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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decomposeloess.wasp
Title produced by softwareDecomposition by Loess
Date of computationFri, 11 Dec 2009 09:44:09 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/11/t12605499008i5ctgndcddg58c.htm/, Retrieved Mon, 29 Apr 2024 03:31:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=66524, Retrieved Mon, 29 Apr 2024 03:31:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121

Tree of Dependent Computations

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   [Decomposition by Loess] [] [2009-11-27 15:00:29] [b98453cac15ba1066b407e146608df68]
-    D    [Decomposition by Loess] [Seizoenale decomp...] [2009-12-01 19:51:41] [d46757a0a8c9b00540ab7e7e0c34bfc4]
-    D      [Decomposition by Loess] [seizoenale decomp...] [2009-12-04 19:15:18] [4f1a20f787b3465111b61213cdeef1a9]
-    D        [Decomposition by Loess] [Seizoenale decomp...] [2009-12-11 15:57:17] [4f1a20f787b3465111b61213cdeef1a9]
-    D            [Decomposition by Loess] [Seizoenale decomp...] [2009-12-11 16:44:09] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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=66524&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=66524&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66524&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal10910110
Trend1912
Low-pass1312

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1091 & 0 & 110 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66524&T=1

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Parameters[/C][/ROW]
[ROW][C]Component[/C][C]Window[/C][C]Degree[/C][C]Jump[/C][/ROW]
[ROW][C]Seasonal[/C][C]1091[/C][C]0[/C][C]110[/C][/ROW]
[ROW][C]Trend[/C][C]19[/C][C]1[/C][C]2[/C][/ROW]
[ROW][C]Low-pass[/C][C]13[/C][C]1[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66524&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66524&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal10910110
Trend1912
Low-pass1312






Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
12179022279.4514224485-4969.1044250470126269.6530025985489.451422448474
21325311506.5592112009-11364.748377824926364.189166624-1746.44078879906
33770241206.80797222237738.4666971282326458.72533064953504.80797222231
43036429294.01236450754879.487155239926554.5004802526-1069.98763549248
53260930602.21616794537965.5082021989726650.2756298557-2006.78383205466
63021228463.2640564465219.7579495798526740.9779939742-1748.73594355401
72996532116.0881315082982.23151039914726831.68035809262151.08813150824
82835228309.81638993071469.0239738706426925.1596361987-42.1836100693399
92581427830.2136858763-3220.8526001811327018.63891430482016.21368587635
102241422971.1822369874-5311.6816780917927168.4994411044557.182236987392
112050617076.8184255081-3383.1783934121127318.359967904-3429.1815744919
122880630201.4561371599-4.9096438419578827415.45350668211395.45613715985
132222821912.5573795868-4969.1044250470127512.5470454602-315.442620413185
141397111935.5654279328-11364.748377824927371.1829498922-2035.43457206722
153684538721.71444854767738.4666971282327229.81885432411876.71444854765
163533838811.61080302724879.487155239926984.90204173293473.61080302721
173502235338.50656865947965.5082021989726739.9852291417316.506568659363
183477737906.21873497615219.7579495798526428.02331544403129.21873497610
192688726675.7070878544982.23151039914726116.0614017464-211.29291214556
202397020788.79506040751469.0239738706425682.1809657219-3181.20493959254
212278023532.5520704838-3220.8526001811325248.3005296974752.552070483751
221735115284.5387127359-5311.6816780917924729.1429653559-2066.46128726415
232138221937.1929923976-3383.1783934121124209.9854010145555.19299239762
242456125358.7008577858-4.9096438419578823768.2087860561797.700857785814
251740916460.6722539492-4969.1044250470123326.4321710978-948.32774605079
261151411291.8903959135-11364.748377824923100.8579819114-222.109604086487
273151432414.24951014677738.4666971282322875.2837927251900.249510146718
282707126438.99556801384879.487155239922823.5172767463-632.004431986214
292946228186.74103703357965.5082021989722771.7507607676-1275.25896296654
302610524157.2715015535219.7579495798522832.9705488672-1947.72849844701
312239720917.5781526341982.23151039914722894.1903369667-1479.42184736589
322384323198.00687008801469.0239738706423018.9691560413-644.993129911978
332170523487.1046250652-3220.8526001811323143.74797511591782.10462506520
341808918103.4907883817-5311.6816780917923386.190889710114.4907883817323
352076421282.5445891079-3383.1783934121123628.6338043042518.544589107922
362531626743.1277767362-4.9096438419578823893.78186710581427.12777673619
371770416218.1744951397-4969.1044250470124158.9299299074-1485.82550486034
381554818253.3242094717-11364.748377824924207.42416835332705.32420947166
392802924063.61489607267738.4666971282324255.9184067992-3965.38510392744
402938329747.06338968384879.487155239924139.4494550763364.063389683757
413643840887.51129444767965.5082021989724022.98050335354449.51129444755
423203434919.06996391745219.7579495798523929.17208650272885.06996391742
432267920540.4048199489982.23151039914723835.363669652-2138.59518005112
442431923434.20919952911469.0239738706423734.7668266003-884.790800470924
451800415594.6826166325-3220.8526001811323634.1699835486-2409.31738336746
461753716981.8984633569-5311.6816780917923403.7832147349-555.101536643098
472036620941.7819474909-3383.1783934121123173.3964459212575.781947490934
482278222632.3387146269-4.9096438419578822936.5709292150-149.661285373069
491916920607.3590125381-4969.1044250470122699.74541250891438.35901253813
