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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 computationSun, 26 Dec 2010 13:01:50 +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/Dec/26/t1293368396iqgc172lsef40ug.htm/, Retrieved Mon, 06 May 2024 23:36:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115578, Retrieved Mon, 06 May 2024 23:36:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Decomposition by Loess] [HPC Retail Sales] [2008-03-06 11:35:25] [74be16979710d4c4e7c6647856088456]
-  M D  [Decomposition by Loess] [WS5 - monthly bir...] [2010-12-08 15:24:24] [8ed0bd3560b9ca2814a2ed0a29182575]
-    D      [Decomposition by Loess] [LOESS Dollar] [2010-12-26 13:01:50] [c9d5faca36bd2ada281161976df30bf1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,8973
0,9383
0,9217
0,9095
0,892
0,8742
0,8532
0,8607
0,9005
0,9111
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684
1,457
1,4718
1,4748
1,5527
1,575
1,5557
1,5553
1,577
1,4975
1,4369
1,3322
1,2732
1,3449
1,3239
1,2785
1,305
1,319
1,365
1,4016
1,4088
1,4268
1,4562
1,4816
1,4914
1,4614
1,4272
1,3686
1,3569
1,3406
1,2565
1,2208
1,277
1,2894
1,3067
1,3898
1,3661

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115578&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115578&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115578&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132






Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal12010121
Trend1912
Low-pass1312

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1201 & 0 & 121 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115578&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]1201[/C][C]0[/C][C]121[/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=115578&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115578&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
Seasonal12010121
Trend1912
Low-pass1312






Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
10.89730.878267073169820.007752036327524580.908580890502655-0.0190329268301795
20.93830.9620041827870660.008589669804546870.9060061474083870.0237041827870664
30.92170.9479912771159-0.008022681430019080.9034314043141190.0262912771159005
40.90950.91979580081931-0.001964066054488960.9011682652351780.0102958008193107
50.8920.888990325529938-0.003895451686175770.898905126156238-0.00300967447006228
60.87420.852782792587538-0.001142755842568030.89675996325503-0.0214172074124621
70.85320.819335284208058-0.007550084561880780.894614800353822-0.0338647157919415
80.86070.8259275677852840.003390236018755750.89208219619596-0.0347724322147160
90.90050.913179849079709-0.001729441117807530.8895495920380980.0126798490797091
100.91110.935880909782224-0.001542959291259250.8878620495090350.0247809097822242
110.90590.9226919815384170.002933511481611160.8861745069799720.0167919815384171
120.88830.884297977374630.003182000347286680.889120022278083-0.00400202262536997
130.89240.884982426096280.007752036327524580.892065537576195-0.00741757390371933
140.88330.85948476291710.008589669804546870.898525567278353-0.0238152370828996
150.870.843037084449508-0.008022681430019080.90498559698051-0.0269629155504916
160.87580.840664612086668-0.001964066054488960.912899453967821-0.0351353879133325
170.88580.854682140731044-0.003895451686175770.920813310955132-0.0311178592689565
180.9170.903949834554846-0.001142755842568030.931192921287722-0.0130501654451540
190.95540.976777552941569-0.007550084561880780.9415725316203120.0213775529415688
200.99221.025365815851120.003390236018755750.9556439481301230.0331658158511213
210.97780.987614076477874-0.001729441117807530.9697153646399340.00981407647787358
220.98080.97715540473648-0.001542959291259250.985987554554779-0.00364459526351957
230.98110.9570067440487650.002933511481611161.00225974446962-0.0240932559512349
241.00140.9805709668939740.003182000347286681.01904703275874-0.0208290331060259
251.01830.993013642624620.007752036327524581.03583432104786-0.0252863573753797
261.06221.064648502297890.008589669804546871.051161827897560.00244850229788907
271.07731.09613334668275-0.008022681430019081.066489334747270.0188333466827459
281.08071.08255586169858-0.001964066054488961.080808204355910.00185586169858087
291.08481.07836837772163-0.003895451686175771.09512707396454-0.00643162227836713
301.15821.20810873412947-0.001142755842568031.109434021713100.0499087341294655
311.16631.21640911510022-0.007550084561880781.123740969461660.0501091151002186
321.13721.132782550801490.003390236018755751.13822721317975-0.00441744919850806
331.11391.07681598421996-0.001729441117807531.15271345689784-0.0370840157800354
341.12221.08136764237426-0.001542959291259251.164575316917-0.0408323576257406
351.16921.159029311582230.002933511481611161.17643717693616-0.0101706884177684
361.17021.152376250487310.003182000347286681.18484174916540-0.0178237495126898
371.22861.256201642277830.007752036327524581.193246321394650.0276016422778267
381.26131.313557341244380.008589669804546871.200452988951070.0522573412443839
391.26461.32956302492253-0.008022681430019081.207659656507490.0649630249225288
401.22621.23975630970790-0.001964066054488961.214607756346590.0135563097079032
411.19851.17933959550049-0.003895451686175771.22155585618568-0.0191604044995055
421.20071.17476967771972-0.001142755842568031.22777307812285-0.0259303222802774
431.21381.20115978450187-0.007550084561880781.23399030006001-0.0126402154981289
441.22661.209371761306810.003390236018755751.24043800267444-0.0172282386931912
451.21761.19004373582895-0.001729441117807531.24688570528886-0.0275562641710536
