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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 13:22:06 +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/t12933696007bc2ylrtjmfmvc1.htm/, Retrieved Mon, 06 May 2024 11:42:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115594, Retrieved Mon, 06 May 2024 11:42:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

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 Yuan] [2010-12-26 13:22:06] [c9d5faca36bd2ada281161976df30bf1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,4271
7,7662
7,6289
7,5281
7,3831
7,2355
7,0617
7,1237
7,4533
7,5411
7,4978
7,3525
7,3862
7,311
7,2013
7,249
7,3321
7,59
7,9082
8,2123
8,0929
8,118
8,1206
8,2883
8,4281
8,7917
8,9168
8,9446
8,9786
9,5862
9,6533
9,4125
9,2195
9,2882
9,6774
9,6857
10,1688
10,4399
10,4675
10,149
9,9163
9,9268
10,0529
10,1622
10,083
10,1134
10,3423
10,7536
11,0967
10,8588
10,7719
10,9262
10,708
10,5062
10,0683
9,8954
9,9589
9,9177
9,7189
9,5273
9,5746
9,763
9,6117
9,6581
9,8361
10,2353
10,1285
10,1347
10,2141
10,0971
9,9651
10,1286
10,3356
10,1238
10,1326
10,2467
10,44
10,3689
10,2415
10,3899
10,3162
10,4533
10,6741
10,8957
10,7404
10,6568
10,5682
10,9833
11,0237
10,8462
10,7287
10,7809
10,2609
9,8252
9,1071
8,695
9,2205
9,0496
8,7406
8,921
9,011
9,3157
9,5786
9,6246
9,7485
9,9431
10,1152
10,1827
9,9777
9,7436
9,3462
9,2623
9,1505
8,5794
8,3245
8,6538
8,752
8,8104
9,2665
9,0895

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'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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115594&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115594&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'Gwilym Jenkins' @ 72.249.127.135






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=115594&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=115594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115594&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
17.42717.271537288098230.07862655399882127.50403615790295-0.155562711901767
27.76627.964942744115580.08224536248579937.485211893398630.198742744115576
37.62897.83228808557461-0.04087571446891297.46638762889430.203388085574608
47.52817.6113132649108-0.004992099135911097.449878834225110.0832132649108033
57.38317.35908845507276-0.02625849462866767.43337003955591-0.0240115449272436
67.23557.048819865619610.004698142077878177.41748199230251-0.186680134380389
77.06176.7716314617301-0.04982540677921577.40159394504911-0.290068538269897
87.12376.857010385991740.008156495032182067.38223311897608-0.266689614008262
97.45337.57103931192951-0.02731160483256287.362872292903050.117739311929515
107.54117.76429793730326-0.03169600997525387.3495980726720.223197937303262
117.49787.65842661102720.0008495365318612347.336323852440940.160626611027202
127.35257.338663417117620.006383330692064667.35995325219032-0.0138365828823828
137.38627.310190794061480.07862655399882127.3835826519397-0.0760092059385213
147.3117.10349803336050.08224536248579937.4362566041537-0.207501966639502
157.20136.95454515810121-0.04087571446891297.4889305563677-0.246754841898793
167.2496.94856662627712-0.004992099135911097.55442547285879-0.300433373722876
177.33217.0705381052788-0.02625849462866767.61992038934987-0.261561894721200
187.597.46858477075960.004698142077878177.70671708716252-0.121415229240395
197.90828.07271162180405-0.04982540677921577.793513784975170.164511621804047
208.21238.505712996032020.008156495032182067.91073050893580.293412996032017
218.09298.18516437193613-0.02731160483256288.027947232896440.0922643719361282
228.1188.10515420212657-0.03169600997525388.16254180784869-0.0128457978734353
238.12067.943214080667190.0008495365318612348.29713638280095-0.177385919332808
248.28838.134937930110220.006383330692064668.43527873919771-0.153362069889779
258.42818.20415235040670.07862655399882128.57342109559448-0.223947649593301
268.79178.8016969050730.08224536248579938.699457732441210.00999690507299178
278.91689.04898134518097-0.04087571446891298.825494369287940.132181345180975
288.94468.95019464506892-0.004992099135911098.943997454066990.00559464506892304
298.97868.92095795578263-0.02625849462866769.06250053884604-0.0576420442173688
309.58629.985882924834930.004698142077878179.18181893308720.399682924834929
319.653310.0552880794509-0.04982540677921579.301137327328350.401988079450867
329.41259.395019369514440.008156495032182069.42182413545338-0.0174806304855615
339.21958.92380066125415-0.02731160483256289.5425109435784-0.295699338745846
349.28828.96756992857378-0.03169600997525389.64052608140147-0.320630071426219
359.67749.61540924424360.0008495365318612349.73854121922454-0.0619907557563977
369.68579.55780009293490.006383330692064669.80721657637303-0.127899907065091
