Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 19 May 2011 13:00:11 +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/2011/May/19/t1305809803qwpw3kd7cfi59hf.htm/, Retrieved Sat, 11 May 2024 06:59:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=122010, Retrieved Sat, 11 May 2024 06:59:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Decompositie Wiss...] [2011-05-19 13:00:11] [8b50cbc1ebd04aa753862408f533fbe8] [Current]
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Dataseries X:
1,2638
1,2640
1,2261
1,1989
1,2000
1,2146
1,2266
1,2191
1,2224
1,2507
1,2997
1,3406
1,3123
1,3013
1,3185
1,2943
1,2697
1,2155
1,2041
1,2295
1,2234
1,2022
1,1789
1,1861
1,2126
1,1940
1,2028
1,2273
1,2767
1,2661
1,2681
1,2810
1,2722
1,2617
1,2888
1,3205
1,2993
1,3080
1,3246
1,3513
1,3518
1,3421
1,3726
1,3626
1,3910
1,4233
1,4683
1,4559
1,4728
1,4759
1,5520
1,5754
1,5554
1,5562
1,5759
1,4955
1,4342
1,3266
1,2744
1,3511
1,3244
1,2797
1,3050
1,3199
1,3646
1,4014
1,4092
1,4266
1,4575
1,4821
1,4908
1,4579
1,4266
1,3680
1,3570
1,3417
1,2563
1,2223
1,2811
1,2903
1,3103
1,3901
1,3654
1,3221




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122010&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122010&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122010&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 time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
11.2638NANA1.0026960805569NA
21.264NANA0.986993103631587NA
31.2261NANA1.00195032564548NA
41.1989NANA1.00677192096988NA
51.2NANA1.00176129462746NA
61.2146NANA0.991872921896452NA
71.22661.255366678113051.245895833333331.00760163452380.977085039284067
81.21911.252023191243311.249470833333331.002042751092610.973704008461205
91.22241.253935231010741.2548750.999251105497150.974850988926026
101.25071.251748068221981.26270.991326576559740.9991627163256
111.29971.265646055783121.269579166666670.996902035740021.02690637248959
121.34061.286302551145511.272520833333331.010830249258921.04221203542366
131.31231.275049225537831.271620833333331.00269608055691.02921516574896
141.30131.254583383911171.271116666666670.9869931036315871.03723675659022
151.31851.274071684504751.271591666666671.001950325645481.03487112698256
161.29431.278210215512371.26961251.006771920969881.01258774518648
171.26971.264782070542681.262558333333331.001761294627461.00388836114289
181.21551.240919814173131.25108750.9918729218964520.9795153450829
191.20411.249925629286621.240495833333331.00760163452380.963337315266686
201.22951.234387238824081.231870833333331.002042751092610.99604075717055
211.22341.221663583849451.222579166666670.999251105497151.00142135377816
221.20221.204428746300861.214966666666670.991326576559740.99814954076137
231.17891.208710488266921.212466666666670.996902035740020.97533694912364
241.18611.228023975483021.214866666666671.010830249258920.965860621355919
251.21261.222929918850551.219641666666671.00269608055690.991553139152681
261.1941.208527818212961.224454166666670.9869931036315870.987978912860737
271.20281.231029568432231.228633333333331.001950325645480.977068326256225
281.22731.241496599461011.233145833333331.006771920969880.988564930852674
291.27671.242388531602371.240204166666671.001761294627461.02761734153597
301.26611.240221370323961.250383333333330.9918729218964521.02086613752614
311.26811.269170820506031.259595833333331.00760163452380.999156283386974
321.2811.270548456604131.267958333333331.002042751092611.00822600928091
331.27221.276826408419171.277783333333330.999251105497150.99637663476518
341.26171.276853413773361.2880250.991326576559740.988132221279358
351.28881.29230487772221.296320833333330.996902035740020.997287886331918
361.32051.31672432985551.302616666666671.010830249258921.00286747199767
371.29931.313669736240621.31013751.00269608055690.989061378332624
381.3081.300749986333541.317891666666670.9869931036315871.00557371804162