501380716319.0215261833-11364.748377824922659.72685164162512.02152618329
512974329127.82501209747738.4666971282322619.7082907744-615.174987902643
522559123704.71964928564879.487155239922597.7931954745-1886.28035071444
532909627650.61369762647965.5082021989722575.8781001747-1445.38630237363
542648225257.65299311325219.7579495798522486.589057307-1224.34700688684
552240521430.4684751616982.23151039914722397.3000144393-974.531524838447
562704430219.67890899891469.0239738706422399.29711713043175.67890899895
571797016759.5583803596-3220.8526001811322401.2942198215-1210.44161964040
581873020174.2804751038-5311.6816780917922597.4012029881444.28047510380
591968419957.6702072577-3383.1783934121122793.5081861544273.670207257663
601978516578.9439782000-4.9096438419578822995.9656656419-3206.05602179998
611847918728.6812799176-4969.1044250470123198.4231451294249.681279917582
62106989503.116288489-11364.748377824923257.6320893359-1194.883711511
633195632856.69226932937738.4666971282323316.8410335424900.692269329324
642950630838.58051478194879.487155239923293.93232997821332.5805147819
653450637775.46817138717965.5082021989723271.02362641403269.46817138708
662716525915.88887637615219.7579495798523194.3531740441-1249.11112362394
672673629372.0857679266982.23151039914723117.68272167422636.08576792664
682369122956.37670072391469.0239738706422956.5993254054-734.623299276063
691815716739.3366710445-3220.8526001811322795.5159291366-1417.66332895551
701732817385.6075022776-5311.6816780917922582.074175814257.6075022776095
711820517424.5459709204-3383.1783934121122368.6324224917-780.454029079614
722099519750.2919950398-4.9096438419578822244.6176488021-1244.70800496018
731738217612.5015499345-4969.1044250470122120.6028751126230.501549934452
7493677918.7687710315-11364.748377824922179.9796067934-1448.2312289685
753112432270.17696439757738.4666971282322239.35633847431146.17696439745
762655125793.09304680584879.487155239922429.4197979543-757.906953194215
773065130717.00854036677965.5082021989722619.483257434366.0085403667144
782585923642.15889122855219.7579495798522856.0831591916-2216.84110877147
792510026125.0854286519982.23151039914723092.68306094891025.08542865194
802577826769.67071723531469.0239738706423317.3053088940991.670717235316
812041820514.9250433420-3220.8526001811323541.927556839296.925043341951
821868818963.0548139022-5311.6816780917923724.6268641896275.054813902181
832042420323.8522218721-3383.1783934121123907.3261715400-100.147778127925
842477625489.6547470625-4.9096438419578824067.2548967794713.654747062541
851981420369.9208030282-4969.1044250470124227.1836220188555.92080302821
861273812534.6599947769-11364.748377824924306.0883830481-203.340005223126
873156631008.54015879447738.4666971282324384.9931440773-557.459841205557
883011130976.50217630054879.487155239924366.0106684596865.502176300459
893001927725.46360495917965.5082021989724347.0281928420-2293.53639504093
903193434444.74837967175219.7579495798524203.49367074852510.74837967168
912582626609.8093409459982.23151039914724059.959148655783.809340945878
922683528428.47162529581469.0239738706423772.50440083361593.47162529575
932020520145.8029471689-3220.8526001811323485.0496530123-59.1970528311176
941778917818.7926350153-5311.6816780917923070.889043076529.7926350152593
952052021766.4499602713-3383.1783934121122656.72843314081246.44996027130
962251822827.4322232011-4.9096438419578822213.4774206409309.432223201085
971557214342.8780169061-4969.1044250470121770.2264081409-1229.12198309393
981150912936.1894583820-11364.748377824921446.55891944301427.18945838198
992544722032.64187212687738.4666971282321122.8914307450-3414.3581278732
1002409022189.02715690964879.487155239921111.4856878505-1900.97284309044
1012778626506.41185284497965.5082021989721100.0799449561-1279.58814715508
1022619525905.72843483175219.7579495798521264.5136155885-289.271565168343
1032051618620.8212033800982.23151039914721428.9472862209-1895.17879662002
1042275922428.87919036961469.0239738706421620.0968357598-330.1208096304
1051902819465.6062148825-3220.8526001811321811.2463852987437.606214882479
1061697117210.7677032240-5311.6816780917922042.9139748678239.767703223981
1072003621180.5968289751-3383.1783934121122274.58156443701144.59682897515
1082248522430.1033027007-4.9096438419578822544.8063411412-54.8966972992748
1091873019614.0733072015-4969.1044250470122815.0311178455884.073307201506

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 21790 & 22279.4514224485 & -4969.10442504701 & 26269.6530025985 & 489.451422448474 \tabularnewline
2 & 13253 & 11506.5592112009 & -11364.7483778249 & 26364.189166624 & -1746.44078879906 \tabularnewline
3 & 37702 & 41206.8079722223 & 7738.46669712823 & 26458.7253306495 & 3504.80797222231 \tabularnewline
4 & 30364 & 29294.0123645075 & 4879.4871552399 & 26554.5004802526 & -1069.98763549248 \tabularnewline
5 & 32609 & 30602.2161679453 & 7965.50820219897 & 26650.2756298557 & -2006.78383205466 \tabularnewline
6 & 30212 & 28463.264056446 & 5219.75794957985 & 26740.9779939742 & -1748.73594355401 \tabularnewline
7 & 29965 & 32116.0881315082 & 982.231510399147 & 26831.6803580926 & 2151.08813150824 \tabularnewline
8 & 28352 & 28309.8163899307 & 1469.02397387064 & 26925.1596361987 & -42.1836100693399 \tabularnewline
9 & 25814 & 27830.2136858763 & -3220.85260018113 & 27018.6389143048 & 2016.21368587635 \tabularnewline
10 & 22414 & 22971.1822369874 & -5311.68167809179 & 27168.4994411044 & 557.182236987392 \tabularnewline
11 & 20506 & 17076.8184255081 & -3383.17839341211 & 27318.359967904 & -3429.1815744919 \tabularnewline
12 & 28806 & 30201.4561371599 & -4.90964384195788 & 27415.4535066821 & 1395.45613715985 \tabularnewline