3710.168810.38308151247970.07862655399882129.875891933521520.214281512479662
3810.439910.86262412172740.08224536248579939.934930515786830.422724121727368
3910.467510.9819066164168-0.04087571446891299.993969098052150.514406616416764
4010.14910.2511817127294-0.0049920991359110910.05181038640650.102181712729385
419.91639.74920681986776-0.026258494628667610.1096516747609-0.167093180132236
429.92689.686679234614030.0046981420778781710.1622226233081-0.240120765385971
4310.05299.94083183492393-0.049825406779215710.2147935718553-0.112068165076069
4410.162210.04717763645720.0081564950321820610.2690658685106-0.115022363542773
4510.0839.86997343966666-0.027311604832562810.3233381651659-0.213026560333336
4610.11349.87201972052794-0.031696009975253810.3864762894473-0.241380279472061
4710.342310.23413604973940.00084953653186123410.4496144137287-0.108163950260591
4810.753611.00360842805270.0063833306920646610.49720824125520.250008428052711
4911.096711.56997137721950.078626553998821210.54480206878170.47327137721946
5010.858811.08760881159440.082245362485799310.54774582591980.228808811594442
5110.771911.0339861314111-0.040875714468912910.55068958305780.262086131411113
5210.926211.3528694226804-0.0049920991359110910.50452267645550.426669422680424
5310.70810.9839027247755-0.026258494628667610.45835576985320.275902724775493
5410.506210.64394469185040.0046981420778781710.36375716607170.137744691850404
5510.06839.91726684448896-0.049825406779215710.2691585622903-0.151033155511044
569.89549.626051667263870.0081564950321820610.1565918377039-0.269348332736131
579.95899.90108649171492-0.027311604832562810.0440251131176-0.0578135082850775
589.91779.91085980019882-0.03169600997525389.95623620977643-0.00684019980117512
599.71899.568503157032920.0008495365318612349.86844730643522-0.15039684296708
609.52739.213833106687660.006383330692064669.83438356262028-0.313466893312343
619.57469.270253627195840.07862655399882129.80031981880534-0.304346372804158
629.7639.629776239053060.08224536248579939.81397839846114-0.133223760946938
639.61179.43663873635198-0.04087571446891299.82763697811694-0.175061263648026
649.65819.45881060888475-0.004992099135911099.86238149025116-0.199289391115252
659.83619.80133249224328-0.02625849462866769.89712600238539-0.0347675077567189
6610.235310.52253632298530.004698142077878179.943365534936850.287236322985271
6710.128510.3172203392909-0.04982540677921579.989605067488320.188720339290896
6810.134710.22805137953490.0081564950321820610.03319212543290.093351379534937
6910.214110.3787324214551-0.027311604832562810.07677918337740.164632421455121
7010.097110.1152569912631-0.031696009975253810.11063901871210.0181569912631048
719.96519.784851609421280.00084953653186123410.1444988540469-0.180248390578717
7210.128610.08402157333850.0063833306920646610.1667950959694-0.0445784266615021
7310.335610.40348210810920.078626553998821210.18909133789200.0678821081091598
7410.12389.955540710317850.082245362485799310.2098139271964-0.168259289682153
7510.132610.0755391979682-0.040875714468912910.2305365165007-0.0570608020317742
7610.246710.2340308164952-0.0049920991359110910.2643612826407-0.0126691835048032
7710.4410.6080724458479-0.026258494628667610.29818604878070.168072445847923
7810.368910.38783077514010.0046981420778781710.34527108278210.0189307751400634
7910.241510.1404692899958-0.049825406779215710.3923561167834-0.101030710004157
8010.389910.33324181516760.0081564950321820610.4384016898003-0.0566581848324397
8110.316210.1752643420154-0.027311604832562810.4844472628171-0.140935657984580
8210.453310.4062516189094-0.031696009975253810.5320443910659-0.0470483810906437
8310.674110.76770894415350.00084953653186123410.57964151931470.0936089441534822
8410.895711.15958064842300.0063833306920646610.62543602088490.263880648423019
8510.740410.7309429235460.078626553998821210.6712305224552-0.0094570764539963
8610.656810.53932121992720.082245362485799310.692033417587-0.117478780072803
8710.568210.4644394017501-0.040875714468912910.7128363127188-0.103760598249922
8810.983311.310312283311-0.0049920991359110910.66127981582490.327012283310992
8911.023711.4639351756977-0.026258494628667610.6097233189310.44023517569766
9010.846211.20539118302800.0046981420778781710.48231067489410.359191183028013
9110.728711.152327375922-0.049825406779215710.35489803085720.423627375922006
9210.780911.36610605391090.0081564950321820610.18753745105690.585206053910911
9310.260910.5289347335760-0.027311604832562810.02017687125660.268034733575957
949.82529.8405577956229-0.03169600997525389.841538214352360.0153577956228919
959.10718.550450906020020.0008495365318612349.66289955744812-0.556649093979981
968.6957.866894002689220.006383330692064669.51672266661872-0.828105997310784
979.22058.991827670211860.07862655399882129.37054577578932-0.228672329788139
989.04968.714190798561220.08224536248579939.30276383895298-0.335409201438779