391.32461.328828269801271.326241666666671.001950325645480.996818046471944
401.35131.346985322363631.3379251.006771920969881.0032032105805
411.35181.354519012514331.35213751.001761294627460.997992636139315
421.34211.354162772226811.365258333333330.9918729218964520.991092081045045
431.37261.388605200918251.378129166666671.00760163452380.988473901071618
441.36261.395198399661921.392354166666671.002042751092610.976635294543182
451.3911.407769938702021.4088250.999251105497150.988087585733303
461.42331.41525499544331.42763750.991326576559741.00568449119247
471.46831.440980355077381.445458333333330.996902035740021.01895906826652
481.45591.478705665506531.46286251.010830249258920.9845772786035
491.47281.484245051144691.480254166666671.00269608055690.992288974697364
501.47591.474826782515291.49426250.9869931036315871.00072769053114
511.5521.504528608989261.50161.001950325645481.03155233521457
521.57541.509524454121211.499370833333331.006771920969881.04363993289339
531.55541.489882007450871.48726251.001761294627461.04397528946687
541.55621.462830716428251.474816666666670.9918729218964521.06382781173732
551.57591.475397486712041.464266666666671.00760163452381.06811894028092
561.49551.452870135165431.449908333333331.002042751092611.02934182746465
571.43421.430369667871351.431441666666670.999251105497151.00267786168477
581.32661.398270266764911.410504166666670.991326576559740.948743623841238
591.27441.38759625106351.391908333333330.996902035740020.918422775373786
601.35111.392427091939581.377508333333331.010830249258920.97032010352369
611.32441.367790257188681.36411251.00269608055690.968277111961699
621.27971.336680647776991.354295833333330.9869931036315870.95737153233141
631.3051.355033445609931.352395833333331.001950325645480.963075859291867
641.31991.369054601847891.359845833333331.006771920969880.964095952212904
651.36461.377764048555081.375341666666671.001761294627460.99044535341963
661.40141.377521379537481.388808333333330.9918729218964521.01733448265648
671.40921.408140077607581.397516666666671.00760163452381.00075271090517
681.42661.408325159701241.405454166666671.002042751092611.01297629327494
691.45751.410243085188131.41130.999251105497151.03350976530799
701.48211.402107526721681.4143750.991326576559741.0570515967954
711.49081.406400315712641.410770833333330.996902035740021.06001113860998
721.45791.413945140870681.398795833333331.010830249258921.03108667929101
731.42661.389732589751531.385995833333331.00269608055691.02652842030211
741.3681.357094955137111.374979166666670.9869931036315871.00803557984032
751.3571.365825285575731.363166666666671.001950325645480.993538495978266
761.34171.362363763456441.35321.006771920969880.984832418469485
771.25631.346509096162711.344141666666671.001761294627460.933005208490767
781.22231.322422838726131.333258333333330.9918729218964520.92428833214755
791.2811NANA1.0076016345238NA
801.2903NANA1.00204275109261NA
811.3103NANA0.99925110549715NA
821.3901NANA0.99132657655974NA
831.3654NANA0.99690203574002NA
841.3221NANA1.01083024925892NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.2638 & NA & NA & 1.0026960805569 & NA \tabularnewline
2 & 1.264 & NA & NA & 0.986993103631587 & NA \tabularnewline
3 & 1.2261 & NA & NA & 1.00195032564548 & NA \tabularnewline
4 & 1.1989 & NA & NA & 1.00677192096988 & NA \tabularnewline
5 & 1.2 & NA & NA & 1.00176129462746 & NA \tabularnewline
6 & 1.2146 & NA & NA & 0.991872921896452 & NA \tabularnewline
7 & 1.2266 & 1.25536667811305 & 1.24589583333333 & 1.0076016345238 & 0.977085039284067 \tabularnewline
8 & 1.2191 & 1.25202319124331 & 1.24947083333333 & 1.00204275109261 & 0.973704008461205 \tabularnewline
9 & 1.2224 & 1.25393523101074 & 1.254875 & 0.99925110549715 & 0.974850988926026 \tabularnewline
10 & 1.2507 & 1.25174806822198 & 1.2627 & 0.99132657655974 & 0.9991627163256 \tabularnewline