13 & 22228 & 21912.5573795868 & -4969.10442504701 & 27512.5470454602 & -315.442620413185 \tabularnewline
14 & 13971 & 11935.5654279328 & -11364.7483778249 & 27371.1829498922 & -2035.43457206722 \tabularnewline
15 & 36845 & 38721.7144485476 & 7738.46669712823 & 27229.8188543241 & 1876.71444854765 \tabularnewline
16 & 35338 & 38811.6108030272 & 4879.4871552399 & 26984.9020417329 & 3473.61080302721 \tabularnewline
17 & 35022 & 35338.5065686594 & 7965.50820219897 & 26739.9852291417 & 316.506568659363 \tabularnewline
18 & 34777 & 37906.2187349761 & 5219.75794957985 & 26428.0233154440 & 3129.21873497610 \tabularnewline
19 & 26887 & 26675.7070878544 & 982.231510399147 & 26116.0614017464 & -211.29291214556 \tabularnewline
20 & 23970 & 20788.7950604075 & 1469.02397387064 & 25682.1809657219 & -3181.20493959254 \tabularnewline
21 & 22780 & 23532.5520704838 & -3220.85260018113 & 25248.3005296974 & 752.552070483751 \tabularnewline
22 & 17351 & 15284.5387127359 & -5311.68167809179 & 24729.1429653559 & -2066.46128726415 \tabularnewline
23 & 21382 & 21937.1929923976 & -3383.17839341211 & 24209.9854010145 & 555.19299239762 \tabularnewline
24 & 24561 & 25358.7008577858 & -4.90964384195788 & 23768.2087860561 & 797.700857785814 \tabularnewline
25 & 17409 & 16460.6722539492 & -4969.10442504701 & 23326.4321710978 & -948.32774605079 \tabularnewline
26 & 11514 & 11291.8903959135 & -11364.7483778249 & 23100.8579819114 & -222.109604086487 \tabularnewline
27 & 31514 & 32414.2495101467 & 7738.46669712823 & 22875.2837927251 & 900.249510146718 \tabularnewline
28 & 27071 & 26438.9955680138 & 4879.4871552399 & 22823.5172767463 & -632.004431986214 \tabularnewline
29 & 29462 & 28186.7410370335 & 7965.50820219897 & 22771.7507607676 & -1275.25896296654 \tabularnewline
30 & 26105 & 24157.271501553 & 5219.75794957985 & 22832.9705488672 & -1947.72849844701 \tabularnewline
31 & 22397 & 20917.5781526341 & 982.231510399147 & 22894.1903369667 & -1479.42184736589 \tabularnewline
32 & 23843 & 23198.0068700880 & 1469.02397387064 & 23018.9691560413 & -644.993129911978 \tabularnewline
33 & 21705 & 23487.1046250652 & -3220.85260018113 & 23143.7479751159 & 1782.10462506520 \tabularnewline
34 & 18089 & 18103.4907883817 & -5311.68167809179 & 23386.1908897101 & 14.4907883817323 \tabularnewline
35 & 20764 & 21282.5445891079 & -3383.17839341211 & 23628.6338043042 & 518.544589107922 \tabularnewline
36 & 25316 & 26743.1277767362 & -4.90964384195788 & 23893.7818671058 & 1427.12777673619 \tabularnewline
37 & 17704 & 16218.1744951397 & -4969.10442504701 & 24158.9299299074 & -1485.82550486034 \tabularnewline
38 & 15548 & 18253.3242094717 & -11364.7483778249 & 24207.4241683533 & 2705.32420947166 \tabularnewline
39 & 28029 & 24063.6148960726 & 7738.46669712823 & 24255.9184067992 & -3965.38510392744 \tabularnewline
40 & 29383 & 29747.0633896838 & 4879.4871552399 & 24139.4494550763 & 364.063389683757 \tabularnewline
41 & 36438 & 40887.5112944476 & 7965.50820219897 & 24022.9805033535 & 4449.51129444755 \tabularnewline
42 & 32034 & 34919.0699639174 & 5219.75794957985 & 23929.1720865027 & 2885.06996391742 \tabularnewline
43 & 22679 & 20540.4048199489 & 982.231510399147 & 23835.363669652 & -2138.59518005112 \tabularnewline
44 & 24319 & 23434.2091995291 & 1469.02397387064 & 23734.7668266003 & -884.790800470924 \tabularnewline
45 & 18004 & 15594.6826166325 & -3220.85260018113 & 23634.1699835486 & -2409.31738336746 \tabularnewline
46 & 17537 & 16981.8984633569 & -5311.68167809179 & 23403.7832147349 & -555.101536643098 \tabularnewline
47 & 20366 & 20941.7819474909 & -3383.17839341211 & 23173.3964459212 & 575.781947490934 \tabularnewline
48 & 22782 & 22632.3387146269 & -4.90964384195788 & 22936.5709292150 & -149.661285373069 \tabularnewline
49 & 19169 & 20607.3590125381 & -4969.10442504701 & 22699.7454125089 & 1438.35901253813 \tabularnewline
50 & 13807 & 16319.0215261833 & -11364.7483778249 & 22659.7268516416 & 2512.02152618329 \tabularnewline
51 & 29743 & 29127.8250120974 & 7738.46669712823 & 22619.7082907744 & -615.174987902643 \tabularnewline
52 & 25591 & 23704.7196492856 & 4879.4871552399 & 22597.7931954745 & -1886.28035071444 \tabularnewline
53 & 29096 & 27650.6136976264 & 7965.50820219897 & 22575.8781001747 & -1445.38630237363 \tabularnewline
54 & 26482 & 25257.6529931132 & 5219.75794957985 & 22486.589057307 & -1224.34700688684 \tabularnewline
55 & 22405 & 21430.4684751616 & 982.231510399147 & 22397.3000144393 & -974.531524838447 \tabularnewline
56 & 27044 & 30219.6789089989 & 1469.02397387064 & 22399.2971171304 & 3175.67890899895 \tabularnewline
57 & 17970 & 16759.5583803596 & -3220.85260018113 & 22401.2942198215 & -1210.44161964040 \tabularnewline
58 & 18730 & 20174.2804751038 & -5311.68167809179 & 22597.401202988 & 1444.28047510380 \tabularnewline
59 & 19684 & 19957.6702072577 & -3383.17839341211 & 22793.5081861544 & 273.670207257663 \tabularnewline
60 & 19785 & 16578.9439782000 & -4.90964384195788 & 22995.9656656419 & -3206.05602179998 \tabularnewline
61 & 18479 & 18728.6812799176 & -4969.10442504701 & 23198.4231451294 & 249.681279917582 \tabularnewline
62 & 10698 & 9503.116288489 & -11364.7483778249 & 23257.6320893359 & -1194.883711511 \tabularnewline
63 & 31956 & 32856.6922693293 & 7738.46669712823 & 23316.8410335424 & 900.692269329324 \tabularnewline
64 & 29506 & 30838.5805147819 & 4879.4871552399 & 23293.9323299782 & 1332.5805147819 \tabularnewline
65 & 34506 & 37775.4681713871 & 7965.50820219897 & 23271.0236264140 & 3269.46817138708 \tabularnewline
66 & 27165 & 25915.8888763761 & 5219.75794957985 & 23194.3531740441 & -1249.11112362394 \tabularnewline
67 & 26736 & 29372.0857679266 & 982.231510399147 & 23117.6827216742 & 2636.08576792664 \tabularnewline