998.74068.28709381235227-0.04087571446891299.23498190211664-0.453506187647728
1008.9218.5830793200624-0.004992099135911099.26391277907352-0.337920679937605
1019.0118.75541483859827-0.02625849462866769.2928436560304-0.255585161401726
1029.31579.244981100001680.004698142077878179.38172075792044-0.0707188999983188
1039.57869.73642754696873-0.04982540677921579.470597859810490.157827546968726
1049.62469.692660931593680.008156495032182069.548382573374140.0680609315936813
1059.74859.89814431789478-0.02731160483256289.626167286937780.149644317894781
1069.943110.2641476523792-0.03169600997525389.653748357596060.321047652379189
10710.115210.54822103521380.0008495365318612349.681329428254350.433021035213793
10810.182710.72490833761830.006383330692064669.634108331689630.542208337618307
1099.977710.28988621087630.07862655399882129.586887235124910.312186210876268
1109.74369.917928751111320.08224536248579939.487025886402880.174328751111322
1119.34629.34611117678806-0.04087571446891299.38716453768085-8.88232119375942e-05
1129.26239.23107697246837-0.004992099135911099.29851512666754-0.0312230275316328
1139.15059.11739277897443-0.02625849462866769.20986571565424-0.0331072210255723
1148.57948.024592454451720.004698142077878179.1295094034704-0.554807545548284
1158.32457.64967231549264-0.04982540677921579.04915309128657-0.674827684507358
1168.65388.331280992385520.008156495032182068.9681625125823-0.322519007614478
1178.7528.64413967095455-0.02731160483256288.88717193387802-0.107860329045453
1188.81048.84054931712284-0.03169600997525388.811946692852410.0301493171228433
1199.26659.795429011641340.0008495365318612348.73672145182680.528929011641335
1209.08959.503639566575050.006383330692064668.668977102732890.414139566575049

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 7.4271 & 7.27153728809823 & 0.0786265539988212 & 7.50403615790295 & -0.155562711901767 \tabularnewline
2 & 7.7662 & 7.96494274411558 & 0.0822453624857993 & 7.48521189339863 & 0.198742744115576 \tabularnewline
3 & 7.6289 & 7.83228808557461 & -0.0408757144689129 & 7.4663876288943 & 0.203388085574608 \tabularnewline
4 & 7.5281 & 7.6113132649108 & -0.00499209913591109 & 7.44987883422511 & 0.0832132649108033 \tabularnewline
5 & 7.3831 & 7.35908845507276 & -0.0262584946286676 & 7.43337003955591 & -0.0240115449272436 \tabularnewline
6 & 7.2355 & 7.04881986561961 & 0.00469814207787817 & 7.41748199230251 & -0.186680134380389 \tabularnewline
7 & 7.0617 & 6.7716314617301 & -0.0498254067792157 & 7.40159394504911 & -0.290068538269897 \tabularnewline
8 & 7.1237 & 6.85701038599174 & 0.00815649503218206 & 7.38223311897608 & -0.266689614008262 \tabularnewline
9 & 7.4533 & 7.57103931192951 & -0.0273116048325628 & 7.36287229290305 & 0.117739311929515 \tabularnewline
10 & 7.5411 & 7.76429793730326 & -0.0316960099752538 & 7.349598072672 & 0.223197937303262 \tabularnewline
11 & 7.4978 & 7.6584266110272 & 0.000849536531861234 & 7.33632385244094 & 0.160626611027202 \tabularnewline
12 & 7.3525 & 7.33866341711762 & 0.00638333069206466 & 7.35995325219032 & -0.0138365828823828 \tabularnewline
13 & 7.3862 & 7.31019079406148 & 0.0786265539988212 & 7.3835826519397 & -0.0760092059385213 \tabularnewline
14 & 7.311 & 7.1034980333605 & 0.0822453624857993 & 7.4362566041537 & -0.207501966639502 \tabularnewline
15 & 7.2013 & 6.95454515810121 & -0.0408757144689129 & 7.4889305563677 & -0.246754841898793 \tabularnewline
16 & 7.249 & 6.94856662627712 & -0.00499209913591109 & 7.55442547285879 & -0.300433373722876 \tabularnewline
17 & 7.3321 & 7.0705381052788 & -0.0262584946286676 & 7.61992038934987 & -0.261561894721200 \tabularnewline
18 & 7.59 & 7.4685847707596 & 0.00469814207787817 & 7.70671708716252 & -0.121415229240395 \tabularnewline
19 & 7.9082 & 8.07271162180405 & -0.0498254067792157 & 7.79351378497517 & 0.164511621804047 \tabularnewline
20 & 8.2123 & 8.50571299603202 & 0.00815649503218206 & 7.9107305089358 & 0.293412996032017 \tabularnewline
21 & 8.0929 & 8.18516437193613 & -0.0273116048325628 & 8.02794723289644 & 0.0922643719361282 \tabularnewline
22 & 8.118 & 8.10515420212657 & -0.0316960099752538 & 8.16254180784869 & -0.0128457978734353 \tabularnewline
23 & 8.1206 & 7.94321408066719 & 0.000849536531861234 & 8.29713638280095 & -0.177385919332808 \tabularnewline
24 & 8.2883 & 8.13493793011022 & 0.00638333069206466 & 8.43527873919771 & -0.153362069889779 \tabularnewline
25 & 8.4281 & 8.2041523504067 & 0.0786265539988212 & 8.57342109559448 & -0.223947649593301 \tabularnewline
26 & 8.7917 & 8.801696905073 & 0.0822453624857993 & 8.69945773244121 & 0.00999690507299178 \tabularnewline
27 & 8.9168 & 9.04898134518097 & -0.0408757144689129 & 8.82549436928794 & 0.132181345180975 \tabularnewline
28 & 8.9446 & 8.95019464506892 & -0.00499209913591109 & 8.94399745406699 & 0.00559464506892304 \tabularnewline