11 & 1.2997 & 1.26564605578312 & 1.26957916666667 & 0.99690203574002 & 1.02690637248959 \tabularnewline
12 & 1.3406 & 1.28630255114551 & 1.27252083333333 & 1.01083024925892 & 1.04221203542366 \tabularnewline
13 & 1.3123 & 1.27504922553783 & 1.27162083333333 & 1.0026960805569 & 1.02921516574896 \tabularnewline
14 & 1.3013 & 1.25458338391117 & 1.27111666666667 & 0.986993103631587 & 1.03723675659022 \tabularnewline
15 & 1.3185 & 1.27407168450475 & 1.27159166666667 & 1.00195032564548 & 1.03487112698256 \tabularnewline
16 & 1.2943 & 1.27821021551237 & 1.2696125 & 1.00677192096988 & 1.01258774518648 \tabularnewline
17 & 1.2697 & 1.26478207054268 & 1.26255833333333 & 1.00176129462746 & 1.00388836114289 \tabularnewline
18 & 1.2155 & 1.24091981417313 & 1.2510875 & 0.991872921896452 & 0.9795153450829 \tabularnewline
19 & 1.2041 & 1.24992562928662 & 1.24049583333333 & 1.0076016345238 & 0.963337315266686 \tabularnewline
20 & 1.2295 & 1.23438723882408 & 1.23187083333333 & 1.00204275109261 & 0.99604075717055 \tabularnewline
21 & 1.2234 & 1.22166358384945 & 1.22257916666667 & 0.99925110549715 & 1.00142135377816 \tabularnewline
22 & 1.2022 & 1.20442874630086 & 1.21496666666667 & 0.99132657655974 & 0.99814954076137 \tabularnewline
23 & 1.1789 & 1.20871048826692 & 1.21246666666667 & 0.99690203574002 & 0.97533694912364 \tabularnewline
24 & 1.1861 & 1.22802397548302 & 1.21486666666667 & 1.01083024925892 & 0.965860621355919 \tabularnewline
25 & 1.2126 & 1.22292991885055 & 1.21964166666667 & 1.0026960805569 & 0.991553139152681 \tabularnewline
26 & 1.194 & 1.20852781821296 & 1.22445416666667 & 0.986993103631587 & 0.987978912860737 \tabularnewline
27 & 1.2028 & 1.23102956843223 & 1.22863333333333 & 1.00195032564548 & 0.977068326256225 \tabularnewline
28 & 1.2273 & 1.24149659946101 & 1.23314583333333 & 1.00677192096988 & 0.988564930852674 \tabularnewline
29 & 1.2767 & 1.24238853160237 & 1.24020416666667 & 1.00176129462746 & 1.02761734153597 \tabularnewline
30 & 1.2661 & 1.24022137032396 & 1.25038333333333 & 0.991872921896452 & 1.02086613752614 \tabularnewline
31 & 1.2681 & 1.26917082050603 & 1.25959583333333 & 1.0076016345238 & 0.999156283386974 \tabularnewline
32 & 1.281 & 1.27054845660413 & 1.26795833333333 & 1.00204275109261 & 1.00822600928091 \tabularnewline
33 & 1.2722 & 1.27682640841917 & 1.27778333333333 & 0.99925110549715 & 0.99637663476518 \tabularnewline
34 & 1.2617 & 1.27685341377336 & 1.288025 & 0.99132657655974 & 0.988132221279358 \tabularnewline
35 & 1.2888 & 1.2923048777222 & 1.29632083333333 & 0.99690203574002 & 0.997287886331918 \tabularnewline
36 & 1.3205 & 1.3167243298555 & 1.30261666666667 & 1.01083024925892 & 1.00286747199767 \tabularnewline
37 & 1.2993 & 1.31366973624062 & 1.3101375 & 1.0026960805569 & 0.989061378332624 \tabularnewline
38 & 1.308 & 1.30074998633354 & 1.31789166666667 & 0.986993103631587 & 1.00557371804162 \tabularnewline
39 & 1.3246 & 1.32882826980127 & 1.32624166666667 & 1.00195032564548 & 0.996818046471944 \tabularnewline
40 & 1.3513 & 1.34698532236363 & 1.337925 & 1.00677192096988 & 1.0032032105805 \tabularnewline
41 & 1.3518 & 1.35451901251433 & 1.3521375 & 1.00176129462746 & 0.997992636139315 \tabularnewline
42 & 1.3421 & 1.35416277222681 & 1.36525833333333 & 0.991872921896452 & 0.991092081045045 \tabularnewline
43 & 1.3726 & 1.38860520091825 & 1.37812916666667 & 1.0076016345238 & 0.988473901071618 \tabularnewline
44 & 1.3626 & 1.39519839966192 & 1.39235416666667 & 1.00204275109261 & 0.976635294543182 \tabularnewline
45 & 1.391 & 1.40776993870202 & 1.408825 & 0.99925110549715 & 0.988087585733303 \tabularnewline
46 & 1.4233 & 1.4152549954433 & 1.4276375 & 0.99132657655974 & 1.00568449119247 \tabularnewline
47 & 1.4683 & 1.44098035507738 & 1.44545833333333 & 0.99690203574002 & 1.01895906826652 \tabularnewline
48 & 1.4559 & 1.47870566550653 & 1.4628625 & 1.01083024925892 & 0.9845772786035 \tabularnewline