461.22181.19063618535194-0.001542959291259251.25450677393932-0.0311638146480571
471.2491.232938645928620.002933511481611161.26212784258977-0.0160613540713828
481.29911.326944440691970.003182000347286681.268073558960740.0278444406919731
491.34081.399828688340770.007752036327524581.274019275331710.0590286883407667
501.31191.339893129417710.008589669804546871.275317200777740.0279931294177103
511.30141.33420755520624-0.008022681430019081.276615126223780.0328075552062419
521.32011.36924607188081-0.001964066054488961.272917994173680.0491460718808117
531.29381.32227458956260-0.003895451686175771.269220862123580.0284745895625980
541.26941.27972304383652-0.001142755842568031.260219712006050.0103230438365212
551.21651.18933152267336-0.007550084561880781.25121856188852-0.0271684773266354
561.20371.163616335190890.003390236018755751.24039342879035-0.0400836648091101
571.22921.23056114542561-0.001729441117807531.229568295692190.00136114542561483
581.22561.23062341665358-0.001542959291259251.222119542637680.00502341665358341
591.20151.185395698935230.002933511481611161.21467078958316-0.0161043010647699
601.17861.140278433544730.003182000347286681.21373956610799-0.0383215664552727
611.18561.150639621039660.007752036327524581.21280834263281-0.0349603789603383
621.21031.194894046523450.008589669804546871.21711628367200-0.0154059534765498
631.19381.17419845671883-0.008022681430019081.22142422471119-0.0196015432811729
641.2021.17802585745309-0.001964066054488961.2279382086014-0.0239741425469111
651.22711.22364325919457-0.003895451686175771.23445219249161-0.00345674080543268
661.2771.31224957731953-0.001142755842568031.242893178523040.0352495773195254
671.2651.28621592000740-0.007550084561880781.251334164554480.0212159200074040
681.26841.273136257026540.003390236018755751.260273506954710.00473625702653813
691.28111.29471659176287-0.001729441117807531.269212849354940.0136165917628717
701.27271.26925875140074-0.001542959291259251.27768420789052-0.00344124859925921
711.26111.233110922092290.002933511481611161.2861555664261-0.0279890779077121
721.28811.279075867350090.003182000347286681.29394213230263-0.00902413264991497
731.32131.333119265493320.007752036327524581.301728698179160.0118192654933198
741.29991.281234197233930.008589669804546871.30997613296152-0.0186658027660653
751.30741.30459911368614-0.008022681430019081.31822356774388-0.00280088631386244
761.32421.32190944190828-0.001964066054488961.32845462414621-0.00229055809171674
771.35161.36840977113765-0.003895451686175771.338685680548530.0168097711376456
781.35111.35213297902282-0.001142755842568031.351209776819750.00103297902281874
791.34191.32761621147091-0.007550084561880781.36373387309097-0.0142837885290874
801.37161.362001052830170.003390236018755751.37780871115108-0.0095989471698339
811.36221.33424589190662-0.001729441117807531.39188354921119-0.0279541080933805
821.38961.37216434584800-0.001542959291259251.40857861344326-0.0174356541520031
831.42271.417192810843050.002933511481611161.42527367767534-0.00550718915694737
841.46841.489996718075650.003182000347286681.443621281577060.0215967180756518
851.4571.444279078193690.007752036327524581.46196888547879-0.0127209218063109
861.47181.457413095533540.008589669804546871.47759723466191-0.0143869044664597
871.47481.46439709758498-0.008022681430019081.49322558384504-0.0104029024150198
881.55271.60943270876027-0.001964066054488961.497931357294220.056732708760268
891.5751.65125832094277-0.003895451686175771.502637130743400.0762583209427734
901.55571.61827839442782-0.001142755842568031.494264361414750.0625783944278173
911.55531.63225849247578-0.007550084561880781.48589159208610.0769584924757811
921.5771.681952899613150.003390236018755751.468656864368100.104952899613146
931.49751.54530730446771-0.001729441117807531.451422136650100.0478073044677112
941.43691.44568092984733-0.001542959291259251.429662029443930.00878092984732537
951.33221.253564566280620.002933511481611161.40790192223777-0.0786354337193829
961.27321.154525511666640.003182000347286681.38869248798607-0.118674488333357
971.34491.312564909938110.007752036327524581.36948305373437-0.0323350900618937
981.32391.278892766004160.008589669804546871.36031756419130-0.0450072339958449
991.27851.21387060678179-0.008022681430019081.35115207464823-0.064629393218208
1001.3051.25639510072518-0.001964066054488961.35556896532931-0.0486048992748245
1011.3191.28190959567578-0.003895451686175771.3599858560104-0.0370904043242237
1021.3651.35807883132040-0.001142755842568031.37306392452217-0.00692116867959713
1031.40161.42460809152795-0.007550084561880781.386141993033930.02300809152795
1041.40881.416563783820430.003390236018755751.397645980160810.00776378382043186
1051.42681.44617947383011-0.001729441117807531.409149967287690.0193794738301132
1061.45621.50058960115251-0.001542959291259251.413353358138740.0443896011525149
1071.48161.542709739528590.002933511481611161.417556748989790.0611097395285944
1081.49141.568695150905500.003182000347286681.410922848747210.0772951509055015
1091.46141.510759015167850.007752036327524581.404288948504630.049359015167846
1101.42721.455499716817930.008589669804546871.390310613377520.0282997168179329
1111.36861.36889040317961-0.008022681430019081.376332278250410.000290403179607823
1121.35691.35052462391047-0.001964066054488961.36523944214402-0.00637537608953442
1131.34061.33094884564854-0.003895451686175771.35414660603764-0.00965115435145991
1141.25651.16956625543929-0.001142755842568031.34457650040328-0.086933744560713
1151.22081.11414368979295-0.007550084561880781.33500639476893-0.106656310207045
1161.2771.225231402057760.003390236018755751.32537836192348-0.0517685979422375