68 & 23691 & 22956.3767007239 & 1469.02397387064 & 22956.5993254054 & -734.623299276063 \tabularnewline
69 & 18157 & 16739.3366710445 & -3220.85260018113 & 22795.5159291366 & -1417.66332895551 \tabularnewline
70 & 17328 & 17385.6075022776 & -5311.68167809179 & 22582.0741758142 & 57.6075022776095 \tabularnewline
71 & 18205 & 17424.5459709204 & -3383.17839341211 & 22368.6324224917 & -780.454029079614 \tabularnewline
72 & 20995 & 19750.2919950398 & -4.90964384195788 & 22244.6176488021 & -1244.70800496018 \tabularnewline
73 & 17382 & 17612.5015499345 & -4969.10442504701 & 22120.6028751126 & 230.501549934452 \tabularnewline
74 & 9367 & 7918.7687710315 & -11364.7483778249 & 22179.9796067934 & -1448.2312289685 \tabularnewline
75 & 31124 & 32270.1769643975 & 7738.46669712823 & 22239.3563384743 & 1146.17696439745 \tabularnewline
76 & 26551 & 25793.0930468058 & 4879.4871552399 & 22429.4197979543 & -757.906953194215 \tabularnewline
77 & 30651 & 30717.0085403667 & 7965.50820219897 & 22619.4832574343 & 66.0085403667144 \tabularnewline
78 & 25859 & 23642.1588912285 & 5219.75794957985 & 22856.0831591916 & -2216.84110877147 \tabularnewline
79 & 25100 & 26125.0854286519 & 982.231510399147 & 23092.6830609489 & 1025.08542865194 \tabularnewline
80 & 25778 & 26769.6707172353 & 1469.02397387064 & 23317.3053088940 & 991.670717235316 \tabularnewline
81 & 20418 & 20514.9250433420 & -3220.85260018113 & 23541.9275568392 & 96.925043341951 \tabularnewline
82 & 18688 & 18963.0548139022 & -5311.68167809179 & 23724.6268641896 & 275.054813902181 \tabularnewline
83 & 20424 & 20323.8522218721 & -3383.17839341211 & 23907.3261715400 & -100.147778127925 \tabularnewline
84 & 24776 & 25489.6547470625 & -4.90964384195788 & 24067.2548967794 & 713.654747062541 \tabularnewline
85 & 19814 & 20369.9208030282 & -4969.10442504701 & 24227.1836220188 & 555.92080302821 \tabularnewline
86 & 12738 & 12534.6599947769 & -11364.7483778249 & 24306.0883830481 & -203.340005223126 \tabularnewline
87 & 31566 & 31008.5401587944 & 7738.46669712823 & 24384.9931440773 & -557.459841205557 \tabularnewline
88 & 30111 & 30976.5021763005 & 4879.4871552399 & 24366.0106684596 & 865.502176300459 \tabularnewline
89 & 30019 & 27725.4636049591 & 7965.50820219897 & 24347.0281928420 & -2293.53639504093 \tabularnewline
90 & 31934 & 34444.7483796717 & 5219.75794957985 & 24203.4936707485 & 2510.74837967168 \tabularnewline
91 & 25826 & 26609.8093409459 & 982.231510399147 & 24059.959148655 & 783.809340945878 \tabularnewline
92 & 26835 & 28428.4716252958 & 1469.02397387064 & 23772.5044008336 & 1593.47162529575 \tabularnewline
93 & 20205 & 20145.8029471689 & -3220.85260018113 & 23485.0496530123 & -59.1970528311176 \tabularnewline
94 & 17789 & 17818.7926350153 & -5311.68167809179 & 23070.8890430765 & 29.7926350152593 \tabularnewline
95 & 20520 & 21766.4499602713 & -3383.17839341211 & 22656.7284331408 & 1246.44996027130 \tabularnewline
96 & 22518 & 22827.4322232011 & -4.90964384195788 & 22213.4774206409 & 309.432223201085 \tabularnewline
97 & 15572 & 14342.8780169061 & -4969.10442504701 & 21770.2264081409 & -1229.12198309393 \tabularnewline
98 & 11509 & 12936.1894583820 & -11364.7483778249 & 21446.5589194430 & 1427.18945838198 \tabularnewline
99 & 25447 & 22032.6418721268 & 7738.46669712823 & 21122.8914307450 & -3414.3581278732 \tabularnewline
100 & 24090 & 22189.0271569096 & 4879.4871552399 & 21111.4856878505 & -1900.97284309044 \tabularnewline
101 & 27786 & 26506.4118528449 & 7965.50820219897 & 21100.0799449561 & -1279.58814715508 \tabularnewline
102 & 26195 & 25905.7284348317 & 5219.75794957985 & 21264.5136155885 & -289.271565168343 \tabularnewline
103 & 20516 & 18620.8212033800 & 982.231510399147 & 21428.9472862209 & -1895.17879662002 \tabularnewline
104 & 22759 & 22428.8791903696 & 1469.02397387064 & 21620.0968357598 & -330.1208096304 \tabularnewline
105 & 19028 & 19465.6062148825 & -3220.85260018113 & 21811.2463852987 & 437.606214882479 \tabularnewline
106 & 16971 & 17210.7677032240 & -5311.68167809179 & 22042.9139748678 & 239.767703223981 \tabularnewline
107 & 20036 & 21180.5968289751 & -3383.17839341211 & 22274.5815644370 & 1144.59682897515 \tabularnewline
108 & 22485 & 22430.1033027007 & -4.90964384195788 & 22544.8063411412 & -54.8966972992748 \tabularnewline
109 & 18730 & 19614.0733072015 & -4969.10442504701 & 22815.0311178455 & 884.073307201506 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=66524&T=2

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Time Series Components[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Fitted[/C][C]Seasonal[/C][C]Trend[/C][C]Remainder[/C][/ROW]
[ROW][C]1[/C][C]21790[/C][C]22279.4514224485[/C][C]-4969.10442504701[/C][C]26269.6530025985[/C][C]489.451422448474[/C][/ROW]
[ROW][C]2[/C][C]13253[/C][C]11506.5592112009[/C][C]-11364.7483778249[/C][C]26364.189166624[/C][C]-1746.44078879906[/C][/ROW]
[ROW][C]3[/C][C]37702[/C][C]41206.8079722223[/C][C]7738.46669712823[/C][C]26458.7253306495[/C][C]3504.80797222231[/C][/ROW]
[ROW][C]4[/C][C]30364[/C][C]29294.0123645075[/C][C]4879.4871552399[/C][C]26554.5004802526[/C][C]-1069.98763549248[/C][/ROW]
[ROW][C]5[/C][C]32609[/C][C]30602.2161679453[/C][C]7965.50820219897[/C][C]26650.2756298557[/C][C]-2006.78383205466[/C][/ROW]
[ROW][C]6[/C][C]30212[/C][C]28463.264056446[/C][C]5219.75794957985[/C][C]26740.9779939742[/C][C]-1748.73594355401[/C][/ROW]
[ROW][C]7[/C][C]29965[/C][C]32116.0881315082[/C][C]982.231510399147[/C][C]26831.6803580926[/C][C]2151.08813150824[/C][/ROW]
[ROW][C]8[/C][C]28352[/C][C]28309.8163899307[/C][C]1469.02397387064[/C][C]26925.1596361987[/C][C]-42.1836100693399[/C][/ROW]