49 & 1.4728 & 1.48424505114469 & 1.48025416666667 & 1.0026960805569 & 0.992288974697364 \tabularnewline
50 & 1.4759 & 1.47482678251529 & 1.4942625 & 0.986993103631587 & 1.00072769053114 \tabularnewline
51 & 1.552 & 1.50452860898926 & 1.5016 & 1.00195032564548 & 1.03155233521457 \tabularnewline
52 & 1.5754 & 1.50952445412121 & 1.49937083333333 & 1.00677192096988 & 1.04363993289339 \tabularnewline
53 & 1.5554 & 1.48988200745087 & 1.4872625 & 1.00176129462746 & 1.04397528946687 \tabularnewline
54 & 1.5562 & 1.46283071642825 & 1.47481666666667 & 0.991872921896452 & 1.06382781173732 \tabularnewline
55 & 1.5759 & 1.47539748671204 & 1.46426666666667 & 1.0076016345238 & 1.06811894028092 \tabularnewline
56 & 1.4955 & 1.45287013516543 & 1.44990833333333 & 1.00204275109261 & 1.02934182746465 \tabularnewline
57 & 1.4342 & 1.43036966787135 & 1.43144166666667 & 0.99925110549715 & 1.00267786168477 \tabularnewline
58 & 1.3266 & 1.39827026676491 & 1.41050416666667 & 0.99132657655974 & 0.948743623841238 \tabularnewline
59 & 1.2744 & 1.3875962510635 & 1.39190833333333 & 0.99690203574002 & 0.918422775373786 \tabularnewline
60 & 1.3511 & 1.39242709193958 & 1.37750833333333 & 1.01083024925892 & 0.97032010352369 \tabularnewline
61 & 1.3244 & 1.36779025718868 & 1.3641125 & 1.0026960805569 & 0.968277111961699 \tabularnewline
62 & 1.2797 & 1.33668064777699 & 1.35429583333333 & 0.986993103631587 & 0.95737153233141 \tabularnewline
63 & 1.305 & 1.35503344560993 & 1.35239583333333 & 1.00195032564548 & 0.963075859291867 \tabularnewline
64 & 1.3199 & 1.36905460184789 & 1.35984583333333 & 1.00677192096988 & 0.964095952212904 \tabularnewline
65 & 1.3646 & 1.37776404855508 & 1.37534166666667 & 1.00176129462746 & 0.99044535341963 \tabularnewline
66 & 1.4014 & 1.37752137953748 & 1.38880833333333 & 0.991872921896452 & 1.01733448265648 \tabularnewline
67 & 1.4092 & 1.40814007760758 & 1.39751666666667 & 1.0076016345238 & 1.00075271090517 \tabularnewline
68 & 1.4266 & 1.40832515970124 & 1.40545416666667 & 1.00204275109261 & 1.01297629327494 \tabularnewline
69 & 1.4575 & 1.41024308518813 & 1.4113 & 0.99925110549715 & 1.03350976530799 \tabularnewline
70 & 1.4821 & 1.40210752672168 & 1.414375 & 0.99132657655974 & 1.0570515967954 \tabularnewline
71 & 1.4908 & 1.40640031571264 & 1.41077083333333 & 0.99690203574002 & 1.06001113860998 \tabularnewline
72 & 1.4579 & 1.41394514087068 & 1.39879583333333 & 1.01083024925892 & 1.03108667929101 \tabularnewline
73 & 1.4266 & 1.38973258975153 & 1.38599583333333 & 1.0026960805569 & 1.02652842030211 \tabularnewline
74 & 1.368 & 1.35709495513711 & 1.37497916666667 & 0.986993103631587 & 1.00803557984032 \tabularnewline
75 & 1.357 & 1.36582528557573 & 1.36316666666667 & 1.00195032564548 & 0.993538495978266 \tabularnewline
76 & 1.3417 & 1.36236376345644 & 1.3532 & 1.00677192096988 & 0.984832418469485 \tabularnewline
77 & 1.2563 & 1.34650909616271 & 1.34414166666667 & 1.00176129462746 & 0.933005208490767 \tabularnewline
78 & 1.2223 & 1.32242283872613 & 1.33325833333333 & 0.991872921896452 & 0.92428833214755 \tabularnewline
79 & 1.2811 & NA & NA & 1.0076016345238 & NA \tabularnewline
80 & 1.2903 & NA & NA & 1.00204275109261 & NA \tabularnewline
81 & 1.3103 & NA & NA & 0.99925110549715 & NA \tabularnewline
82 & 1.3901 & NA & NA & 0.99132657655974 & NA \tabularnewline
83 & 1.3654 & NA & NA & 0.99690203574002 & NA \tabularnewline
84 & 1.3221 & NA & NA & 1.01083024925892 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122010&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]1.2638[/C][C]NA[/C][C]NA[/C][C]1.0026960805569[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.264[/C][C]NA[/C][C]NA[/C][C]0.986993103631587[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.2261[/C][C]NA[/C][C]NA[/C][C]1.00195032564548[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.1989[/C][C]NA[/C][C]NA[/C][C]1.00677192096988[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.2[/C][C]NA[/C][C]NA[/C][C]1.00176129462746[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.2146[/C][C]NA[/C][C]NA[/C][C]0.991872921896452[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.2266[/C][C]1.25536667811305[/C][C]1.24589583333333[/C][C]1.0076016345238[/C][C]0.977085039284067[/C][/ROW]