1171.28941.26477911203977-0.001729441117807531.31575032907804-0.0246208879602297
1181.30671.30786948655402-0.001542959291259251.307073472737240.00116948655401528
1191.38981.478269872121940.002933511481611161.298396616396450.0884698721219381
1201.36611.438060706842120.003182000347286681.290957292810590.0719607068421186

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 0.8973 & 0.87826707316982 & 0.00775203632752458 & 0.908580890502655 & -0.0190329268301795 \tabularnewline
2 & 0.9383 & 0.962004182787066 & 0.00858966980454687 & 0.906006147408387 & 0.0237041827870664 \tabularnewline
3 & 0.9217 & 0.9479912771159 & -0.00802268143001908 & 0.903431404314119 & 0.0262912771159005 \tabularnewline
4 & 0.9095 & 0.91979580081931 & -0.00196406605448896 & 0.901168265235178 & 0.0102958008193107 \tabularnewline
5 & 0.892 & 0.888990325529938 & -0.00389545168617577 & 0.898905126156238 & -0.00300967447006228 \tabularnewline
6 & 0.8742 & 0.852782792587538 & -0.00114275584256803 & 0.89675996325503 & -0.0214172074124621 \tabularnewline
7 & 0.8532 & 0.819335284208058 & -0.00755008456188078 & 0.894614800353822 & -0.0338647157919415 \tabularnewline
8 & 0.8607 & 0.825927567785284 & 0.00339023601875575 & 0.89208219619596 & -0.0347724322147160 \tabularnewline
9 & 0.9005 & 0.913179849079709 & -0.00172944111780753 & 0.889549592038098 & 0.0126798490797091 \tabularnewline
10 & 0.9111 & 0.935880909782224 & -0.00154295929125925 & 0.887862049509035 & 0.0247809097822242 \tabularnewline
11 & 0.9059 & 0.922691981538417 & 0.00293351148161116 & 0.886174506979972 & 0.0167919815384171 \tabularnewline
12 & 0.8883 & 0.88429797737463 & 0.00318200034728668 & 0.889120022278083 & -0.00400202262536997 \tabularnewline
13 & 0.8924 & 0.88498242609628 & 0.00775203632752458 & 0.892065537576195 & -0.00741757390371933 \tabularnewline
14 & 0.8833 & 0.8594847629171 & 0.00858966980454687 & 0.898525567278353 & -0.0238152370828996 \tabularnewline
15 & 0.87 & 0.843037084449508 & -0.00802268143001908 & 0.90498559698051 & -0.0269629155504916 \tabularnewline
16 & 0.8758 & 0.840664612086668 & -0.00196406605448896 & 0.912899453967821 & -0.0351353879133325 \tabularnewline
17 & 0.8858 & 0.854682140731044 & -0.00389545168617577 & 0.920813310955132 & -0.0311178592689565 \tabularnewline
18 & 0.917 & 0.903949834554846 & -0.00114275584256803 & 0.931192921287722 & -0.0130501654451540 \tabularnewline
19 & 0.9554 & 0.976777552941569 & -0.00755008456188078 & 0.941572531620312 & 0.0213775529415688 \tabularnewline
20 & 0.9922 & 1.02536581585112 & 0.00339023601875575 & 0.955643948130123 & 0.0331658158511213 \tabularnewline
21 & 0.9778 & 0.987614076477874 & -0.00172944111780753 & 0.969715364639934 & 0.00981407647787358 \tabularnewline
22 & 0.9808 & 0.97715540473648 & -0.00154295929125925 & 0.985987554554779 & -0.00364459526351957 \tabularnewline
23 & 0.9811 & 0.957006744048765 & 0.00293351148161116 & 1.00225974446962 & -0.0240932559512349 \tabularnewline
24 & 1.0014 & 0.980570966893974 & 0.00318200034728668 & 1.01904703275874 & -0.0208290331060259 \tabularnewline
25 & 1.0183 & 0.99301364262462 & 0.00775203632752458 & 1.03583432104786 & -0.0252863573753797 \tabularnewline
26 & 1.0622 & 1.06464850229789 & 0.00858966980454687 & 1.05116182789756 & 0.00244850229788907 \tabularnewline
27 & 1.0773 & 1.09613334668275 & -0.00802268143001908 & 1.06648933474727 & 0.0188333466827459 \tabularnewline
28 & 1.0807 & 1.08255586169858 & -0.00196406605448896 & 1.08080820435591 & 0.00185586169858087 \tabularnewline
29 & 1.0848 & 1.07836837772163 & -0.00389545168617577 & 1.09512707396454 & -0.00643162227836713 \tabularnewline
30 & 1.1582 & 1.20810873412947 & -0.00114275584256803 & 1.10943402171310 & 0.0499087341294655 \tabularnewline
31 & 1.1663 & 1.21640911510022 & -0.00755008456188078 & 1.12374096946166 & 0.0501091151002186 \tabularnewline
32 & 1.1372 & 1.13278255080149 & 0.00339023601875575 & 1.13822721317975 & -0.00441744919850806 \tabularnewline
33 & 1.1139 & 1.07681598421996 & -0.00172944111780753 & 1.15271345689784 & -0.0370840157800354 \tabularnewline
34 & 1.1222 & 1.08136764237426 & -0.00154295929125925 & 1.164575316917 & -0.0408323576257406 \tabularnewline
35 & 1.1692 & 1.15902931158223 & 0.00293351148161116 & 1.17643717693616 & -0.0101706884177684 \tabularnewline
36 & 1.1702 & 1.15237625048731 & 0.00318200034728668 & 1.18484174916540 & -0.0178237495126898 \tabularnewline
37 & 1.2286 & 1.25620164227783 & 0.00775203632752458 & 1.19324632139465 & 0.0276016422778267 \tabularnewline
38 & 1.2613 & 1.31355734124438 & 0.00858966980454687 & 1.20045298895107 & 0.0522573412443839 \tabularnewline
39 & 1.2646 & 1.32956302492253 & -0.00802268143001908 & 1.20765965650749 & 0.0649630249225288 \tabularnewline
40 & 1.2262 & 1.23975630970790 & -0.00196406605448896 & 1.21460775634659 & 0.0135563097079032 \tabularnewline
41 & 1.1985 & 1.17933959550049 & -0.00389545168617577 & 1.22155585618568 & -0.0191604044995055 \tabularnewline
42 & 1.2007 & 1.17476967771972 & -0.00114275584256803 & 1.22777307812285 & -0.0259303222802774 \tabularnewline
43 & 1.2138 & 1.20115978450187 & -0.00755008456188078 & 1.23399030006001 & -0.0126402154981289 \tabularnewline
44 & 1.2266 & 1.20937176130681 & 0.00339023601875575 & 1.24043800267444 & -0.0172282386931912 \tabularnewline
45 & 1.2176 & 1.19004373582895 & -0.00172944111780753 & 1.24688570528886 & -0.0275562641710536 \tabularnewline
46 & 1.2218 & 1.19063618535194 & -0.00154295929125925 & 1.25450677393932 & -0.0311638146480571 \tabularnewline
47 & 1.249 & 1.23293864592862 & 0.00293351148161116 & 1.26212784258977 & -0.0160613540713828 \tabularnewline