[ROW][C]9[/C][C]25814[/C][C]27830.2136858763[/C][C]-3220.85260018113[/C][C]27018.6389143048[/C][C]2016.21368587635[/C][/ROW]
[ROW][C]10[/C][C]22414[/C][C]22971.1822369874[/C][C]-5311.68167809179[/C][C]27168.4994411044[/C][C]557.182236987392[/C][/ROW]
[ROW][C]11[/C][C]20506[/C][C]17076.8184255081[/C][C]-3383.17839341211[/C][C]27318.359967904[/C][C]-3429.1815744919[/C][/ROW]
[ROW][C]12[/C][C]28806[/C][C]30201.4561371599[/C][C]-4.90964384195788[/C][C]27415.4535066821[/C][C]1395.45613715985[/C][/ROW]
[ROW][C]13[/C][C]22228[/C][C]21912.5573795868[/C][C]-4969.10442504701[/C][C]27512.5470454602[/C][C]-315.442620413185[/C][/ROW]
[ROW][C]14[/C][C]13971[/C][C]11935.5654279328[/C][C]-11364.7483778249[/C][C]27371.1829498922[/C][C]-2035.43457206722[/C][/ROW]
[ROW][C]15[/C][C]36845[/C][C]38721.7144485476[/C][C]7738.46669712823[/C][C]27229.8188543241[/C][C]1876.71444854765[/C][/ROW]
[ROW][C]16[/C][C]35338[/C][C]38811.6108030272[/C][C]4879.4871552399[/C][C]26984.9020417329[/C][C]3473.61080302721[/C][/ROW]
[ROW][C]17[/C][C]35022[/C][C]35338.5065686594[/C][C]7965.50820219897[/C][C]26739.9852291417[/C][C]316.506568659363[/C][/ROW]
[ROW][C]18[/C][C]34777[/C][C]37906.2187349761[/C][C]5219.75794957985[/C][C]26428.0233154440[/C][C]3129.21873497610[/C][/ROW]
[ROW][C]19[/C][C]26887[/C][C]26675.7070878544[/C][C]982.231510399147[/C][C]26116.0614017464[/C][C]-211.29291214556[/C][/ROW]
[ROW][C]20[/C][C]23970[/C][C]20788.7950604075[/C][C]1469.02397387064[/C][C]25682.1809657219[/C][C]-3181.20493959254[/C][/ROW]
[ROW][C]21[/C][C]22780[/C][C]23532.5520704838[/C][C]-3220.85260018113[/C][C]25248.3005296974[/C][C]752.552070483751[/C][/ROW]
[ROW][C]22[/C][C]17351[/C][C]15284.5387127359[/C][C]-5311.68167809179[/C][C]24729.1429653559[/C][C]-2066.46128726415[/C][/ROW]
[ROW][C]23[/C][C]21382[/C][C]21937.1929923976[/C][C]-3383.17839341211[/C][C]24209.9854010145[/C][C]555.19299239762[/C][/ROW]
[ROW][C]24[/C][C]24561[/C][C]25358.7008577858[/C][C]-4.90964384195788[/C][C]23768.2087860561[/C][C]797.700857785814[/C][/ROW]
[ROW][C]25[/C][C]17409[/C][C]16460.6722539492[/C][C]-4969.10442504701[/C][C]23326.4321710978[/C][C]-948.32774605079[/C][/ROW]
[ROW][C]26[/C][C]11514[/C][C]11291.8903959135[/C][C]-11364.7483778249[/C][C]23100.8579819114[/C][C]-222.109604086487[/C][/ROW]
[ROW][C]27[/C][C]31514[/C][C]32414.2495101467[/C][C]7738.46669712823[/C][C]22875.2837927251[/C][C]900.249510146718[/C][/ROW]
[ROW][C]28[/C][C]27071[/C][C]26438.9955680138[/C][C]4879.4871552399[/C][C]22823.5172767463[/C][C]-632.004431986214[/C][/ROW]
[ROW][C]29[/C][C]29462[/C][C]28186.7410370335[/C][C]7965.50820219897[/C][C]22771.7507607676[/C][C]-1275.25896296654[/C][/ROW]
[ROW][C]30[/C][C]26105[/C][C]24157.271501553[/C][C]5219.75794957985[/C][C]22832.9705488672[/C][C]-1947.72849844701[/C][/ROW]
[ROW][C]31[/C][C]22397[/C][C]20917.5781526341[/C][C]982.231510399147[/C][C]22894.1903369667[/C][C]-1479.42184736589[/C][/ROW]
[ROW][C]32[/C][C]23843[/C][C]23198.0068700880[/C][C]1469.02397387064[/C][C]23018.9691560413[/C][C]-644.993129911978[/C][/ROW]
[ROW][C]33[/C][C]21705[/C][C]23487.1046250652[/C][C]-3220.85260018113[/C][C]23143.7479751159[/C][C]1782.10462506520[/C][/ROW]
[ROW][C]34[/C][C]18089[/C][C]18103.4907883817[/C][C]-5311.68167809179[/C][C]23386.1908897101[/C][C]14.4907883817323[/C][/ROW]
[ROW][C]35[/C][C]20764[/C][C]21282.5445891079[/C][C]-3383.17839341211[/C][C]23628.6338043042[/C][C]518.544589107922[/C][/ROW]
[ROW][C]36[/C][C]25316[/C][C]26743.1277767362[/C][C]-4.90964384195788[/C][C]23893.7818671058[/C][C]1427.12777673619[/C][/ROW]
[ROW][C]37[/C][C]17704[/C][C]16218.1744951397[/C][C]-4969.10442504701[/C][C]24158.9299299074[/C][C]-1485.82550486034[/C][/ROW]
[ROW][C]38[/C][C]15548[/C][C]18253.3242094717[/C][C]-11364.7483778249[/C][C]24207.4241683533[/C][C]2705.32420947166[/C][/ROW]
[ROW][C]39[/C][C]28029[/C][C]24063.6148960726[/C][C]7738.46669712823[/C][C]24255.9184067992[/C][C]-3965.38510392744[/C][/ROW]
[ROW][C]40[/C][C]29383[/C][C]29747.0633896838[/C][C]4879.4871552399[/C][C]24139.4494550763[/C][C]364.063389683757[/C][/ROW]
[ROW][C]41[/C][C]36438[/C][C]40887.5112944476[/C][C]7965.50820219897[/C][C]24022.9805033535[/C][C]4449.51129444755[/C][/ROW]
[ROW][C]42[/C][C]32034[/C][C]34919.0699639174[/C][C]5219.75794957985[/C][C]23929.1720865027[/C][C]2885.06996391742[/C][/ROW]
[ROW][C]43[/C][C]22679[/C][C]20540.4048199489[/C][C]982.231510399147[/C][C]23835.363669652[/C][C]-2138.59518005112[/C][/ROW]
[ROW][C]44[/C][C]24319[/C][C]23434.2091995291[/C][C]1469.02397387064[/C][C]23734.7668266003[/C][C]-884.790800470924[/C][/ROW]
[ROW][C]45[/C][C]18004[/C][C]15594.6826166325[/C][C]-3220.85260018113[/C][C]23634.1699835486[/C][C]-2409.31738336746[/C][/ROW]
[ROW][C]46[/C][C]17537[/C][C]16981.8984633569[/C][C]-5311.68167809179[/C][C]23403.7832147349[/C][C]-555.101536643098[/C][/ROW]
[ROW][C]47[/C][C]20366[/C][C]20941.7819474909[/C][C]-3383.17839341211[/C][C]23173.3964459212[/C][C]575.781947490934[/C][/ROW]
[ROW][C]48[/C][C]22782[/C][C]22632.3387146269[/C][C]-4.90964384195788[/C][C]22936.5709292150[/C][C]-149.661285373069[/C][/ROW]
[ROW][C]49[/C][C]19169[/C][C]20607.3590125381[/C][C]-4969.10442504701[/C][C]22699.7454125089[/C][C]1438.35901253813[/C][/ROW]
[ROW][C]50[/C][C]13807[/C][C]16319.0215261833[/C][C]-11364.7483778249[/C][C]22659.7268516416[/C][C]2512.02152618329[/C][/ROW]
[ROW][C]51[/C][C]29743[/C][C]29127.8250120974[/C][C]7738.46669712823[/C][C]22619.7082907744[/C][C]-615.174987902643[/C][/ROW]
[ROW][C]52[/C][C]25591[/C][C]23704.7196492856[/C][C]4879.4871552399[/C][C]22597.7931954745[/C][C]-1886.28035071444[/C][/ROW]
[ROW][C]53[/C][C]29096[/C][C]27650.6136976264[/C][C]7965.50820219897[/C][C]22575.8781001747[/C][C]-1445.38630237363[/C][/ROW]