29 & 8.9786 & 8.92095795578263 & -0.0262584946286676 & 9.06250053884604 & -0.0576420442173688 \tabularnewline
30 & 9.5862 & 9.98588292483493 & 0.00469814207787817 & 9.1818189330872 & 0.399682924834929 \tabularnewline
31 & 9.6533 & 10.0552880794509 & -0.0498254067792157 & 9.30113732732835 & 0.401988079450867 \tabularnewline
32 & 9.4125 & 9.39501936951444 & 0.00815649503218206 & 9.42182413545338 & -0.0174806304855615 \tabularnewline
33 & 9.2195 & 8.92380066125415 & -0.0273116048325628 & 9.5425109435784 & -0.295699338745846 \tabularnewline
34 & 9.2882 & 8.96756992857378 & -0.0316960099752538 & 9.64052608140147 & -0.320630071426219 \tabularnewline
35 & 9.6774 & 9.6154092442436 & 0.000849536531861234 & 9.73854121922454 & -0.0619907557563977 \tabularnewline
36 & 9.6857 & 9.5578000929349 & 0.00638333069206466 & 9.80721657637303 & -0.127899907065091 \tabularnewline
37 & 10.1688 & 10.3830815124797 & 0.0786265539988212 & 9.87589193352152 & 0.214281512479662 \tabularnewline
38 & 10.4399 & 10.8626241217274 & 0.0822453624857993 & 9.93493051578683 & 0.422724121727368 \tabularnewline
39 & 10.4675 & 10.9819066164168 & -0.0408757144689129 & 9.99396909805215 & 0.514406616416764 \tabularnewline
40 & 10.149 & 10.2511817127294 & -0.00499209913591109 & 10.0518103864065 & 0.102181712729385 \tabularnewline
41 & 9.9163 & 9.74920681986776 & -0.0262584946286676 & 10.1096516747609 & -0.167093180132236 \tabularnewline
42 & 9.9268 & 9.68667923461403 & 0.00469814207787817 & 10.1622226233081 & -0.240120765385971 \tabularnewline
43 & 10.0529 & 9.94083183492393 & -0.0498254067792157 & 10.2147935718553 & -0.112068165076069 \tabularnewline
44 & 10.1622 & 10.0471776364572 & 0.00815649503218206 & 10.2690658685106 & -0.115022363542773 \tabularnewline
45 & 10.083 & 9.86997343966666 & -0.0273116048325628 & 10.3233381651659 & -0.213026560333336 \tabularnewline
46 & 10.1134 & 9.87201972052794 & -0.0316960099752538 & 10.3864762894473 & -0.241380279472061 \tabularnewline
47 & 10.3423 & 10.2341360497394 & 0.000849536531861234 & 10.4496144137287 & -0.108163950260591 \tabularnewline
48 & 10.7536 & 11.0036084280527 & 0.00638333069206466 & 10.4972082412552 & 0.250008428052711 \tabularnewline
49 & 11.0967 & 11.5699713772195 & 0.0786265539988212 & 10.5448020687817 & 0.47327137721946 \tabularnewline
50 & 10.8588 & 11.0876088115944 & 0.0822453624857993 & 10.5477458259198 & 0.228808811594442 \tabularnewline
51 & 10.7719 & 11.0339861314111 & -0.0408757144689129 & 10.5506895830578 & 0.262086131411113 \tabularnewline
52 & 10.9262 & 11.3528694226804 & -0.00499209913591109 & 10.5045226764555 & 0.426669422680424 \tabularnewline
53 & 10.708 & 10.9839027247755 & -0.0262584946286676 & 10.4583557698532 & 0.275902724775493 \tabularnewline
54 & 10.5062 & 10.6439446918504 & 0.00469814207787817 & 10.3637571660717 & 0.137744691850404 \tabularnewline
55 & 10.0683 & 9.91726684448896 & -0.0498254067792157 & 10.2691585622903 & -0.151033155511044 \tabularnewline
56 & 9.8954 & 9.62605166726387 & 0.00815649503218206 & 10.1565918377039 & -0.269348332736131 \tabularnewline
57 & 9.9589 & 9.90108649171492 & -0.0273116048325628 & 10.0440251131176 & -0.0578135082850775 \tabularnewline
58 & 9.9177 & 9.91085980019882 & -0.0316960099752538 & 9.95623620977643 & -0.00684019980117512 \tabularnewline
59 & 9.7189 & 9.56850315703292 & 0.000849536531861234 & 9.86844730643522 & -0.15039684296708 \tabularnewline
60 & 9.5273 & 9.21383310668766 & 0.00638333069206466 & 9.83438356262028 & -0.313466893312343 \tabularnewline
61 & 9.5746 & 9.27025362719584 & 0.0786265539988212 & 9.80031981880534 & -0.304346372804158 \tabularnewline
62 & 9.763 & 9.62977623905306 & 0.0822453624857993 & 9.81397839846114 & -0.133223760946938 \tabularnewline
63 & 9.6117 & 9.43663873635198 & -0.0408757144689129 & 9.82763697811694 & -0.175061263648026 \tabularnewline
64 & 9.6581 & 9.45881060888475 & -0.00499209913591109 & 9.86238149025116 & -0.199289391115252 \tabularnewline
65 & 9.8361 & 9.80133249224328 & -0.0262584946286676 & 9.89712600238539 & -0.0347675077567189 \tabularnewline
66 & 10.2353 & 10.5225363229853 & 0.00469814207787817 & 9.94336553493685 & 0.287236322985271 \tabularnewline
67 & 10.1285 & 10.3172203392909 & -0.0498254067792157 & 9.98960506748832 & 0.188720339290896 \tabularnewline
68 & 10.1347 & 10.2280513795349 & 0.00815649503218206 & 10.0331921254329 & 0.093351379534937 \tabularnewline
69 & 10.2141 & 10.3787324214551 & -0.0273116048325628 & 10.0767791833774 & 0.164632421455121 \tabularnewline
70 & 10.0971 & 10.1152569912631 & -0.0316960099752538 & 10.1106390187121 & 0.0181569912631048 \tabularnewline
71 & 9.9651 & 9.78485160942128 & 0.000849536531861234 & 10.1444988540469 & -0.180248390578717 \tabularnewline
72 & 10.1286 & 10.0840215733385 & 0.00638333069206466 & 10.1667950959694 & -0.0445784266615021 \tabularnewline