48 & 1.2991 & 1.32694444069197 & 0.00318200034728668 & 1.26807355896074 & 0.0278444406919731 \tabularnewline
49 & 1.3408 & 1.39982868834077 & 0.00775203632752458 & 1.27401927533171 & 0.0590286883407667 \tabularnewline
50 & 1.3119 & 1.33989312941771 & 0.00858966980454687 & 1.27531720077774 & 0.0279931294177103 \tabularnewline
51 & 1.3014 & 1.33420755520624 & -0.00802268143001908 & 1.27661512622378 & 0.0328075552062419 \tabularnewline
52 & 1.3201 & 1.36924607188081 & -0.00196406605448896 & 1.27291799417368 & 0.0491460718808117 \tabularnewline
53 & 1.2938 & 1.32227458956260 & -0.00389545168617577 & 1.26922086212358 & 0.0284745895625980 \tabularnewline
54 & 1.2694 & 1.27972304383652 & -0.00114275584256803 & 1.26021971200605 & 0.0103230438365212 \tabularnewline
55 & 1.2165 & 1.18933152267336 & -0.00755008456188078 & 1.25121856188852 & -0.0271684773266354 \tabularnewline
56 & 1.2037 & 1.16361633519089 & 0.00339023601875575 & 1.24039342879035 & -0.0400836648091101 \tabularnewline
57 & 1.2292 & 1.23056114542561 & -0.00172944111780753 & 1.22956829569219 & 0.00136114542561483 \tabularnewline
58 & 1.2256 & 1.23062341665358 & -0.00154295929125925 & 1.22211954263768 & 0.00502341665358341 \tabularnewline
59 & 1.2015 & 1.18539569893523 & 0.00293351148161116 & 1.21467078958316 & -0.0161043010647699 \tabularnewline
60 & 1.1786 & 1.14027843354473 & 0.00318200034728668 & 1.21373956610799 & -0.0383215664552727 \tabularnewline
61 & 1.1856 & 1.15063962103966 & 0.00775203632752458 & 1.21280834263281 & -0.0349603789603383 \tabularnewline
62 & 1.2103 & 1.19489404652345 & 0.00858966980454687 & 1.21711628367200 & -0.0154059534765498 \tabularnewline
63 & 1.1938 & 1.17419845671883 & -0.00802268143001908 & 1.22142422471119 & -0.0196015432811729 \tabularnewline
64 & 1.202 & 1.17802585745309 & -0.00196406605448896 & 1.2279382086014 & -0.0239741425469111 \tabularnewline
65 & 1.2271 & 1.22364325919457 & -0.00389545168617577 & 1.23445219249161 & -0.00345674080543268 \tabularnewline
66 & 1.277 & 1.31224957731953 & -0.00114275584256803 & 1.24289317852304 & 0.0352495773195254 \tabularnewline
67 & 1.265 & 1.28621592000740 & -0.00755008456188078 & 1.25133416455448 & 0.0212159200074040 \tabularnewline
68 & 1.2684 & 1.27313625702654 & 0.00339023601875575 & 1.26027350695471 & 0.00473625702653813 \tabularnewline
69 & 1.2811 & 1.29471659176287 & -0.00172944111780753 & 1.26921284935494 & 0.0136165917628717 \tabularnewline
70 & 1.2727 & 1.26925875140074 & -0.00154295929125925 & 1.27768420789052 & -0.00344124859925921 \tabularnewline
71 & 1.2611 & 1.23311092209229 & 0.00293351148161116 & 1.2861555664261 & -0.0279890779077121 \tabularnewline
72 & 1.2881 & 1.27907586735009 & 0.00318200034728668 & 1.29394213230263 & -0.00902413264991497 \tabularnewline
73 & 1.3213 & 1.33311926549332 & 0.00775203632752458 & 1.30172869817916 & 0.0118192654933198 \tabularnewline
74 & 1.2999 & 1.28123419723393 & 0.00858966980454687 & 1.30997613296152 & -0.0186658027660653 \tabularnewline
75 & 1.3074 & 1.30459911368614 & -0.00802268143001908 & 1.31822356774388 & -0.00280088631386244 \tabularnewline
76 & 1.3242 & 1.32190944190828 & -0.00196406605448896 & 1.32845462414621 & -0.00229055809171674 \tabularnewline
77 & 1.3516 & 1.36840977113765 & -0.00389545168617577 & 1.33868568054853 & 0.0168097711376456 \tabularnewline
78 & 1.3511 & 1.35213297902282 & -0.00114275584256803 & 1.35120977681975 & 0.00103297902281874 \tabularnewline
79 & 1.3419 & 1.32761621147091 & -0.00755008456188078 & 1.36373387309097 & -0.0142837885290874 \tabularnewline
80 & 1.3716 & 1.36200105283017 & 0.00339023601875575 & 1.37780871115108 & -0.0095989471698339 \tabularnewline
81 & 1.3622 & 1.33424589190662 & -0.00172944111780753 & 1.39188354921119 & -0.0279541080933805 \tabularnewline
82 & 1.3896 & 1.37216434584800 & -0.00154295929125925 & 1.40857861344326 & -0.0174356541520031 \tabularnewline
83 & 1.4227 & 1.41719281084305 & 0.00293351148161116 & 1.42527367767534 & -0.00550718915694737 \tabularnewline
84 & 1.4684 & 1.48999671807565 & 0.00318200034728668 & 1.44362128157706 & 0.0215967180756518 \tabularnewline
85 & 1.457 & 1.44427907819369 & 0.00775203632752458 & 1.46196888547879 & -0.0127209218063109 \tabularnewline
86 & 1.4718 & 1.45741309553354 & 0.00858966980454687 & 1.47759723466191 & -0.0143869044664597 \tabularnewline
87 & 1.4748 & 1.46439709758498 & -0.00802268143001908 & 1.49322558384504 & -0.0104029024150198 \tabularnewline
88 & 1.5527 & 1.60943270876027 & -0.00196406605448896 & 1.49793135729422 & 0.056732708760268 \tabularnewline
89 & 1.575 & 1.65125832094277 & -0.00389545168617577 & 1.50263713074340 & 0.0762583209427734 \tabularnewline
90 & 1.5557 & 1.61827839442782 & -0.00114275584256803 & 1.49426436141475 & 0.0625783944278173 \tabularnewline
91 & 1.5553 & 1.63225849247578 & -0.00755008456188078 & 1.4858915920861 & 0.0769584924757811 \tabularnewline
92 & 1.577 & 1.68195289961315 & 0.00339023601875575 & 1.46865686436810 & 0.104952899613146 \tabularnewline
93 & 1.4975 & 1.54530730446771 & -0.00172944111780753 & 1.45142213665010 & 0.0478073044677112 \tabularnewline
94 & 1.4369 & 1.44568092984733 & -0.00154295929125925 & 1.42966202944393 & 0.00878092984732537 \tabularnewline
95 & 1.3322 & 1.25356456628062 & 0.00293351148161116 & 1.40790192223777 & -0.0786354337193829 \tabularnewline
96 & 1.2732 & 1.15452551166664 & 0.00318200034728668 & 1.38869248798607 & -0.118674488333357 \tabularnewline
97 & 1.3449 & 1.31256490993811 & 0.00775203632752458 & 1.36948305373437 & -0.0323350900618937 \tabularnewline