[ROW][C]54[/C][C]26482[/C][C]25257.6529931132[/C][C]5219.75794957985[/C][C]22486.589057307[/C][C]-1224.34700688684[/C][/ROW]
[ROW][C]55[/C][C]22405[/C][C]21430.4684751616[/C][C]982.231510399147[/C][C]22397.3000144393[/C][C]-974.531524838447[/C][/ROW]
[ROW][C]56[/C][C]27044[/C][C]30219.6789089989[/C][C]1469.02397387064[/C][C]22399.2971171304[/C][C]3175.67890899895[/C][/ROW]
[ROW][C]57[/C][C]17970[/C][C]16759.5583803596[/C][C]-3220.85260018113[/C][C]22401.2942198215[/C][C]-1210.44161964040[/C][/ROW]
[ROW][C]58[/C][C]18730[/C][C]20174.2804751038[/C][C]-5311.68167809179[/C][C]22597.401202988[/C][C]1444.28047510380[/C][/ROW]
[ROW][C]59[/C][C]19684[/C][C]19957.6702072577[/C][C]-3383.17839341211[/C][C]22793.5081861544[/C][C]273.670207257663[/C][/ROW]
[ROW][C]60[/C][C]19785[/C][C]16578.9439782000[/C][C]-4.90964384195788[/C][C]22995.9656656419[/C][C]-3206.05602179998[/C][/ROW]
[ROW][C]61[/C][C]18479[/C][C]18728.6812799176[/C][C]-4969.10442504701[/C][C]23198.4231451294[/C][C]249.681279917582[/C][/ROW]
[ROW][C]62[/C][C]10698[/C][C]9503.116288489[/C][C]-11364.7483778249[/C][C]23257.6320893359[/C][C]-1194.883711511[/C][/ROW]
[ROW][C]63[/C][C]31956[/C][C]32856.6922693293[/C][C]7738.46669712823[/C][C]23316.8410335424[/C][C]900.692269329324[/C][/ROW]
[ROW][C]64[/C][C]29506[/C][C]30838.5805147819[/C][C]4879.4871552399[/C][C]23293.9323299782[/C][C]1332.5805147819[/C][/ROW]
[ROW][C]65[/C][C]34506[/C][C]37775.4681713871[/C][C]7965.50820219897[/C][C]23271.0236264140[/C][C]3269.46817138708[/C][/ROW]
[ROW][C]66[/C][C]27165[/C][C]25915.8888763761[/C][C]5219.75794957985[/C][C]23194.3531740441[/C][C]-1249.11112362394[/C][/ROW]
[ROW][C]67[/C][C]26736[/C][C]29372.0857679266[/C][C]982.231510399147[/C][C]23117.6827216742[/C][C]2636.08576792664[/C][/ROW]
[ROW][C]68[/C][C]23691[/C][C]22956.3767007239[/C][C]1469.02397387064[/C][C]22956.5993254054[/C][C]-734.623299276063[/C][/ROW]
[ROW][C]69[/C][C]18157[/C][C]16739.3366710445[/C][C]-3220.85260018113[/C][C]22795.5159291366[/C][C]-1417.66332895551[/C][/ROW]
[ROW][C]70[/C][C]17328[/C][C]17385.6075022776[/C][C]-5311.68167809179[/C][C]22582.0741758142[/C][C]57.6075022776095[/C][/ROW]
[ROW][C]71[/C][C]18205[/C][C]17424.5459709204[/C][C]-3383.17839341211[/C][C]22368.6324224917[/C][C]-780.454029079614[/C][/ROW]
[ROW][C]72[/C][C]20995[/C][C]19750.2919950398[/C][C]-4.90964384195788[/C][C]22244.6176488021[/C][C]-1244.70800496018[/C][/ROW]
[ROW][C]73[/C][C]17382[/C][C]17612.5015499345[/C][C]-4969.10442504701[/C][C]22120.6028751126[/C][C]230.501549934452[/C][/ROW]
[ROW][C]74[/C][C]9367[/C][C]7918.7687710315[/C][C]-11364.7483778249[/C][C]22179.9796067934[/C][C]-1448.2312289685[/C][/ROW]
[ROW][C]75[/C][C]31124[/C][C]32270.1769643975[/C][C]7738.46669712823[/C][C]22239.3563384743[/C][C]1146.17696439745[/C][/ROW]
[ROW][C]76[/C][C]26551[/C][C]25793.0930468058[/C][C]4879.4871552399[/C][C]22429.4197979543[/C][C]-757.906953194215[/C][/ROW]
[ROW][C]77[/C][C]30651[/C][C]30717.0085403667[/C][C]7965.50820219897[/C][C]22619.4832574343[/C][C]66.0085403667144[/C][/ROW]
[ROW][C]78[/C][C]25859[/C][C]23642.1588912285[/C][C]5219.75794957985[/C][C]22856.0831591916[/C][C]-2216.84110877147[/C][/ROW]
[ROW][C]79[/C][C]25100[/C][C]26125.0854286519[/C][C]982.231510399147[/C][C]23092.6830609489[/C][C]1025.08542865194[/C][/ROW]
[ROW][C]80[/C][C]25778[/C][C]26769.6707172353[/C][C]1469.02397387064[/C][C]23317.3053088940[/C][C]991.670717235316[/C][/ROW]
[ROW][C]81[/C][C]20418[/C][C]20514.9250433420[/C][C]-3220.85260018113[/C][C]23541.9275568392[/C][C]96.925043341951[/C][/ROW]
[ROW][C]82[/C][C]18688[/C][C]18963.0548139022[/C][C]-5311.68167809179[/C][C]23724.6268641896[/C][C]275.054813902181[/C][/ROW]
[ROW][C]83[/C][C]20424[/C][C]20323.8522218721[/C][C]-3383.17839341211[/C][C]23907.3261715400[/C][C]-100.147778127925[/C][/ROW]
[ROW][C]84[/C][C]24776[/C][C]25489.6547470625[/C][C]-4.90964384195788[/C][C]24067.2548967794[/C][C]713.654747062541[/C][/ROW]
[ROW][C]85[/C][C]19814[/C][C]20369.9208030282[/C][C]-4969.10442504701[/C][C]24227.1836220188[/C][C]555.92080302821[/C][/ROW]
[ROW][C]86[/C][C]12738[/C][C]12534.6599947769[/C][C]-11364.7483778249[/C][C]24306.0883830481[/C][C]-203.340005223126[/C][/ROW]
[ROW][C]87[/C][C]31566[/C][C]31008.5401587944[/C][C]7738.46669712823[/C][C]24384.9931440773[/C][C]-557.459841205557[/C][/ROW]
[ROW][C]88[/C][C]30111[/C][C]30976.5021763005[/C][C]4879.4871552399[/C][C]24366.0106684596[/C][C]865.502176300459[/C][/ROW]
[ROW][C]89[/C][C]30019[/C][C]27725.4636049591[/C][C]7965.50820219897[/C][C]24347.0281928420[/C][C]-2293.53639504093[/C][/ROW]
[ROW][C]90[/C][C]31934[/C][C]34444.7483796717[/C][C]5219.75794957985[/C][C]24203.4936707485[/C][C]2510.74837967168[/C][/ROW]
[ROW][C]91[/C][C]25826[/C][C]26609.8093409459[/C][C]982.231510399147[/C][C]24059.959148655[/C][C]783.809340945878[/C][/ROW]
[ROW][C]92[/C][C]26835[/C][C]28428.4716252958[/C][C]1469.02397387064[/C][C]23772.5044008336[/C][C]1593.47162529575[/C][/ROW]
[ROW][C]93[/C][C]20205[/C][C]20145.8029471689[/C][C]-3220.85260018113[/C][C]23485.0496530123[/C][C]-59.1970528311176[/C][/ROW]
[ROW][C]94[/C][C]17789[/C][C]17818.7926350153[/C][C]-5311.68167809179[/C][C]23070.8890430765[/C][C]29.7926350152593[/C][/ROW]
[ROW][C]95[/C][C]20520[/C][C]21766.4499602713[/C][C]-3383.17839341211[/C][C]22656.7284331408[/C][C]1246.44996027130[/C][/ROW]
[ROW][C]96[/C][C]22518[/C][C]22827.4322232011[/C][C]-4.90964384195788[/C][C]22213.4774206409[/C][C]309.432223201085[/C][/ROW]
[ROW][C]97[/C][C]15572[/C][C]14342.8780169061[/C][C]-4969.10442504701[/C][C]21770.2264081409[/C][C]-1229.12198309393[/C][/ROW]
[ROW][C]98[/C][C]11509[/C][C]12936.1894583820[/C][C]-11364.7483778249[/C][C]21446.5589194430[/C][C]1427.18945838198[/C][/ROW]