73 & 10.3356 & 10.4034821081092 & 0.0786265539988212 & 10.1890913378920 & 0.0678821081091598 \tabularnewline
74 & 10.1238 & 9.95554071031785 & 0.0822453624857993 & 10.2098139271964 & -0.168259289682153 \tabularnewline
75 & 10.1326 & 10.0755391979682 & -0.0408757144689129 & 10.2305365165007 & -0.0570608020317742 \tabularnewline
76 & 10.2467 & 10.2340308164952 & -0.00499209913591109 & 10.2643612826407 & -0.0126691835048032 \tabularnewline
77 & 10.44 & 10.6080724458479 & -0.0262584946286676 & 10.2981860487807 & 0.168072445847923 \tabularnewline
78 & 10.3689 & 10.3878307751401 & 0.00469814207787817 & 10.3452710827821 & 0.0189307751400634 \tabularnewline
79 & 10.2415 & 10.1404692899958 & -0.0498254067792157 & 10.3923561167834 & -0.101030710004157 \tabularnewline
80 & 10.3899 & 10.3332418151676 & 0.00815649503218206 & 10.4384016898003 & -0.0566581848324397 \tabularnewline
81 & 10.3162 & 10.1752643420154 & -0.0273116048325628 & 10.4844472628171 & -0.140935657984580 \tabularnewline
82 & 10.4533 & 10.4062516189094 & -0.0316960099752538 & 10.5320443910659 & -0.0470483810906437 \tabularnewline
83 & 10.6741 & 10.7677089441535 & 0.000849536531861234 & 10.5796415193147 & 0.0936089441534822 \tabularnewline
84 & 10.8957 & 11.1595806484230 & 0.00638333069206466 & 10.6254360208849 & 0.263880648423019 \tabularnewline
85 & 10.7404 & 10.730942923546 & 0.0786265539988212 & 10.6712305224552 & -0.0094570764539963 \tabularnewline
86 & 10.6568 & 10.5393212199272 & 0.0822453624857993 & 10.692033417587 & -0.117478780072803 \tabularnewline
87 & 10.5682 & 10.4644394017501 & -0.0408757144689129 & 10.7128363127188 & -0.103760598249922 \tabularnewline
88 & 10.9833 & 11.310312283311 & -0.00499209913591109 & 10.6612798158249 & 0.327012283310992 \tabularnewline
89 & 11.0237 & 11.4639351756977 & -0.0262584946286676 & 10.609723318931 & 0.44023517569766 \tabularnewline
90 & 10.8462 & 11.2053911830280 & 0.00469814207787817 & 10.4823106748941 & 0.359191183028013 \tabularnewline
91 & 10.7287 & 11.152327375922 & -0.0498254067792157 & 10.3548980308572 & 0.423627375922006 \tabularnewline
92 & 10.7809 & 11.3661060539109 & 0.00815649503218206 & 10.1875374510569 & 0.585206053910911 \tabularnewline
93 & 10.2609 & 10.5289347335760 & -0.0273116048325628 & 10.0201768712566 & 0.268034733575957 \tabularnewline
94 & 9.8252 & 9.8405577956229 & -0.0316960099752538 & 9.84153821435236 & 0.0153577956228919 \tabularnewline
95 & 9.1071 & 8.55045090602002 & 0.000849536531861234 & 9.66289955744812 & -0.556649093979981 \tabularnewline
96 & 8.695 & 7.86689400268922 & 0.00638333069206466 & 9.51672266661872 & -0.828105997310784 \tabularnewline
97 & 9.2205 & 8.99182767021186 & 0.0786265539988212 & 9.37054577578932 & -0.228672329788139 \tabularnewline
98 & 9.0496 & 8.71419079856122 & 0.0822453624857993 & 9.30276383895298 & -0.335409201438779 \tabularnewline
99 & 8.7406 & 8.28709381235227 & -0.0408757144689129 & 9.23498190211664 & -0.453506187647728 \tabularnewline
100 & 8.921 & 8.5830793200624 & -0.00499209913591109 & 9.26391277907352 & -0.337920679937605 \tabularnewline
101 & 9.011 & 8.75541483859827 & -0.0262584946286676 & 9.2928436560304 & -0.255585161401726 \tabularnewline
102 & 9.3157 & 9.24498110000168 & 0.00469814207787817 & 9.38172075792044 & -0.0707188999983188 \tabularnewline
103 & 9.5786 & 9.73642754696873 & -0.0498254067792157 & 9.47059785981049 & 0.157827546968726 \tabularnewline
104 & 9.6246 & 9.69266093159368 & 0.00815649503218206 & 9.54838257337414 & 0.0680609315936813 \tabularnewline
105 & 9.7485 & 9.89814431789478 & -0.0273116048325628 & 9.62616728693778 & 0.149644317894781 \tabularnewline
106 & 9.9431 & 10.2641476523792 & -0.0316960099752538 & 9.65374835759606 & 0.321047652379189 \tabularnewline
107 & 10.1152 & 10.5482210352138 & 0.000849536531861234 & 9.68132942825435 & 0.433021035213793 \tabularnewline
108 & 10.1827 & 10.7249083376183 & 0.00638333069206466 & 9.63410833168963 & 0.542208337618307 \tabularnewline
109 & 9.9777 & 10.2898862108763 & 0.0786265539988212 & 9.58688723512491 & 0.312186210876268 \tabularnewline
110 & 9.7436 & 9.91792875111132 & 0.0822453624857993 & 9.48702588640288 & 0.174328751111322 \tabularnewline
111 & 9.3462 & 9.34611117678806 & -0.0408757144689129 & 9.38716453768085 & -8.88232119375942e-05 \tabularnewline
112 & 9.2623 & 9.23107697246837 & -0.00499209913591109 & 9.29851512666754 & -0.0312230275316328 \tabularnewline
113 & 9.1505 & 9.11739277897443 & -0.0262584946286676 & 9.20986571565424 & -0.0331072210255723 \tabularnewline
114 & 8.5794 & 8.02459245445172 & 0.00469814207787817 & 9.1295094034704 & -0.554807545548284 \tabularnewline
115 & 8.3245 & 7.64967231549264 & -0.0498254067792157 & 9.04915309128657 & -0.674827684507358 \tabularnewline