98 & 1.3239 & 1.27889276600416 & 0.00858966980454687 & 1.36031756419130 & -0.0450072339958449 \tabularnewline
99 & 1.2785 & 1.21387060678179 & -0.00802268143001908 & 1.35115207464823 & -0.064629393218208 \tabularnewline
100 & 1.305 & 1.25639510072518 & -0.00196406605448896 & 1.35556896532931 & -0.0486048992748245 \tabularnewline
101 & 1.319 & 1.28190959567578 & -0.00389545168617577 & 1.3599858560104 & -0.0370904043242237 \tabularnewline
102 & 1.365 & 1.35807883132040 & -0.00114275584256803 & 1.37306392452217 & -0.00692116867959713 \tabularnewline
103 & 1.4016 & 1.42460809152795 & -0.00755008456188078 & 1.38614199303393 & 0.02300809152795 \tabularnewline
104 & 1.4088 & 1.41656378382043 & 0.00339023601875575 & 1.39764598016081 & 0.00776378382043186 \tabularnewline
105 & 1.4268 & 1.44617947383011 & -0.00172944111780753 & 1.40914996728769 & 0.0193794738301132 \tabularnewline
106 & 1.4562 & 1.50058960115251 & -0.00154295929125925 & 1.41335335813874 & 0.0443896011525149 \tabularnewline
107 & 1.4816 & 1.54270973952859 & 0.00293351148161116 & 1.41755674898979 & 0.0611097395285944 \tabularnewline
108 & 1.4914 & 1.56869515090550 & 0.00318200034728668 & 1.41092284874721 & 0.0772951509055015 \tabularnewline
109 & 1.4614 & 1.51075901516785 & 0.00775203632752458 & 1.40428894850463 & 0.049359015167846 \tabularnewline
110 & 1.4272 & 1.45549971681793 & 0.00858966980454687 & 1.39031061337752 & 0.0282997168179329 \tabularnewline
111 & 1.3686 & 1.36889040317961 & -0.00802268143001908 & 1.37633227825041 & 0.000290403179607823 \tabularnewline
112 & 1.3569 & 1.35052462391047 & -0.00196406605448896 & 1.36523944214402 & -0.00637537608953442 \tabularnewline
113 & 1.3406 & 1.33094884564854 & -0.00389545168617577 & 1.35414660603764 & -0.00965115435145991 \tabularnewline
114 & 1.2565 & 1.16956625543929 & -0.00114275584256803 & 1.34457650040328 & -0.086933744560713 \tabularnewline
115 & 1.2208 & 1.11414368979295 & -0.00755008456188078 & 1.33500639476893 & -0.106656310207045 \tabularnewline
116 & 1.277 & 1.22523140205776 & 0.00339023601875575 & 1.32537836192348 & -0.0517685979422375 \tabularnewline
117 & 1.2894 & 1.26477911203977 & -0.00172944111780753 & 1.31575032907804 & -0.0246208879602297 \tabularnewline
118 & 1.3067 & 1.30786948655402 & -0.00154295929125925 & 1.30707347273724 & 0.00116948655401528 \tabularnewline
119 & 1.3898 & 1.47826987212194 & 0.00293351148161116 & 1.29839661639645 & 0.0884698721219381 \tabularnewline
120 & 1.3661 & 1.43806070684212 & 0.00318200034728668 & 1.29095729281059 & 0.0719607068421186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115578&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]0.8973[/C][C]0.87826707316982[/C][C]0.00775203632752458[/C][C]0.908580890502655[/C][C]-0.0190329268301795[/C][/ROW]
[ROW][C]2[/C][C]0.9383[/C][C]0.962004182787066[/C][C]0.00858966980454687[/C][C]0.906006147408387[/C][C]0.0237041827870664[/C][/ROW]
[ROW][C]3[/C][C]0.9217[/C][C]0.9479912771159[/C][C]-0.00802268143001908[/C][C]0.903431404314119[/C][C]0.0262912771159005[/C][/ROW]
[ROW][C]4[/C][C]0.9095[/C][C]0.91979580081931[/C][C]-0.00196406605448896[/C][C]0.901168265235178[/C][C]0.0102958008193107[/C][/ROW]
[ROW][C]5[/C][C]0.892[/C][C]0.888990325529938[/C][C]-0.00389545168617577[/C][C]0.898905126156238[/C][C]-0.00300967447006228[/C][/ROW]
[ROW][C]6[/C][C]0.8742[/C][C]0.852782792587538[/C][C]-0.00114275584256803[/C][C]0.89675996325503[/C][C]-0.0214172074124621[/C][/ROW]
[ROW][C]7[/C][C]0.8532[/C][C]0.819335284208058[/C][C]-0.00755008456188078[/C][C]0.894614800353822[/C][C]-0.0338647157919415[/C][/ROW]
[ROW][C]8[/C][C]0.8607[/C][C]0.825927567785284[/C][C]0.00339023601875575[/C][C]0.89208219619596[/C][C]-0.0347724322147160[/C][/ROW]
[ROW][C]9[/C][C]0.9005[/C][C]0.913179849079709[/C][C]-0.00172944111780753[/C][C]0.889549592038098[/C][C]0.0126798490797091[/C][/ROW]
[ROW][C]10[/C][C]0.9111[/C][C]0.935880909782224[/C][C]-0.00154295929125925[/C][C]0.887862049509035[/C][C]0.0247809097822242[/C][/ROW]
[ROW][C]11[/C][C]0.9059[/C][C]0.922691981538417[/C][C]0.00293351148161116[/C][C]0.886174506979972[/C][C]0.0167919815384171[/C][/ROW]
[ROW][C]12[/C][C]0.8883[/C][C]0.88429797737463[/C][C]0.00318200034728668[/C][C]0.889120022278083[/C][C]-0.00400202262536997[/C][/ROW]
[ROW][C]13[/C][C]0.8924[/C][C]0.88498242609628[/C][C]0.00775203632752458[/C][C]0.892065537576195[/C][C]-0.00741757390371933[/C][/ROW]
[ROW][C]14[/C][C]0.8833[/C][C]0.8594847629171[/C][C]0.00858966980454687[/C][C]0.898525567278353[/C][C]-0.0238152370828996[/C][/ROW]
[ROW][C]15[/C][C]0.87[/C][C]0.843037084449508[/C][C]-0.00802268143001908[/C][C]0.90498559698051[/C][C]-0.0269629155504916[/C][/ROW]
[ROW][C]16[/C][C]0.8758[/C][C]0.840664612086668[/C][C]-0.00196406605448896[/C][C]0.912899453967821[/C][C]-0.0351353879133325[/C][/ROW]
[ROW][C]17[/C][C]0.8858[/C][C]0.854682140731044[/C][C]-0.00389545168617577[/C][C]0.920813310955132[/C][C]-0.0311178592689565[/C][/ROW]
[ROW][C]18[/C][C]0.917[/C][C]0.903949834554846[/C][C]-0.00114275584256803[/C][C]0.931192921287722[/C][C]-0.0130501654451540[/C][/ROW]
[ROW][C]19[/C][C]0.9554[/C][C]0.976777552941569[/C][C]-0.00755008456188078[/C][C]0.941572531620312[/C][C]0.0213775529415688[/C][/ROW]
[ROW][C]20[/C][C]0.9922[/C][C]1.02536581585112[/C][C]0.00339023601875575[/C][C]0.955643948130123[/C][C]0.0331658158511213[/C][/ROW]
[ROW][C]21[/C][C]0.9778[/C][C]0.987614076477874[/C][C]-0.00172944111780753[/C][C]0.969715364639934[/C][C]0.00981407647787358[/C][/ROW]
[ROW][C]22[/C][C]0.9808[/C][C]0.97715540473648[/C][C]-0.00154295929125925[/C][C]0.985987554554779[/C][C]-0.00364459526351957[/C][/ROW]