[ROW][C]8[/C][C]1.2191[/C][C]1.25202319124331[/C][C]1.24947083333333[/C][C]1.00204275109261[/C][C]0.973704008461205[/C][/ROW]
[ROW][C]9[/C][C]1.2224[/C][C]1.25393523101074[/C][C]1.254875[/C][C]0.99925110549715[/C][C]0.974850988926026[/C][/ROW]
[ROW][C]10[/C][C]1.2507[/C][C]1.25174806822198[/C][C]1.2627[/C][C]0.99132657655974[/C][C]0.9991627163256[/C][/ROW]
[ROW][C]11[/C][C]1.2997[/C][C]1.26564605578312[/C][C]1.26957916666667[/C][C]0.99690203574002[/C][C]1.02690637248959[/C][/ROW]
[ROW][C]12[/C][C]1.3406[/C][C]1.28630255114551[/C][C]1.27252083333333[/C][C]1.01083024925892[/C][C]1.04221203542366[/C][/ROW]
[ROW][C]13[/C][C]1.3123[/C][C]1.27504922553783[/C][C]1.27162083333333[/C][C]1.0026960805569[/C][C]1.02921516574896[/C][/ROW]
[ROW][C]14[/C][C]1.3013[/C][C]1.25458338391117[/C][C]1.27111666666667[/C][C]0.986993103631587[/C][C]1.03723675659022[/C][/ROW]
[ROW][C]15[/C][C]1.3185[/C][C]1.27407168450475[/C][C]1.27159166666667[/C][C]1.00195032564548[/C][C]1.03487112698256[/C][/ROW]
[ROW][C]16[/C][C]1.2943[/C][C]1.27821021551237[/C][C]1.2696125[/C][C]1.00677192096988[/C][C]1.01258774518648[/C][/ROW]
[ROW][C]17[/C][C]1.2697[/C][C]1.26478207054268[/C][C]1.26255833333333[/C][C]1.00176129462746[/C][C]1.00388836114289[/C][/ROW]
[ROW][C]18[/C][C]1.2155[/C][C]1.24091981417313[/C][C]1.2510875[/C][C]0.991872921896452[/C][C]0.9795153450829[/C][/ROW]
[ROW][C]19[/C][C]1.2041[/C][C]1.24992562928662[/C][C]1.24049583333333[/C][C]1.0076016345238[/C][C]0.963337315266686[/C][/ROW]
[ROW][C]20[/C][C]1.2295[/C][C]1.23438723882408[/C][C]1.23187083333333[/C][C]1.00204275109261[/C][C]0.99604075717055[/C][/ROW]
[ROW][C]21[/C][C]1.2234[/C][C]1.22166358384945[/C][C]1.22257916666667[/C][C]0.99925110549715[/C][C]1.00142135377816[/C][/ROW]
[ROW][C]22[/C][C]1.2022[/C][C]1.20442874630086[/C][C]1.21496666666667[/C][C]0.99132657655974[/C][C]0.99814954076137[/C][/ROW]
[ROW][C]23[/C][C]1.1789[/C][C]1.20871048826692[/C][C]1.21246666666667[/C][C]0.99690203574002[/C][C]0.97533694912364[/C][/ROW]
[ROW][C]24[/C][C]1.1861[/C][C]1.22802397548302[/C][C]1.21486666666667[/C][C]1.01083024925892[/C][C]0.965860621355919[/C][/ROW]
[ROW][C]25[/C][C]1.2126[/C][C]1.22292991885055[/C][C]1.21964166666667[/C][C]1.0026960805569[/C][C]0.991553139152681[/C][/ROW]
[ROW][C]26[/C][C]1.194[/C][C]1.20852781821296[/C][C]1.22445416666667[/C][C]0.986993103631587[/C][C]0.987978912860737[/C][/ROW]
[ROW][C]27[/C][C]1.2028[/C][C]1.23102956843223[/C][C]1.22863333333333[/C][C]1.00195032564548[/C][C]0.977068326256225[/C][/ROW]
[ROW][C]28[/C][C]1.2273[/C][C]1.24149659946101[/C][C]1.23314583333333[/C][C]1.00677192096988[/C][C]0.988564930852674[/C][/ROW]
[ROW][C]29[/C][C]1.2767[/C][C]1.24238853160237[/C][C]1.24020416666667[/C][C]1.00176129462746[/C][C]1.02761734153597[/C][/ROW]
[ROW][C]30[/C][C]1.2661[/C][C]1.24022137032396[/C][C]1.25038333333333[/C][C]0.991872921896452[/C][C]1.02086613752614[/C][/ROW]
[ROW][C]31[/C][C]1.2681[/C][C]1.26917082050603[/C][C]1.25959583333333[/C][C]1.0076016345238[/C][C]0.999156283386974[/C][/ROW]
[ROW][C]32[/C][C]1.281[/C][C]1.27054845660413[/C][C]1.26795833333333[/C][C]1.00204275109261[/C][C]1.00822600928091[/C][/ROW]
[ROW][C]33[/C][C]1.2722[/C][C]1.27682640841917[/C][C]1.27778333333333[/C][C]0.99925110549715[/C][C]0.99637663476518[/C][/ROW]
[ROW][C]34[/C][C]1.2617[/C][C]1.27685341377336[/C][C]1.288025[/C][C]0.99132657655974[/C][C]0.988132221279358[/C][/ROW]
[ROW][C]35[/C][C]1.2888[/C][C]1.2923048777222[/C][C]1.29632083333333[/C][C]0.99690203574002[/C][C]0.997287886331918[/C][/ROW]