[ROW][C]99[/C][C]25447[/C][C]22032.6418721268[/C][C]7738.46669712823[/C][C]21122.8914307450[/C][C]-3414.3581278732[/C][/ROW]
[ROW][C]100[/C][C]24090[/C][C]22189.0271569096[/C][C]4879.4871552399[/C][C]21111.4856878505[/C][C]-1900.97284309044[/C][/ROW]
[ROW][C]101[/C][C]27786[/C][C]26506.4118528449[/C][C]7965.50820219897[/C][C]21100.0799449561[/C][C]-1279.58814715508[/C][/ROW]
[ROW][C]102[/C][C]26195[/C][C]25905.7284348317[/C][C]5219.75794957985[/C][C]21264.5136155885[/C][C]-289.271565168343[/C][/ROW]
[ROW][C]103[/C][C]20516[/C][C]18620.8212033800[/C][C]982.231510399147[/C][C]21428.9472862209[/C][C]-1895.17879662002[/C][/ROW]
[ROW][C]104[/C][C]22759[/C][C]22428.8791903696[/C][C]1469.02397387064[/C][C]21620.0968357598[/C][C]-330.1208096304[/C][/ROW]
[ROW][C]105[/C][C]19028[/C][C]19465.6062148825[/C][C]-3220.85260018113[/C][C]21811.2463852987[/C][C]437.606214882479[/C][/ROW]
[ROW][C]106[/C][C]16971[/C][C]17210.7677032240[/C][C]-5311.68167809179[/C][C]22042.9139748678[/C][C]239.767703223981[/C][/ROW]
[ROW][C]107[/C][C]20036[/C][C]21180.5968289751[/C][C]-3383.17839341211[/C][C]22274.5815644370[/C][C]1144.59682897515[/C][/ROW]
[ROW][C]108[/C][C]22485[/C][C]22430.1033027007[/C][C]-4.90964384195788[/C][C]22544.8063411412[/C][C]-54.8966972992748[/C][/ROW]
[ROW][C]109[/C][C]18730[/C][C]19614.0733072015[/C][C]-4969.10442504701[/C][C]22815.0311178455[/C][C]884.073307201506[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=66524&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=66524&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
12179022279.4514224485-4969.1044250470126269.6530025985489.451422448474
21325311506.5592112009-11364.748377824926364.189166624-1746.44078879906
33770241206.80797222237738.4666971282326458.72533064953504.80797222231
43036429294.01236450754879.487155239926554.5004802526-1069.98763549248
53260930602.21616794537965.5082021989726650.2756298557-2006.78383205466
63021228463.2640564465219.7579495798526740.9779939742-1748.73594355401
72996532116.0881315082982.23151039914726831.68035809262151.08813150824
82835228309.81638993071469.0239738706426925.1596361987-42.1836100693399
92581427830.2136858763-3220.8526001811327018.63891430482016.21368587635
102241422971.1822369874-5311.6816780917927168.4994411044557.182236987392
112050617076.8184255081-3383.1783934121127318.359967904-3429.1815744919
122880630201.4561371599-4.9096438419578827415.45350668211395.45613715985
132222821912.5573795868-4969.1044250470127512.5470454602-315.442620413185
141397111935.5654279328-11364.748377824927371.1829498922-2035.43457206722
153684538721.71444854767738.4666971282327229.81885432411876.71444854765
163533838811.61080302724879.487155239926984.90204173293473.61080302721
173502235338.50656865947965.5082021989726739.9852291417316.506568659363
183477737906.21873497615219.7579495798526428.02331544403129.21873497610
192688726675.7070878544982.23151039914726116.0614017464-211.29291214556
202397020788.79506040751469.0239738706425682.1809657219-3181.20493959254
212278023532.5520704838-3220.8526001811325248.3005296974752.552070483751
221735115284.5387127359-5311.6816780917924729.1429653559-2066.46128726415
232138221937.1929923976-3383.1783934121124209.9854010145555.19299239762
242456125358.7008577858-4.9096438419578823768.2087860561797.700857785814
251740916460.6722539492-4969.1044250470123326.4321710978-948.32774605079
261151411291.8903959135-11364.748377824923100.8579819114-222.109604086487
273151432414.24951014677738.4666971282322875.2837927251900.249510146718
282707126438.99556801384879.487155239922823.5172767463-632.004431986214
292946228186.74103703357965.5082021989722771.7507607676-1275.25896296654
302610524157.2715015535219.7579495798522832.9705488672-1947.72849844701
312239720917.5781526341982.23151039914722894.1903369667-1479.42184736589
322384323198.00687008801469.0239738706423018.9691560413-644.993129911978
332170523487.1046250652-3220.8526001811323143.74797511591782.10462506520
341808918103.4907883817-5311.6816780917923386.190889710114.4907883817323
352076421282.5445891079-3383.1783934121123628.6338043042518.544589107922
362531626743.1277767362-4.9096438419578823893.78186710581427.12777673619
371770416218.1744951397-4969.1044250470124158.9299299074-1485.82550486034
381554818253.3242094717-11364.748377824924207.42416835332705.32420947166
392802924063.61489607267738.4666971282324255.9184067992-3965.38510392744
402938329747.06338968384879.487155239924139.4494550763364.063389683757
413643840887.51129444767965.5082021989724022.98050335354449.51129444755
423203434919.06996391745219.7579495798523929.17208650272885.06996391742
432267920540.4048199489982.23151039914723835.363669652-2138.59518005112
442431923434.20919952911469.0239738706423734.7668266003-884.790800470924
451800415594.6826166325-3220.8526001811323634.1699835486-2409.31738336746
461753716981.8984633569-5311.6816780917923403.7832147349-555.101536643098
472036620941.7819474909-3383.1783934121123173.3964459212575.781947490934
482278222632.3387146269-4.9096438419578822936.5709292150-149.661285373069
491916920607.3590125381-4969.1044250470122699.74541250891438.35901253813
501380716319.0215261833-11364.748377824922659.72685164162512.02152618329
512974329127.82501209747738.4666971282322619.7082907744-615.174987902643
522559123704.71964928564879.487155239922597.7931954745-1886.28035071444
532909627650.61369762647965.5082021989722575.8781001747-1445.38630237363
542648225257.65299311325219.7579495798522486.589057307-1224.34700688684
552240521430.4684751616982.23151039914722397.3000144393-974.531524838447
562704430219.67890899891469.0239738706422399.29711713043175.67890899895
571797016759.5583803596-3220.8526001811322401.2942198215-1210.44161964040
