544[/C][C]0.994939791109035[/C][/ROW]
[ROW][C]55[/C][C]621[/C][C]621.486070353769[/C][C]596.333333333333[/C][C]1.04217898885484[/C][C]0.9992178901878[/C][/ROW]
[ROW][C]56[/C][C]569[/C][C]578.96554799667[/C][C]596.166666666667[/C][C]0.971147131109875[/C][C]0.982787321229816[/C][/ROW]
[ROW][C]57[/C][C]567[/C][C]567.584093829552[/C][C]596.041666666667[/C][C]0.952255732394915[/C][C]0.99897091226498[/C][/ROW]
[ROW][C]58[/C][C]573[/C][C]573.842397255575[/C][C]595.958333333333[/C][C]0.962890130331664[/C][C]0.998532005896387[/C][/ROW]
[ROW][C]59[/C][C]584[/C][C]580.675136670571[/C][C]595.291666666667[/C][C]0.975446439427012[/C][C]1.00572585791858[/C][/ROW]
[ROW][C]60[/C][C]589[/C][C]588.788163361551[/C][C]593.916666666667[/C][C]0.991364944624473[/C][C]1.00035978413227[/C][/ROW]
[ROW][C]61[/C][C]591[/C][C]591.737069820087[/C][C]592.041666666667[/C][C]0.99948551451067[/C][C]0.998754396407324[/C][/ROW]
[ROW][C]62[/C][C]595[/C][C]586.789274348991[/C][C]589.833333333333[/C][C]0.994839120116967[/C][C]1.0139926307619[/C][/ROW]
[ROW][C]63[/C][C]594[/C][C]581.508187304156[/C][C]587.5[/C][C]0.989801169879415[/C][C]1.02148174861261[/C][/ROW]
[ROW][C]64[/C][C]611[/C][C]594.846612291027[/C][C]585.041666666667[/C][C]1.01675939712162[/C][C]1.02715555132231[/C][/ROW]
[ROW][C]65[/C][C]613[/C][C]608.207977080519[/C][C]582.625[/C][C]1.04390985124311[/C][C]1.00787892152037[/C][/ROW]
[ROW][C]66[/C][C]611[/C][C]615.019497018652[/C][C]580.25[/C][C]1.05992158038544[/C][C]0.993464439683397[/C][/ROW]
[ROW][C]67[/C][C]594[/C][C]602.24918318449[/C][C]577.875[/C][C]1.04217898885484[/C][C]0.986302707558902[/C][/ROW]
[ROW][C]68[/C][C]543[/C][C]NA[/C][C]NA[/C][C]0.971147131109875[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]537[/C][C]NA[/C][C]NA[/C][C]0.952255732394915[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]544[/C][C]NA[/C][C]NA[/C][C]0.962890130331664[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]555[/C][C]NA[/C][C]NA[/C][C]0.975446439427012[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]561[/C][C]NA[/C][C]NA[/C][C]0.991364944624473[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]562[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=76481&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=76481&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
tObservationsFitTrendSeasonalRandom
1580NANA0.99948551451067NA
2575NANA0.994839120116967NA
3558NANA0.989801169879415NA
4564NANA1.01675939712162NA
5581NANA1.04390985124311NA
6597NANA1.05992158038544NA
7587580.320000294003556.8333333333331.042178988854841.01151089003069
8536536.275538691632552.2083333333330.9711471311098750.999486199403567
9524521.28065884185547.4166666666670.9522557323949151.0052166546217
10537522.528377393316542.6666666666670.9628901303316641.02769538121332
11536524.424391996947537.6250.9754464394270121.02207297787766
12533527.777912394454532.3750.9913649446244731.00989447925521
13528527.020382755522527.2916666666670.999485514510671.00185878435926
14516519.720537001105522.4166666666670.9948391201169670.992841273845798
15502512.428313989655517.7083333333330.9898011698794150.979649223696359
16506522.063585447071513.4583333333331.016759397121620.969230595860627
17518532.089550427375509.7083333333331.043909851243110.973520339920116
18534537.247751057871506.8751.059921580385440.99395483545259
19528526.691206492514505.3751.042178988854841.00248493517900
20478490.267443355302504.8333333333330.9711471311098750.974978058360666
21469480.968499503798505.0833333333330.9522557323949150.975115834995128
22490487.503248902502506.2916666666670.9628901303316641.00512150658097
23493495.689365635493508.1666666666670.9754464394270120.994574493983656
24508506.050497358101510.4583333333330.9913649446244731.00385238756226
25517512.611133254659512.8750.999485514510671.00856178584627
26514512.217791970223514.8750.9948391201169671.00347939501071
27510512.222105412597517.50.9898011698794150.995661832261598
28527529.477456051083520.751.016759397121620.99532094138708
29542546.878273319986523.8751.043909851243110.99107978217827
30565558.799489859041527.2083333333331.059921580385441.01109612706075
31555553.136498334706530.751.042178988854841.00336897252469
32499518.956748186839534.3750.9711471311098750.961544486594374
33511512.789711894661538.50.9522557323949150.99650985218083
34526523.210424568968543.3750.9628901303316641.00533165109111
35532535.682669652549.1666666666670.9754464394270120.993125277593182
36549550.16623739389554.9583333333330.9913649446244730.997880209081143
37561559.920114274831560.2083333333330.999485514510671.00192864249317
38557563.0789419862035660.9948391201169670.98920410348723
39566565.836335447732571.6666666666670.9898011698794151.00028924362402
40588585.907602591333576.251.016759397121621.00357120713132
41620605.728691183816580.251.043909851243111.0235605627138
42626618.950039545915583.9583333333331.059921580385441.01139019307480
43620611.759066457795871.042178988854841.01347088093018
44573572.9768073548265900.9711471311098751.00004047745891
45573564.568617343635592.8750.9522557323949151.01493420356242
46574572.999868391534595.0833333333330.9628901303316641.00174543078216
47580581.772513914927596.4166666666670.9754464394270120.996953252564307
48590591.720951322732596.8750.9913649446244730.9970916167175
49593596.734497392641597.0416666666670.999485514510670.993741777274553
50597593.836051449819596.9166666666670.9948391201169671.00532798327494
51595590.416397833071596.50.9898011698794151.00776333818598
52612606.200425558885596.2083333333331.016759397121621.00956709067924
53628622.51824129131596.3333333333331.043909851243111.00880578004802
54629632.199059300733596.4583333333331.059921580385440.994939791109035
55621621.486070353769596.3333333333331.042178988854840.9992178901878
56569578.96554799667596.1666666666670.9711471311098750.982787321229816
57567567.584093829552596.0416666666670.9522557323949150.99897091226498
58573573.842397255575595.9583333333330.9628901303316640.998532005896387
59584580.675136670571595.2916666666670.9754464394270121.00572585791858
60589588.788163361551593.9166666666670.9913649446244731.00035978413227
61591591.737069820087592.0416666666670.999485514510670.998754396407324
62595586.789274348991589.8333333333330.9948391201169671.0139926307619
63594581.508187304156587.50.9898011698794151.02148174861261
64611594.846612291027585.0416666666671.016759397121621.02715555132231
65613608.207977080519582.6251.043909851243111.00787892152037
66611615.019497018652580.251.059921580385440.993464439683397
67594602.24918318449577.8751.042178988854840.986302707558902
68543NANA0.971147131109875NA
69537NANA0.952255732394915NA
70544NANA0.962890130331664NA
71555NANA0.975446439427012NA
72561NANA0.991364944624473NA
73562NANANANA



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')