[ROW][C]36[/C][C]1.3205[/C][C]1.3167243298555[/C][C]1.30261666666667[/C][C]1.01083024925892[/C][C]1.00286747199767[/C][/ROW]
[ROW][C]37[/C][C]1.2993[/C][C]1.31366973624062[/C][C]1.3101375[/C][C]1.0026960805569[/C][C]0.989061378332624[/C][/ROW]
[ROW][C]38[/C][C]1.308[/C][C]1.30074998633354[/C][C]1.31789166666667[/C][C]0.986993103631587[/C][C]1.00557371804162[/C][/ROW]
[ROW][C]39[/C][C]1.3246[/C][C]1.32882826980127[/C][C]1.32624166666667[/C][C]1.00195032564548[/C][C]0.996818046471944[/C][/ROW]
[ROW][C]40[/C][C]1.3513[/C][C]1.34698532236363[/C][C]1.337925[/C][C]1.00677192096988[/C][C]1.0032032105805[/C][/ROW]
[ROW][C]41[/C][C]1.3518[/C][C]1.35451901251433[/C][C]1.3521375[/C][C]1.00176129462746[/C][C]0.997992636139315[/C][/ROW]
[ROW][C]42[/C][C]1.3421[/C][C]1.35416277222681[/C][C]1.36525833333333[/C][C]0.991872921896452[/C][C]0.991092081045045[/C][/ROW]
[ROW][C]43[/C][C]1.3726[/C][C]1.38860520091825[/C][C]1.37812916666667[/C][C]1.0076016345238[/C][C]0.988473901071618[/C][/ROW]
[ROW][C]44[/C][C]1.3626[/C][C]1.39519839966192[/C][C]1.39235416666667[/C][C]1.00204275109261[/C][C]0.976635294543182[/C][/ROW]
[ROW][C]45[/C][C]1.391[/C][C]1.40776993870202[/C][C]1.408825[/C][C]0.99925110549715[/C][C]0.988087585733303[/C][/ROW]
[ROW][C]46[/C][C]1.4233[/C][C]1.4152549954433[/C][C]1.4276375[/C][C]0.99132657655974[/C][C]1.00568449119247[/C][/ROW]
[ROW][C]47[/C][C]1.4683[/C][C]1.44098035507738[/C][C]1.44545833333333[/C][C]0.99690203574002[/C][C]1.01895906826652[/C][/ROW]
[ROW][C]48[/C][C]1.4559[/C][C]1.47870566550653[/C][C]1.4628625[/C][C]1.01083024925892[/C][C]0.9845772786035[/C][/ROW]
[ROW][C]49[/C][C]1.4728[/C][C]1.48424505114469[/C][C]1.48025416666667[/C][C]1.0026960805569[/C][C]0.992288974697364[/C][/ROW]
[ROW][C]50[/C][C]1.4759[/C][C]1.47482678251529[/C][C]1.4942625[/C][C]0.986993103631587[/C][C]1.00072769053114[/C][/ROW]
[ROW][C]51[/C][C]1.552[/C][C]1.50452860898926[/C][C]1.5016[/C][C]1.00195032564548[/C][C]1.03155233521457[/C][/ROW]
[ROW][C]52[/C][C]1.5754[/C][C]1.50952445412121[/C][C]1.49937083333333[/C][C]1.00677192096988[/C][C]1.04363993289339[/C][/ROW]
[ROW][C]53[/C][C]1.5554[/C][C]1.48988200745087[/C][C]1.4872625[/C][C]1.00176129462746[/C][C]1.04397528946687[/C][/ROW]
[ROW][C]54[/C][C]1.5562[/C][C]1.46283071642825[/C][C]1.47481666666667[/C][C]0.991872921896452[/C][C]1.06382781173732[/C][/ROW]
[ROW][C]55[/C][C]1.5759[/C][C]1.47539748671204[/C][C]1.46426666666667[/C][C]1.0076016345238[/C][C]1.06811894028092[/C][/ROW]
[ROW][C]56[/C][C]1.4955[/C][C]1.45287013516543[/C][C]1.44990833333333[/C][C]1.00204275109261[/C][C]1.02934182746465[/C][/ROW]
[ROW][C]57[/C][C]1.4342[/C][C]1.43036966787135[/C][C]1.43144166666667[/C][C]0.99925110549715[/C][C]1.00267786168477[/C][/ROW]
[ROW][C]58[/C][C]1.3266[/C][C]1.39827026676491[/C][C]1.41050416666667[/C][C]0.99132657655974[/C][C]0.948743623841238[/C][/ROW]
[ROW][C]59[/C][C]1.2744[/C][C]1.3875962510635[/C][C]1.39190833333333[/C][C]0.99690203574002[/C][C]0.918422775373786[/C][/ROW]
[ROW][C]60[/C][C]1.3511[/C][C]1.39242709193958[/C][C]1.37750833333333[/C][C]1.01083024925892[/C][C]0.97032010352369[/C][/ROW]
[ROW][C]61[/C][C]1.3244[/C][C]1.36779025718868[/C][C]1.3641125[/C][C]1.0026960805569[/C][C]0.968277111961699[/C][/ROW]
[ROW][C]62[/C][C]1.2797[/C][C]1.33668064777699[/C][C]1.35429583333333[/C][C]0.986993103631587[/C][C]0.95737153233141[/C][/ROW]
[ROW][C]63[/C][C]1.305[/C][C]1.35503344560993[/C][C]1.35239583333333[/C][C]1.00195032564548[/C][C]0.963075859291867[/C][/ROW]
[ROW][C]64[/C][C]1.3199[/C][C]1.36905460184789[/C][C]1.35984583333333[/C][C]1.00677192096988[/C][C]0.964095952212904[/C][/ROW]
[ROW][C]65[/C][C]1.3646[/C][C]1.37776404855508[/C][C]1.37534166666667[/C][C]1.00176129462746[/C][C]0.99044535341963[/C][/ROW]
[ROW][C]66[/C][C]1.4014[/C][C]1.37752137953748[/C][C]1.38880833333333[/C][C]0.991872921896452[/C][C]1.01733448265648[/C][/ROW]