116 & 8.6538 & 8.33128099238552 & 0.00815649503218206 & 8.9681625125823 & -0.322519007614478 \tabularnewline
117 & 8.752 & 8.64413967095455 & -0.0273116048325628 & 8.88717193387802 & -0.107860329045453 \tabularnewline
118 & 8.8104 & 8.84054931712284 & -0.0316960099752538 & 8.81194669285241 & 0.0301493171228433 \tabularnewline
119 & 9.2665 & 9.79542901164134 & 0.000849536531861234 & 8.7367214518268 & 0.528929011641335 \tabularnewline
120 & 9.0895 & 9.50363956657505 & 0.00638333069206466 & 8.66897710273289 & 0.414139566575049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115594&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]7.4271[/C][C]7.27153728809823[/C][C]0.0786265539988212[/C][C]7.50403615790295[/C][C]-0.155562711901767[/C][/ROW]
[ROW][C]2[/C][C]7.7662[/C][C]7.96494274411558[/C][C]0.0822453624857993[/C][C]7.48521189339863[/C][C]0.198742744115576[/C][/ROW]
[ROW][C]3[/C][C]7.6289[/C][C]7.83228808557461[/C][C]-0.0408757144689129[/C][C]7.4663876288943[/C][C]0.203388085574608[/C][/ROW]
[ROW][C]4[/C][C]7.5281[/C][C]7.6113132649108[/C][C]-0.00499209913591109[/C][C]7.44987883422511[/C][C]0.0832132649108033[/C][/ROW]
[ROW][C]5[/C][C]7.3831[/C][C]7.35908845507276[/C][C]-0.0262584946286676[/C][C]7.43337003955591[/C][C]-0.0240115449272436[/C][/ROW]
[ROW][C]6[/C][C]7.2355[/C][C]7.04881986561961[/C][C]0.00469814207787817[/C][C]7.41748199230251[/C][C]-0.186680134380389[/C][/ROW]
[ROW][C]7[/C][C]7.0617[/C][C]6.7716314617301[/C][C]-0.0498254067792157[/C][C]7.40159394504911[/C][C]-0.290068538269897[/C][/ROW]
[ROW][C]8[/C][C]7.1237[/C][C]6.85701038599174[/C][C]0.00815649503218206[/C][C]7.38223311897608[/C][C]-0.266689614008262[/C][/ROW]
[ROW][C]9[/C][C]7.4533[/C][C]7.57103931192951[/C][C]-0.0273116048325628[/C][C]7.36287229290305[/C][C]0.117739311929515[/C][/ROW]
[ROW][C]10[/C][C]7.5411[/C][C]7.76429793730326[/C][C]-0.0316960099752538[/C][C]7.349598072672[/C][C]0.223197937303262[/C][/ROW]
[ROW][C]11[/C][C]7.4978[/C][C]7.6584266110272[/C][C]0.000849536531861234[/C][C]7.33632385244094[/C][C]0.160626611027202[/C][/ROW]
[ROW][C]12[/C][C]7.3525[/C][C]7.33866341711762[/C][C]0.00638333069206466[/C][C]7.35995325219032[/C][C]-0.0138365828823828[/C][/ROW]
[ROW][C]13[/C][C]7.3862[/C][C]7.31019079406148[/C][C]0.0786265539988212[/C][C]7.3835826519397[/C][C]-0.0760092059385213[/C][/ROW]
[ROW][C]14[/C][C]7.311[/C][C]7.1034980333605[/C][C]0.0822453624857993[/C][C]7.4362566041537[/C][C]-0.207501966639502[/C][/ROW]
[ROW][C]15[/C][C]7.2013[/C][C]6.95454515810121[/C][C]-0.0408757144689129[/C][C]7.4889305563677[/C][C]-0.246754841898793[/C][/ROW]
[ROW][C]16[/C][C]7.249[/C][C]6.94856662627712[/C][C]-0.00499209913591109[/C][C]7.55442547285879[/C][C]-0.300433373722876[/C][/ROW]
[ROW][C]17[/C][C]7.3321[/C][C]7.0705381052788[/C][C]-0.0262584946286676[/C][C]7.61992038934987[/C][C]-0.261561894721200[/C][/ROW]
[ROW][C]18[/C][C]7.59[/C][C]7.4685847707596[/C][C]0.00469814207787817[/C][C]7.70671708716252[/C][C]-0.121415229240395[/C][/ROW]
[ROW][C]19[/C][C]7.9082[/C][C]8.07271162180405[/C][C]-0.0498254067792157[/C][C]7.79351378497517[/C][C]0.164511621804047[/C][/ROW]
[ROW][C]20[/C][C]8.2123[/C][C]8.50571299603202[/C][C]0.00815649503218206[/C][C]7.9107305089358[/C][C]0.293412996032017[/C][/ROW]
[ROW][C]21[/C][C]8.0929[/C][C]8.18516437193613[/C][C]-0.0273116048325628[/C][C]8.02794723289644[/C][C]0.0922643719361282[/C][/ROW]
[ROW][C]22[/C][C]8.118[/C][C]8.10515420212657[/C][C]-0.0316960099752538[/C][C]8.16254180784869[/C][C]-0.0128457978734353[/C][/ROW]
[ROW][C]23[/C][C]8.1206[/C][C]7.94321408066719[/C][C]0.000849536531861234[/C][C]8.29713638280095[/C][C]-0.177385919332808[/C][/ROW]
[ROW][C]24[/C][C]8.2883[/C][C]8.13493793011022[/C][C]0.00638333069206466[/C][C]8.43527873919771[/C][C]-0.153362069889779[/C][/ROW]
[ROW][C]25[/C][C]8.4281[/C][C]8.2041523504067[/C][C]0.0786265539988212[/C][C]8.57342109559448[/C][C]-0.223947649593301[/C][/ROW]
[ROW][C]26[/C][C]8.7917[/C][C]8.801696905073[/C][C]0.0822453624857993[/C][C]8.69945773244121[/C][C]0.00999690507299178[/C][/ROW]
[ROW][C]27[/C][C]8.9168[/C][C]9.04898134518097[/C][C]-0.0408757144689129[/C][C]8.82549436928794[/C][C]0.132181345180975[/C][/ROW]
[ROW][C]28[/C][C]8.9446[/C][C]8.95019464506892[/C][C]-0.00499209913591109[/C][C]8.94399745406699[/C][C]0.00559464506892304[/C][/ROW]
[ROW][C]29[/C][C]8.9786[/C][C]8.92095795578263[/C][C]-0.0262584946286676[/C][C]9.06250053884604[/C][C]-0.0576420442173688[/C][/ROW]
[ROW][C]30[/C][C]9.5862[/C][C]9.98588292483493[/C][C]0.00469814207787817[/C][C]9.1818189330872[/C][C]0.399682924834929[/C][/ROW]
[ROW][C]31[/C][C]9.6533[/C][C]10.0552880794509[/C][C]-0.0498254067792157[/C][C]9.30113732732835[/C][C]0.401988079450867[/C][/ROW]
[ROW][C]32[/C][C]9.4125[/C][C]9.39501936951444[/C][C]0.00815649503218206[/C][C]9.42182413545338[/C][C]-0.0174806304855615[/C][/ROW]