[ROW][C]23[/C][C]0.9811[/C][C]0.957006744048765[/C][C]0.00293351148161116[/C][C]1.00225974446962[/C][C]-0.0240932559512349[/C][/ROW]
[ROW][C]24[/C][C]1.0014[/C][C]0.980570966893974[/C][C]0.00318200034728668[/C][C]1.01904703275874[/C][C]-0.0208290331060259[/C][/ROW]
[ROW][C]25[/C][C]1.0183[/C][C]0.99301364262462[/C][C]0.00775203632752458[/C][C]1.03583432104786[/C][C]-0.0252863573753797[/C][/ROW]
[ROW][C]26[/C][C]1.0622[/C][C]1.06464850229789[/C][C]0.00858966980454687[/C][C]1.05116182789756[/C][C]0.00244850229788907[/C][/ROW]
[ROW][C]27[/C][C]1.0773[/C][C]1.09613334668275[/C][C]-0.00802268143001908[/C][C]1.06648933474727[/C][C]0.0188333466827459[/C][/ROW]
[ROW][C]28[/C][C]1.0807[/C][C]1.08255586169858[/C][C]-0.00196406605448896[/C][C]1.08080820435591[/C][C]0.00185586169858087[/C][/ROW]
[ROW][C]29[/C][C]1.0848[/C][C]1.07836837772163[/C][C]-0.00389545168617577[/C][C]1.09512707396454[/C][C]-0.00643162227836713[/C][/ROW]
[ROW][C]30[/C][C]1.1582[/C][C]1.20810873412947[/C][C]-0.00114275584256803[/C][C]1.10943402171310[/C][C]0.0499087341294655[/C][/ROW]
[ROW][C]31[/C][C]1.1663[/C][C]1.21640911510022[/C][C]-0.00755008456188078[/C][C]1.12374096946166[/C][C]0.0501091151002186[/C][/ROW]
[ROW][C]32[/C][C]1.1372[/C][C]1.13278255080149[/C][C]0.00339023601875575[/C][C]1.13822721317975[/C][C]-0.00441744919850806[/C][/ROW]
[ROW][C]33[/C][C]1.1139[/C][C]1.07681598421996[/C][C]-0.00172944111780753[/C][C]1.15271345689784[/C][C]-0.0370840157800354[/C][/ROW]
[ROW][C]34[/C][C]1.1222[/C][C]1.08136764237426[/C][C]-0.00154295929125925[/C][C]1.164575316917[/C][C]-0.0408323576257406[/C][/ROW]
[ROW][C]35[/C][C]1.1692[/C][C]1.15902931158223[/C][C]0.00293351148161116[/C][C]1.17643717693616[/C][C]-0.0101706884177684[/C][/ROW]
[ROW][C]36[/C][C]1.1702[/C][C]1.15237625048731[/C][C]0.00318200034728668[/C][C]1.18484174916540[/C][C]-0.0178237495126898[/C][/ROW]
[ROW][C]37[/C][C]1.2286[/C][C]1.25620164227783[/C][C]0.00775203632752458[/C][C]1.19324632139465[/C][C]0.0276016422778267[/C][/ROW]
[ROW][C]38[/C][C]1.2613[/C][C]1.31355734124438[/C][C]0.00858966980454687[/C][C]1.20045298895107[/C][C]0.0522573412443839[/C][/ROW]
[ROW][C]39[/C][C]1.2646[/C][C]1.32956302492253[/C][C]-0.00802268143001908[/C][C]1.20765965650749[/C][C]0.0649630249225288[/C][/ROW]
[ROW][C]40[/C][C]1.2262[/C][C]1.23975630970790[/C][C]-0.00196406605448896[/C][C]1.21460775634659[/C][C]0.0135563097079032[/C][/ROW]
[ROW][C]41[/C][C]1.1985[/C][C]1.17933959550049[/C][C]-0.00389545168617577[/C][C]1.22155585618568[/C][C]-0.0191604044995055[/C][/ROW]
[ROW][C]42[/C][C]1.2007[/C][C]1.17476967771972[/C][C]-0.00114275584256803[/C][C]1.22777307812285[/C][C]-0.0259303222802774[/C][/ROW]
[ROW][C]43[/C][C]1.2138[/C][C]1.20115978450187[/C][C]-0.00755008456188078[/C][C]1.23399030006001[/C][C]-0.0126402154981289[/C][/ROW]
[ROW][C]44[/C][C]1.2266[/C][C]1.20937176130681[/C][C]0.00339023601875575[/C][C]1.24043800267444[/C][C]-0.0172282386931912[/C][/ROW]
[ROW][C]45[/C][C]1.2176[/C][C]1.19004373582895[/C][C]-0.00172944111780753[/C][C]1.24688570528886[/C][C]-0.0275562641710536[/C][/ROW]
[ROW][C]46[/C][C]1.2218[/C][C]1.19063618535194[/C][C]-0.00154295929125925[/C][C]1.25450677393932[/C][C]-0.0311638146480571[/C][/ROW]
[ROW][C]47[/C][C]1.249[/C][C]1.23293864592862[/C][C]0.00293351148161116[/C][C]1.26212784258977[/C][C]-0.0160613540713828[/C][/ROW]
[ROW][C]48[/C][C]1.2991[/C][C]1.32694444069197[/C][C]0.00318200034728668[/C][C]1.26807355896074[/C][C]0.0278444406919731[/C][/ROW]
[ROW][C]49[/C][C]1.3408[/C][C]1.39982868834077[/C][C]0.00775203632752458[/C][C]1.27401927533171[/C][C]0.0590286883407667[/C][/ROW]
[ROW][C]50[/C][C]1.3119[/C][C]1.33989312941771[/C][C]0.00858966980454687[/C][C]1.27531720077774[/C][C]0.0279931294177103[/C][/ROW]
[ROW][C]51[/C][C]1.3014[/C][C]1.33420755520624[/C][C]-0.00802268143001908[/C][C]1.27661512622378[/C][C]0.0328075552062419[/C][/ROW]
[ROW][C]52[/C][C]1.3201[/C][C]1.36924607188081[/C][C]-0.00196406605448896[/C][C]1.27291799417368[/C][C]0.0491460718808117[/C][/ROW]
[ROW][C]53[/C][C]1.2938[/C][C]1.32227458956260[/C][C]-0.00389545168617577[/C][C]1.26922086212358[/C][C]0.0284745895625980[/C][/ROW]
[ROW][C]54[/C][C]1.2694[/C][C]1.27972304383652[/C][C]-0.00114275584256803[/C][C]1.26021971200605[/C][C]0.0103230438365212[/C][/ROW]
[ROW][C]55[/C][C]1.2165[/C][C]1.18933152267336[/C][C]-0.00755008456188078[/C][C]1.25121856188852[/C][C]-0.0271684773266354[/C][/ROW]
[ROW][C]56[/C][C]1.2037[/C][C]1.16361633519089[/C][C]0.00339023601875575[/C][C]1.24039342879035[/C][C]-0.0400836648091101[/C][/ROW]
[ROW][C]57[/C][C]1.2292[/C][C]1.23056114542561[/C][C]-0.00172944111780753[/C][C]1.22956829569219[/C][C]0.00136114542561483[/C][/ROW]
[ROW][C]58[/C][C]1.2256[/C][C]1.23062341665358[/C][C]-0.00154295929125925[/C][C]1.22211954263768[/C][C]0.00502341665358341[/C][/ROW]
[ROW][C]59[/C][C]1.2015[/C][C]1.18539569893523[/C][C]0.00293351148161116[/C][C]1.21467078958316[/C][C]-0.0161043010647699[/C][/ROW]
[ROW][C]60[/C][C]1.1786[/C][C]1.14027843354473[/C][C]0.00318200034728668[/C][C]1.21373956610799[/C][C]-0.0383215664552727[/C][/ROW]
[ROW][C]61[/C][C]1.1856[/C][C]1.15063962103966[/C][C]0.00775203632752458[/C][C]1.21280834263281[/C][C]-0.0349603789603383[/C][/ROW]
[ROW][C]62[/C][C]1.2103[/C][C]1.19489404652345[/C][C]0.00858966980454687[/C][C]1.21711628367200[/C][C]-0.0154059534765498[/C][/ROW]
[ROW][C]63[/C][C]1.1938[/C][C]1.17419845671883[/C][C]-0.00802268143001908[/C][C]1.22142422471119[/C][C]-0.0196015432811729[/C][/ROW]
[ROW][C]64[/C][C]1.202[/C][C]1.17802585745309[/C][C]-0.00196406605448896[/C][C]1.2279382086014[/C][C]-0.0239741425469111[/C][/ROW]
[ROW][C]65[/C][C]1.2271[/C][C]1.22364325919457[/C][C]-0.00389545168617577[/C][C]1.23445219249161[/C][C]-0.00345674080543268[/C][/ROW]