[ROW][C]67[/C][C]1.4092[/C][C]1.40814007760758[/C][C]1.39751666666667[/C][C]1.0076016345238[/C][C]1.00075271090517[/C][/ROW]
[ROW][C]68[/C][C]1.4266[/C][C]1.40832515970124[/C][C]1.40545416666667[/C][C]1.00204275109261[/C][C]1.01297629327494[/C][/ROW]
[ROW][C]69[/C][C]1.4575[/C][C]1.41024308518813[/C][C]1.4113[/C][C]0.99925110549715[/C][C]1.03350976530799[/C][/ROW]
[ROW][C]70[/C][C]1.4821[/C][C]1.40210752672168[/C][C]1.414375[/C][C]0.99132657655974[/C][C]1.0570515967954[/C][/ROW]
[ROW][C]71[/C][C]1.4908[/C][C]1.40640031571264[/C][C]1.41077083333333[/C][C]0.99690203574002[/C][C]1.06001113860998[/C][/ROW]
[ROW][C]72[/C][C]1.4579[/C][C]1.41394514087068[/C][C]1.39879583333333[/C][C]1.01083024925892[/C][C]1.03108667929101[/C][/ROW]
[ROW][C]73[/C][C]1.4266[/C][C]1.38973258975153[/C][C]1.38599583333333[/C][C]1.0026960805569[/C][C]1.02652842030211[/C][/ROW]
[ROW][C]74[/C][C]1.368[/C][C]1.35709495513711[/C][C]1.37497916666667[/C][C]0.986993103631587[/C][C]1.00803557984032[/C][/ROW]
[ROW][C]75[/C][C]1.357[/C][C]1.36582528557573[/C][C]1.36316666666667[/C][C]1.00195032564548[/C][C]0.993538495978266[/C][/ROW]
[ROW][C]76[/C][C]1.3417[/C][C]1.36236376345644[/C][C]1.3532[/C][C]1.00677192096988[/C][C]0.984832418469485[/C][/ROW]
[ROW][C]77[/C][C]1.2563[/C][C]1.34650909616271[/C][C]1.34414166666667[/C][C]1.00176129462746[/C][C]0.933005208490767[/C][/ROW]
[ROW][C]78[/C][C]1.2223[/C][C]1.32242283872613[/C][C]1.33325833333333[/C][C]0.991872921896452[/C][C]0.92428833214755[/C][/ROW]
[ROW][C]79[/C][C]1.2811[/C][C]NA[/C][C]NA[/C][C]1.0076016345238[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.2903[/C][C]NA[/C][C]NA[/C][C]1.00204275109261[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.3103[/C][C]NA[/C][C]NA[/C][C]0.99925110549715[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.3901[/C][C]NA[/C][C]NA[/C][C]0.99132657655974[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.3654[/C][C]NA[/C][C]NA[/C][C]0.99690203574002[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.3221[/C][C]NA[/C][C]NA[/C][C]1.01083024925892[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122010&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122010&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
11.2638NANA1.0026960805569NA
21.264NANA0.986993103631587NA
31.2261NANA1.00195032564548NA
41.1989NANA1.00677192096988NA
51.2NANA1.00176129462746NA
61.2146NANA0.991872921896452NA
71.22661.255366678113051.245895833333331.00760163452380.977085039284067
81.21911.252023191243311.249470833333331.002042751092610.973704008461205
91.22241.253935231010741.2548750.999251105497150.974850988926026
101.25071.251748068221981.26270.991326576559740.9991627163256
111.29971.265646055783121.269579166666670.996902035740021.02690637248959
121.34061.286302551145511.272520833333331.010830249258921.04221203542366
131.31231.275049225537831.271620833333331.00269608055691.02921516574896
141.30131.254583383911171.271116666666670.9869931036315871.03723675659022
151.31851.274071684504751.271591666666671.001950325645481.03487112698256
161.29431.278210215512371.26961251.006771920969881.01258774518648
171.26971.264782070542681.262558333333331.001761294627461.00388836114289
181.21551.240919814173131.25108750.9918729218964520.9795153450829
191.20411.249925629286621.240495833333331.00760163452380.963337315266686
201.22951.234387238824081.231870833333331.002042751092610.99604075717055
211.22341.221663583849451.222579166666670.999251105497151.00142135377816
221.20221.204428746300861.214966666666670.991326576559740.99814954076137
231.17891.208710488266921.212466666666670.996902035740020.97533694912364
241.18611.228023975483021.214866666666671.010830249258920.965860621355919
251.21261.222929918850551.219641666666671.00269608055690.991553139152681
261.1941.208527818212961.224454166666670.9869931036315870.987978912860737
271.20281.231029568432231.228633333333331.001950325645480.977068326256225