[ROW][C]33[/C][C]9.2195[/C][C]8.92380066125415[/C][C]-0.0273116048325628[/C][C]9.5425109435784[/C][C]-0.295699338745846[/C][/ROW]
[ROW][C]34[/C][C]9.2882[/C][C]8.96756992857378[/C][C]-0.0316960099752538[/C][C]9.64052608140147[/C][C]-0.320630071426219[/C][/ROW]
[ROW][C]35[/C][C]9.6774[/C][C]9.6154092442436[/C][C]0.000849536531861234[/C][C]9.73854121922454[/C][C]-0.0619907557563977[/C][/ROW]
[ROW][C]36[/C][C]9.6857[/C][C]9.5578000929349[/C][C]0.00638333069206466[/C][C]9.80721657637303[/C][C]-0.127899907065091[/C][/ROW]
[ROW][C]37[/C][C]10.1688[/C][C]10.3830815124797[/C][C]0.0786265539988212[/C][C]9.87589193352152[/C][C]0.214281512479662[/C][/ROW]
[ROW][C]38[/C][C]10.4399[/C][C]10.8626241217274[/C][C]0.0822453624857993[/C][C]9.93493051578683[/C][C]0.422724121727368[/C][/ROW]
[ROW][C]39[/C][C]10.4675[/C][C]10.9819066164168[/C][C]-0.0408757144689129[/C][C]9.99396909805215[/C][C]0.514406616416764[/C][/ROW]
[ROW][C]40[/C][C]10.149[/C][C]10.2511817127294[/C][C]-0.00499209913591109[/C][C]10.0518103864065[/C][C]0.102181712729385[/C][/ROW]
[ROW][C]41[/C][C]9.9163[/C][C]9.74920681986776[/C][C]-0.0262584946286676[/C][C]10.1096516747609[/C][C]-0.167093180132236[/C][/ROW]
[ROW][C]42[/C][C]9.9268[/C][C]9.68667923461403[/C][C]0.00469814207787817[/C][C]10.1622226233081[/C][C]-0.240120765385971[/C][/ROW]
[ROW][C]43[/C][C]10.0529[/C][C]9.94083183492393[/C][C]-0.0498254067792157[/C][C]10.2147935718553[/C][C]-0.112068165076069[/C][/ROW]
[ROW][C]44[/C][C]10.1622[/C][C]10.0471776364572[/C][C]0.00815649503218206[/C][C]10.2690658685106[/C][C]-0.115022363542773[/C][/ROW]
[ROW][C]45[/C][C]10.083[/C][C]9.86997343966666[/C][C]-0.0273116048325628[/C][C]10.3233381651659[/C][C]-0.213026560333336[/C][/ROW]
[ROW][C]46[/C][C]10.1134[/C][C]9.87201972052794[/C][C]-0.0316960099752538[/C][C]10.3864762894473[/C][C]-0.241380279472061[/C][/ROW]
[ROW][C]47[/C][C]10.3423[/C][C]10.2341360497394[/C][C]0.000849536531861234[/C][C]10.4496144137287[/C][C]-0.108163950260591[/C][/ROW]
[ROW][C]48[/C][C]10.7536[/C][C]11.0036084280527[/C][C]0.00638333069206466[/C][C]10.4972082412552[/C][C]0.250008428052711[/C][/ROW]
[ROW][C]49[/C][C]11.0967[/C][C]11.5699713772195[/C][C]0.0786265539988212[/C][C]10.5448020687817[/C][C]0.47327137721946[/C][/ROW]
[ROW][C]50[/C][C]10.8588[/C][C]11.0876088115944[/C][C]0.0822453624857993[/C][C]10.5477458259198[/C][C]0.228808811594442[/C][/ROW]
[ROW][C]51[/C][C]10.7719[/C][C]11.0339861314111[/C][C]-0.0408757144689129[/C][C]10.5506895830578[/C][C]0.262086131411113[/C][/ROW]
[ROW][C]52[/C][C]10.9262[/C][C]11.3528694226804[/C][C]-0.00499209913591109[/C][C]10.5045226764555[/C][C]0.426669422680424[/C][/ROW]
[ROW][C]53[/C][C]10.708[/C][C]10.9839027247755[/C][C]-0.0262584946286676[/C][C]10.4583557698532[/C][C]0.275902724775493[/C][/ROW]
[ROW][C]54[/C][C]10.5062[/C][C]10.6439446918504[/C][C]0.00469814207787817[/C][C]10.3637571660717[/C][C]0.137744691850404[/C][/ROW]
[ROW][C]55[/C][C]10.0683[/C][C]9.91726684448896[/C][C]-0.0498254067792157[/C][C]10.2691585622903[/C][C]-0.151033155511044[/C][/ROW]
[ROW][C]56[/C][C]9.8954[/C][C]9.62605166726387[/C][C]0.00815649503218206[/C][C]10.1565918377039[/C][C]-0.269348332736131[/C][/ROW]
[ROW][C]57[/C][C]9.9589[/C][C]9.90108649171492[/C][C]-0.0273116048325628[/C][C]10.0440251131176[/C][C]-0.0578135082850775[/C][/ROW]
[ROW][C]58[/C][C]9.9177[/C][C]9.91085980019882[/C][C]-0.0316960099752538[/C][C]9.95623620977643[/C][C]-0.00684019980117512[/C][/ROW]
[ROW][C]59[/C][C]9.7189[/C][C]9.56850315703292[/C][C]0.000849536531861234[/C][C]9.86844730643522[/C][C]-0.15039684296708[/C][/ROW]
[ROW][C]60[/C][C]9.5273[/C][C]9.21383310668766[/C][C]0.00638333069206466[/C][C]9.83438356262028[/C][C]-0.313466893312343[/C][/ROW]
[ROW][C]61[/C][C]9.5746[/C][C]9.27025362719584[/C][C]0.0786265539988212[/C][C]9.80031981880534[/C][C]-0.304346372804158[/C][/ROW]
[ROW][C]62[/C][C]9.763[/C][C]9.62977623905306[/C][C]0.0822453624857993[/C][C]9.81397839846114[/C][C]-0.133223760946938[/C][/ROW]
[ROW][C]63[/C][C]9.6117[/C][C]9.43663873635198[/C][C]-0.0408757144689129[/C][C]9.82763697811694[/C][C]-0.175061263648026[/C][/ROW]
[ROW][C]64[/C][C]9.6581[/C][C]9.45881060888475[/C][C]-0.00499209913591109[/C][C]9.86238149025116[/C][C]-0.199289391115252[/C][/ROW]
[ROW][C]65[/C][C]9.8361[/C][C]9.80133249224328[/C][C]-0.0262584946286676[/C][C]9.89712600238539[/C][C]-0.0347675077567189[/C][/ROW]
[ROW][C]66[/C][C]10.2353[/C][C]10.5225363229853[/C][C]0.00469814207787817[/C][C]9.94336553493685[/C][C]0.287236322985271[/C][/ROW]
[ROW][C]67[/C][C]10.1285[/C][C]10.3172203392909[/C][C]-0.0498254067792157[/C][C]9.98960506748832[/C][C]0.188720339290896[/C][/ROW]
[ROW][C]68[/C][C]10.1347[/C][C]10.2280513795349[/C][C]0.00815649503218206[/C][C]10.0331921254329[/C][C]0.093351379534937[/C][/ROW]
[ROW][C]69[/C][C]10.2141[/C][C]10.3787324214551[/C][C]-0.0273116048325628[/C][C]10.0767791833774[/C][C]0.164632421455121[/C][/ROW]