[ROW][C]66[/C][C]1.277[/C][C]1.31224957731953[/C][C]-0.00114275584256803[/C][C]1.24289317852304[/C][C]0.0352495773195254[/C][/ROW]
[ROW][C]67[/C][C]1.265[/C][C]1.28621592000740[/C][C]-0.00755008456188078[/C][C]1.25133416455448[/C][C]0.0212159200074040[/C][/ROW]
[ROW][C]68[/C][C]1.2684[/C][C]1.27313625702654[/C][C]0.00339023601875575[/C][C]1.26027350695471[/C][C]0.00473625702653813[/C][/ROW]
[ROW][C]69[/C][C]1.2811[/C][C]1.29471659176287[/C][C]-0.00172944111780753[/C][C]1.26921284935494[/C][C]0.0136165917628717[/C][/ROW]
[ROW][C]70[/C][C]1.2727[/C][C]1.26925875140074[/C][C]-0.00154295929125925[/C][C]1.27768420789052[/C][C]-0.00344124859925921[/C][/ROW]
[ROW][C]71[/C][C]1.2611[/C][C]1.23311092209229[/C][C]0.00293351148161116[/C][C]1.2861555664261[/C][C]-0.0279890779077121[/C][/ROW]
[ROW][C]72[/C][C]1.2881[/C][C]1.27907586735009[/C][C]0.00318200034728668[/C][C]1.29394213230263[/C][C]-0.00902413264991497[/C][/ROW]
[ROW][C]73[/C][C]1.3213[/C][C]1.33311926549332[/C][C]0.00775203632752458[/C][C]1.30172869817916[/C][C]0.0118192654933198[/C][/ROW]
[ROW][C]74[/C][C]1.2999[/C][C]1.28123419723393[/C][C]0.00858966980454687[/C][C]1.30997613296152[/C][C]-0.0186658027660653[/C][/ROW]
[ROW][C]75[/C][C]1.3074[/C][C]1.30459911368614[/C][C]-0.00802268143001908[/C][C]1.31822356774388[/C][C]-0.00280088631386244[/C][/ROW]
[ROW][C]76[/C][C]1.3242[/C][C]1.32190944190828[/C][C]-0.00196406605448896[/C][C]1.32845462414621[/C][C]-0.00229055809171674[/C][/ROW]
[ROW][C]77[/C][C]1.3516[/C][C]1.36840977113765[/C][C]-0.00389545168617577[/C][C]1.33868568054853[/C][C]0.0168097711376456[/C][/ROW]
[ROW][C]78[/C][C]1.3511[/C][C]1.35213297902282[/C][C]-0.00114275584256803[/C][C]1.35120977681975[/C][C]0.00103297902281874[/C][/ROW]
[ROW][C]79[/C][C]1.3419[/C][C]1.32761621147091[/C][C]-0.00755008456188078[/C][C]1.36373387309097[/C][C]-0.0142837885290874[/C][/ROW]
[ROW][C]80[/C][C]1.3716[/C][C]1.36200105283017[/C][C]0.00339023601875575[/C][C]1.37780871115108[/C][C]-0.0095989471698339[/C][/ROW]
[ROW][C]81[/C][C]1.3622[/C][C]1.33424589190662[/C][C]-0.00172944111780753[/C][C]1.39188354921119[/C][C]-0.0279541080933805[/C][/ROW]
[ROW][C]82[/C][C]1.3896[/C][C]1.37216434584800[/C][C]-0.00154295929125925[/C][C]1.40857861344326[/C][C]-0.0174356541520031[/C][/ROW]
[ROW][C]83[/C][C]1.4227[/C][C]1.41719281084305[/C][C]0.00293351148161116[/C][C]1.42527367767534[/C][C]-0.00550718915694737[/C][/ROW]
[ROW][C]84[/C][C]1.4684[/C][C]1.48999671807565[/C][C]0.00318200034728668[/C][C]1.44362128157706[/C][C]0.0215967180756518[/C][/ROW]
[ROW][C]85[/C][C]1.457[/C][C]1.44427907819369[/C][C]0.00775203632752458[/C][C]1.46196888547879[/C][C]-0.0127209218063109[/C][/ROW]
[ROW][C]86[/C][C]1.4718[/C][C]1.45741309553354[/C][C]0.00858966980454687[/C][C]1.47759723466191[/C][C]-0.0143869044664597[/C][/ROW]
[ROW][C]87[/C][C]1.4748[/C][C]1.46439709758498[/C][C]-0.00802268143001908[/C][C]1.49322558384504[/C][C]-0.0104029024150198[/C][/ROW]
[ROW][C]88[/C][C]1.5527[/C][C]1.60943270876027[/C][C]-0.00196406605448896[/C][C]1.49793135729422[/C][C]0.056732708760268[/C][/ROW]
[ROW][C]89[/C][C]1.575[/C][C]1.65125832094277[/C][C]-0.00389545168617577[/C][C]1.50263713074340[/C][C]0.0762583209427734[/C][/ROW]
[ROW][C]90[/C][C]1.5557[/C][C]1.61827839442782[/C][C]-0.00114275584256803[/C][C]1.49426436141475[/C][C]0.0625783944278173[/C][/ROW]
[ROW][C]91[/C][C]1.5553[/C][C]1.63225849247578[/C][C]-0.00755008456188078[/C][C]1.4858915920861[/C][C]0.0769584924757811[/C][/ROW]
[ROW][C]92[/C][C]1.577[/C][C]1.68195289961315[/C][C]0.00339023601875575[/C][C]1.46865686436810[/C][C]0.104952899613146[/C][/ROW]
[ROW][C]93[/C][C]1.4975[/C][C]1.54530730446771[/C][C]-0.00172944111780753[/C][C]1.45142213665010[/C][C]0.0478073044677112[/C][/ROW]
[ROW][C]94[/C][C]1.4369[/C][C]1.44568092984733[/C][C]-0.00154295929125925[/C][C]1.42966202944393[/C][C]0.00878092984732537[/C][/ROW]
[ROW][C]95[/C][C]1.3322[/C][C]1.25356456628062[/C][C]0.00293351148161116[/C][C]1.40790192223777[/C][C]-0.0786354337193829[/C][/ROW]
[ROW][C]96[/C][C]1.2732[/C][C]1.15452551166664[/C][C]0.00318200034728668[/C][C]1.38869248798607[/C][C]-0.118674488333357[/C][/ROW]
[ROW][C]97[/C][C]1.3449[/C][C]1.31256490993811[/C][C]0.00775203632752458[/C][C]1.36948305373437[/C][C]-0.0323350900618937[/C][/ROW]
[ROW][C]98[/C][C]1.3239[/C][C]1.27889276600416[/C][C]0.00858966980454687[/C][C]1.36031756419130[/C][C]-0.0450072339958449[/C][/ROW]
[ROW][C]99[/C][C]1.2785[/C][C]1.21387060678179[/C][C]-0.00802268143001908[/C][C]1.35115207464823[/C][C]-0.064629393218208[/C][/ROW]
[ROW][C]100[/C][C]1.305[/C][C]1.25639510072518[/C][C]-0.00196406605448896[/C][C]1.35556896532931[/C][C]-0.0486048992748245[/C][/ROW]
[ROW][C]101[/C][C]1.319[/C][C]1.28190959567578[/C][C]-0.00389545168617577[/C][C]1.3599858560104[/C][C]-0.0370904043242237[/C][/ROW]
[ROW][C]102[/C][C]1.365[/C][C]1.35807883132040[/C][C]-0.00114275584256803[/C][C]1.37306392452217[/C][C]-0.00692116867959713[/C][/ROW]
[ROW][C]103[/C][C]1.4016[/C][C]1.42460809152795[/C][C]-0.00755008456188078[/C][C]1.38614199303393[/C][C]0.02300809152795[/C][/ROW]
[ROW][C]104[/C][C]1.4088[/C][C]1.41656378382043[/C][C]0.00339023601875575[/C][C]1.39764598016081[/C][C]0.00776378382043186[/C][/ROW]
[ROW][C]105[/C][C]1.4268[/C][C]1.44617947383011[/C][C]-0.00172944111780753[/C][C]1.40914996728769[/C][C]0.0193794738301132[/C][/ROW]
[ROW][C]106[/C][C]1.4562[/C][C]1.50058960115251[/C][C]-0.00154295929125925[/C][C]1.41335335813874[/C][C]0.0443896011525149[/C][/ROW]
[ROW][C]107[/C][C]1.4816[/C][C]1.54270973952859[/C][C]0.00293351148161116[/C][C]1.41755674898979[/C][C]0.0611097395285944[/C][/ROW]