581873020174.2804751038-5311.6816780917922597.4012029881444.28047510380
591968419957.6702072577-3383.1783934121122793.5081861544273.670207257663
601978516578.9439782000-4.9096438419578822995.9656656419-3206.05602179998
611847918728.6812799176-4969.1044250470123198.4231451294249.681279917582
62106989503.116288489-11364.748377824923257.6320893359-1194.883711511
633195632856.69226932937738.4666971282323316.8410335424900.692269329324
642950630838.58051478194879.487155239923293.93232997821332.5805147819
653450637775.46817138717965.5082021989723271.02362641403269.46817138708
662716525915.88887637615219.7579495798523194.3531740441-1249.11112362394
672673629372.0857679266982.23151039914723117.68272167422636.08576792664
682369122956.37670072391469.0239738706422956.5993254054-734.623299276063
691815716739.3366710445-3220.8526001811322795.5159291366-1417.66332895551
701732817385.6075022776-5311.6816780917922582.074175814257.6075022776095
711820517424.5459709204-3383.1783934121122368.6324224917-780.454029079614
722099519750.2919950398-4.9096438419578822244.6176488021-1244.70800496018
731738217612.5015499345-4969.1044250470122120.6028751126230.501549934452
7493677918.7687710315-11364.748377824922179.9796067934-1448.2312289685
753112432270.17696439757738.4666971282322239.35633847431146.17696439745
762655125793.09304680584879.487155239922429.4197979543-757.906953194215
773065130717.00854036677965.5082021989722619.483257434366.0085403667144
782585923642.15889122855219.7579495798522856.0831591916-2216.84110877147
792510026125.0854286519982.23151039914723092.68306094891025.08542865194
802577826769.67071723531469.0239738706423317.3053088940991.670717235316
812041820514.9250433420-3220.8526001811323541.927556839296.925043341951
821868818963.0548139022-5311.6816780917923724.6268641896275.054813902181
832042420323.8522218721-3383.1783934121123907.3261715400-100.147778127925
842477625489.6547470625-4.9096438419578824067.2548967794713.654747062541
851981420369.9208030282-4969.1044250470124227.1836220188555.92080302821
861273812534.6599947769-11364.748377824924306.0883830481-203.340005223126
873156631008.54015879447738.4666971282324384.9931440773-557.459841205557
883011130976.50217630054879.487155239924366.0106684596865.502176300459
893001927725.46360495917965.5082021989724347.0281928420-2293.53639504093
903193434444.74837967175219.7579495798524203.49367074852510.74837967168
912582626609.8093409459982.23151039914724059.959148655783.809340945878
922683528428.47162529581469.0239738706423772.50440083361593.47162529575
932020520145.8029471689-3220.8526001811323485.0496530123-59.1970528311176
941778917818.7926350153-5311.6816780917923070.889043076529.7926350152593
952052021766.4499602713-3383.1783934121122656.72843314081246.44996027130
962251822827.4322232011-4.9096438419578822213.4774206409309.432223201085
971557214342.8780169061-4969.1044250470121770.2264081409-1229.12198309393
981150912936.1894583820-11364.748377824921446.55891944301427.18945838198
992544722032.64187212687738.4666971282321122.8914307450-3414.3581278732
1002409022189.02715690964879.487155239921111.4856878505-1900.97284309044
1012778626506.41185284497965.5082021989721100.0799449561-1279.58814715508
1022619525905.72843483175219.7579495798521264.5136155885-289.271565168343
1032051618620.8212033800982.23151039914721428.9472862209-1895.17879662002
1042275922428.87919036961469.0239738706421620.0968357598-330.1208096304
1051902819465.6062148825-3220.8526001811321811.2463852987437.606214882479
1061697117210.7677032240-5311.6816780917922042.9139748678239.767703223981
1072003621180.5968289751-3383.1783934121122274.58156443701144.59682897515
1082248522430.1033027007-4.9096438419578822544.8063411412-54.8966972992748
1091873019614.0733072015-4969.1044250470122815.0311178455884.073307201506


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;
Parameters (R input):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par4 = ; par5 = 1 ; par6 = ; par7 = 1 ; par8 = FALSE ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) #seasonal period
if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
par3 <- as.numeric(par3) #s.degree
if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
par5 <- as.numeric(par5)#t.degree
if (par6 != '') par6 <- as.numeric(par6)#l.window
par7 <- as.numeric(par7)#l.degree
if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
nx <- length(x)
x <- ts(x,frequency=par1)
if (par6 != '') {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
} else {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
}
m$time.series
m$win
m$deg
m$jump
m$inner
m$outer
bitmap(file='test1.png')
plot(m,main=main)
dev.off()
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Component',header=TRUE)
a<-table.element(a,'Window',header=TRUE)
a<-table.element(a,'Degree',header=TRUE)
a<-table.element(a,'Jump',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,m$win['s'])
a<-table.element(a,m$deg['s'])
a<-table.element(a,m$jump['s'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,m$win['t'])
a<-table.element(a,m$deg['t'])
a<-table.element(a,m$jump['t'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Low-pass',header=TRUE)
a<-table.element(a,m$win['l'])
a<-table.element(a,m$deg['l'])
a<-table.element(a,m$jump['l'])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Fitted',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Remainder',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]+m$time.series[i,'remainder'])
a<-table.element(a,m$time.series[i,'seasonal'])
a<-table.element(a,m$time.series[i,'trend'])
a<-table.element(a,m$time.series[i,'remainder'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')