281.22731.241496599461011.233145833333331.006771920969880.988564930852674
291.27671.242388531602371.240204166666671.001761294627461.02761734153597
301.26611.240221370323961.250383333333330.9918729218964521.02086613752614
311.26811.269170820506031.259595833333331.00760163452380.999156283386974
321.2811.270548456604131.267958333333331.002042751092611.00822600928091
331.27221.276826408419171.277783333333330.999251105497150.99637663476518
341.26171.276853413773361.2880250.991326576559740.988132221279358
351.28881.29230487772221.296320833333330.996902035740020.997287886331918
361.32051.31672432985551.302616666666671.010830249258921.00286747199767
371.29931.313669736240621.31013751.00269608055690.989061378332624
381.3081.300749986333541.317891666666670.9869931036315871.00557371804162
391.32461.328828269801271.326241666666671.001950325645480.996818046471944
401.35131.346985322363631.3379251.006771920969881.0032032105805
411.35181.354519012514331.35213751.001761294627460.997992636139315
421.34211.354162772226811.365258333333330.9918729218964520.991092081045045
431.37261.388605200918251.378129166666671.00760163452380.988473901071618
441.36261.395198399661921.392354166666671.002042751092610.976635294543182
451.3911.407769938702021.4088250.999251105497150.988087585733303
461.42331.41525499544331.42763750.991326576559741.00568449119247
471.46831.440980355077381.445458333333330.996902035740021.01895906826652
481.45591.478705665506531.46286251.010830249258920.9845772786035
491.47281.484245051144691.480254166666671.00269608055690.992288974697364
501.47591.474826782515291.49426250.9869931036315871.00072769053114
511.5521.504528608989261.50161.001950325645481.03155233521457
521.57541.509524454121211.499370833333331.006771920969881.04363993289339
531.55541.489882007450871.48726251.001761294627461.04397528946687
541.55621.462830716428251.474816666666670.9918729218964521.06382781173732
551.57591.475397486712041.464266666666671.00760163452381.06811894028092
561.49551.452870135165431.449908333333331.002042751092611.02934182746465
571.43421.430369667871351.431441666666670.999251105497151.00267786168477
581.32661.398270266764911.410504166666670.991326576559740.948743623841238
591.27441.38759625106351.391908333333330.996902035740020.918422775373786
601.35111.392427091939581.377508333333331.010830249258920.97032010352369
611.32441.367790257188681.36411251.00269608055690.968277111961699
621.27971.336680647776991.354295833333330.9869931036315870.95737153233141
631.3051.355033445609931.352395833333331.001950325645480.963075859291867
641.31991.369054601847891.359845833333331.006771920969880.964095952212904
651.36461.377764048555081.375341666666671.001761294627460.99044535341963
661.40141.377521379537481.388808333333330.9918729218964521.01733448265648
671.40921.408140077607581.397516666666671.00760163452381.00075271090517
681.42661.408325159701241.405454166666671.002042751092611.01297629327494
691.45751.410243085188131.41130.999251105497151.03350976530799
701.48211.402107526721681.4143750.991326576559741.0570515967954
711.49081.406400315712641.410770833333330.996902035740021.06001113860998
721.45791.413945140870681.398795833333331.010830249258921.03108667929101
731.42661.389732589751531.385995833333331.00269608055691.02652842030211
741.3681.357094955137111.374979166666670.9869931036315871.00803557984032
751.3571.365825285575731.363166666666671.001950325645480.993538495978266
761.34171.362363763456441.35321.006771920969880.984832418469485
771.25631.346509096162711.344141666666671.001761294627460.933005208490767
781.22231.322422838726131.333258333333330.9918729218964520.92428833214755
791.2811NANA1.0076016345238NA
801.2903NANA1.00204275109261NA
811.3103NANA0.99925110549715NA
821.3901NANA0.99132657655974NA
831.3654NANA0.99690203574002NA
841.3221NANA1.01083024925892NA



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')