[ROW][C]108[/C][C]1.4914[/C][C]1.56869515090550[/C][C]0.00318200034728668[/C][C]1.41092284874721[/C][C]0.0772951509055015[/C][/ROW]
[ROW][C]109[/C][C]1.4614[/C][C]1.51075901516785[/C][C]0.00775203632752458[/C][C]1.40428894850463[/C][C]0.049359015167846[/C][/ROW]
[ROW][C]110[/C][C]1.4272[/C][C]1.45549971681793[/C][C]0.00858966980454687[/C][C]1.39031061337752[/C][C]0.0282997168179329[/C][/ROW]
[ROW][C]111[/C][C]1.3686[/C][C]1.36889040317961[/C][C]-0.00802268143001908[/C][C]1.37633227825041[/C][C]0.000290403179607823[/C][/ROW]
[ROW][C]112[/C][C]1.3569[/C][C]1.35052462391047[/C][C]-0.00196406605448896[/C][C]1.36523944214402[/C][C]-0.00637537608953442[/C][/ROW]
[ROW][C]113[/C][C]1.3406[/C][C]1.33094884564854[/C][C]-0.00389545168617577[/C][C]1.35414660603764[/C][C]-0.00965115435145991[/C][/ROW]
[ROW][C]114[/C][C]1.2565[/C][C]1.16956625543929[/C][C]-0.00114275584256803[/C][C]1.34457650040328[/C][C]-0.086933744560713[/C][/ROW]
[ROW][C]115[/C][C]1.2208[/C][C]1.11414368979295[/C][C]-0.00755008456188078[/C][C]1.33500639476893[/C][C]-0.106656310207045[/C][/ROW]
[ROW][C]116[/C][C]1.277[/C][C]1.22523140205776[/C][C]0.00339023601875575[/C][C]1.32537836192348[/C][C]-0.0517685979422375[/C][/ROW]
[ROW][C]117[/C][C]1.2894[/C][C]1.26477911203977[/C][C]-0.00172944111780753[/C][C]1.31575032907804[/C][C]-0.0246208879602297[/C][/ROW]
[ROW][C]118[/C][C]1.3067[/C][C]1.30786948655402[/C][C]-0.00154295929125925[/C][C]1.30707347273724[/C][C]0.00116948655401528[/C][/ROW]
[ROW][C]119[/C][C]1.3898[/C][C]1.47826987212194[/C][C]0.00293351148161116[/C][C]1.29839661639645[/C][C]0.0884698721219381[/C][/ROW]
[ROW][C]120[/C][C]1.3661[/C][C]1.43806070684212[/C][C]0.00318200034728668[/C][C]1.29095729281059[/C][C]0.0719607068421186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115578&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115578&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
10.89730.878267073169820.007752036327524580.908580890502655-0.0190329268301795
20.93830.9620041827870660.008589669804546870.9060061474083870.0237041827870664
30.92170.9479912771159-0.008022681430019080.9034314043141190.0262912771159005
40.90950.91979580081931-0.001964066054488960.9011682652351780.0102958008193107
50.8920.888990325529938-0.003895451686175770.898905126156238-0.00300967447006228
60.87420.852782792587538-0.001142755842568030.89675996325503-0.0214172074124621
70.85320.819335284208058-0.007550084561880780.894614800353822-0.0338647157919415
80.86070.8259275677852840.003390236018755750.89208219619596-0.0347724322147160
90.90050.913179849079709-0.001729441117807530.8895495920380980.0126798490797091
100.91110.935880909782224-0.001542959291259250.8878620495090350.0247809097822242
110.90590.9226919815384170.002933511481611160.8861745069799720.0167919815384171
120.88830.884297977374630.003182000347286680.889120022278083-0.00400202262536997
130.89240.884982426096280.007752036327524580.892065537576195-0.00741757390371933
140.88330.85948476291710.008589669804546870.898525567278353-0.0238152370828996
150.870.843037084449508-0.008022681430019080.90498559698051-0.0269629155504916
160.87580.840664612086668-0.001964066054488960.912899453967821-0.0351353879133325
170.88580.854682140731044-0.003895451686175770.920813310955132-0.0311178592689565
180.9170.903949834554846-0.001142755842568030.931192921287722-0.0130501654451540
190.95540.976777552941569-0.007550084561880780.9415725316203120.0213775529415688
200.99221.025365815851120.003390236018755750.9556439481301230.0331658158511213
210.97780.987614076477874-0.001729441117807530.9697153646399340.00981407647787358
220.98080.97715540473648-0.001542959291259250.985987554554779-0.00364459526351957
230.98110.9570067440487650.002933511481611161.00225974446962-0.0240932559512349
241.00140.9805709668939740.003182000347286681.01904703275874-0.0208290331060259
251.01830.993013642624620.007752036327524581.03583432104786-0.0252863573753797
261.06221.064648502297890.008589669804546871.051161827897560.00244850229788907
271.07731.09613334668275-0.008022681430019081.066489334747270.0188333466827459
281.08071.08255586169858-0.001964066054488961.080808204355910.00185586169858087
291.08481.07836837772163-0.003895451686175771.09512707396454-0.00643162227836713
301.15821.20810873412947-0.001142755842568031.109434021713100.0499087341294655
311.16631.21640911510022-0.007550084561880781.123740969461660.0501091151002186
321.13721.132782550801490.003390236018755751.13822721317975-0.00441744919850806
331.11391.07681598421996-0.001729441117807531.15271345689784-0.0370840157800354
341.12221.08136764237426-0.001542959291259251.164575316917-0.0408323576257406
351.16921.159029311582230.002933511481611161.17643717693616-0.0101706884177684
361.17021.152376250487310.003182000347286681.18484174916540-0.0178237495126898
371.22861.256201642277830.007752036327524581.193246321394650.0276016422778267
381.26131.313557341244380.008589669804546871.200452988951070.0522573412443839
391.26461.32956302492253-0.008022681430019081.207659656507490.0649630249225288
401.22621.23975630970790-0.001964066054488961.214607756346590.0135563097079032
411.19851.17933959550049-0.003895451686175771.22155585618568-0.0191604044995055
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1151.22081.11414368979295-0.007550084561880781.33500639476893-0.106656310207045
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1191.38981.478269872121940.002933511481611161.298396616396450.0884698721219381
1201.36611.438060706842120.003182000347286681.290957292810590.0719607068421186


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')