[ROW][C]70[/C][C]10.0971[/C][C]10.1152569912631[/C][C]-0.0316960099752538[/C][C]10.1106390187121[/C][C]0.0181569912631048[/C][/ROW]
[ROW][C]71[/C][C]9.9651[/C][C]9.78485160942128[/C][C]0.000849536531861234[/C][C]10.1444988540469[/C][C]-0.180248390578717[/C][/ROW]
[ROW][C]72[/C][C]10.1286[/C][C]10.0840215733385[/C][C]0.00638333069206466[/C][C]10.1667950959694[/C][C]-0.0445784266615021[/C][/ROW]
[ROW][C]73[/C][C]10.3356[/C][C]10.4034821081092[/C][C]0.0786265539988212[/C][C]10.1890913378920[/C][C]0.0678821081091598[/C][/ROW]
[ROW][C]74[/C][C]10.1238[/C][C]9.95554071031785[/C][C]0.0822453624857993[/C][C]10.2098139271964[/C][C]-0.168259289682153[/C][/ROW]
[ROW][C]75[/C][C]10.1326[/C][C]10.0755391979682[/C][C]-0.0408757144689129[/C][C]10.2305365165007[/C][C]-0.0570608020317742[/C][/ROW]
[ROW][C]76[/C][C]10.2467[/C][C]10.2340308164952[/C][C]-0.00499209913591109[/C][C]10.2643612826407[/C][C]-0.0126691835048032[/C][/ROW]
[ROW][C]77[/C][C]10.44[/C][C]10.6080724458479[/C][C]-0.0262584946286676[/C][C]10.2981860487807[/C][C]0.168072445847923[/C][/ROW]
[ROW][C]78[/C][C]10.3689[/C][C]10.3878307751401[/C][C]0.00469814207787817[/C][C]10.3452710827821[/C][C]0.0189307751400634[/C][/ROW]
[ROW][C]79[/C][C]10.2415[/C][C]10.1404692899958[/C][C]-0.0498254067792157[/C][C]10.3923561167834[/C][C]-0.101030710004157[/C][/ROW]
[ROW][C]80[/C][C]10.3899[/C][C]10.3332418151676[/C][C]0.00815649503218206[/C][C]10.4384016898003[/C][C]-0.0566581848324397[/C][/ROW]
[ROW][C]81[/C][C]10.3162[/C][C]10.1752643420154[/C][C]-0.0273116048325628[/C][C]10.4844472628171[/C][C]-0.140935657984580[/C][/ROW]
[ROW][C]82[/C][C]10.4533[/C][C]10.4062516189094[/C][C]-0.0316960099752538[/C][C]10.5320443910659[/C][C]-0.0470483810906437[/C][/ROW]
[ROW][C]83[/C][C]10.6741[/C][C]10.7677089441535[/C][C]0.000849536531861234[/C][C]10.5796415193147[/C][C]0.0936089441534822[/C][/ROW]
[ROW][C]84[/C][C]10.8957[/C][C]11.1595806484230[/C][C]0.00638333069206466[/C][C]10.6254360208849[/C][C]0.263880648423019[/C][/ROW]
[ROW][C]85[/C][C]10.7404[/C][C]10.730942923546[/C][C]0.0786265539988212[/C][C]10.6712305224552[/C][C]-0.0094570764539963[/C][/ROW]
[ROW][C]86[/C][C]10.6568[/C][C]10.5393212199272[/C][C]0.0822453624857993[/C][C]10.692033417587[/C][C]-0.117478780072803[/C][/ROW]
[ROW][C]87[/C][C]10.5682[/C][C]10.4644394017501[/C][C]-0.0408757144689129[/C][C]10.7128363127188[/C][C]-0.103760598249922[/C][/ROW]
[ROW][C]88[/C][C]10.9833[/C][C]11.310312283311[/C][C]-0.00499209913591109[/C][C]10.6612798158249[/C][C]0.327012283310992[/C][/ROW]
[ROW][C]89[/C][C]11.0237[/C][C]11.4639351756977[/C][C]-0.0262584946286676[/C][C]10.609723318931[/C][C]0.44023517569766[/C][/ROW]
[ROW][C]90[/C][C]10.8462[/C][C]11.2053911830280[/C][C]0.00469814207787817[/C][C]10.4823106748941[/C][C]0.359191183028013[/C][/ROW]
[ROW][C]91[/C][C]10.7287[/C][C]11.152327375922[/C][C]-0.0498254067792157[/C][C]10.3548980308572[/C][C]0.423627375922006[/C][/ROW]
[ROW][C]92[/C][C]10.7809[/C][C]11.3661060539109[/C][C]0.00815649503218206[/C][C]10.1875374510569[/C][C]0.585206053910911[/C][/ROW]
[ROW][C]93[/C][C]10.2609[/C][C]10.5289347335760[/C][C]-0.0273116048325628[/C][C]10.0201768712566[/C][C]0.268034733575957[/C][/ROW]
[ROW][C]94[/C][C]9.8252[/C][C]9.8405577956229[/C][C]-0.0316960099752538[/C][C]9.84153821435236[/C][C]0.0153577956228919[/C][/ROW]
[ROW][C]95[/C][C]9.1071[/C][C]8.55045090602002[/C][C]0.000849536531861234[/C][C]9.66289955744812[/C][C]-0.556649093979981[/C][/ROW]
[ROW][C]96[/C][C]8.695[/C][C]7.86689400268922[/C][C]0.00638333069206466[/C][C]9.51672266661872[/C][C]-0.828105997310784[/C][/ROW]
[ROW][C]97[/C][C]9.2205[/C][C]8.99182767021186[/C][C]0.0786265539988212[/C][C]9.37054577578932[/C][C]-0.228672329788139[/C][/ROW]
[ROW][C]98[/C][C]9.0496[/C][C]8.71419079856122[/C][C]0.0822453624857993[/C][C]9.30276383895298[/C][C]-0.335409201438779[/C][/ROW]
[ROW][C]99[/C][C]8.7406[/C][C]8.28709381235227[/C][C]-0.0408757144689129[/C][C]9.23498190211664[/C][C]-0.453506187647728[/C][/ROW]
[ROW][C]100[/C][C]8.921[/C][C]8.5830793200624[/C][C]-0.00499209913591109[/C][C]9.26391277907352[/C][C]-0.337920679937605[/C][/ROW]
[ROW][C]101[/C][C]9.011[/C][C]8.75541483859827[/C][C]-0.0262584946286676[/C][C]9.2928436560304[/C][C]-0.255585161401726[/C][/ROW]
[ROW][C]102[/C][C]9.3157[/C][C]9.24498110000168[/C][C]0.00469814207787817[/C][C]9.38172075792044[/C][C]-0.0707188999983188[/C][/ROW]
[ROW][C]103[/C][C]9.5786[/C][C]9.73642754696873[/C][C]-0.0498254067792157[/C][C]9.47059785981049[/C][C]0.157827546968726[/C][/ROW]
[ROW][C]104[/C][C]9.6246[/C][C]9.69266093159368[/C][C]0.00815649503218206[/C][C]9.54838257337414[/C][C]0.0680609315936813[/C][/ROW]
[ROW][C]105[/C][C]9.7485[/C][C]9.89814431789478[/C][C]-0.0273116048325628[/C][C]9.62616728693778[/C][C]0.149644317894781[/C][/ROW]
[ROW][C]106[/C][C]9.9431[/C][C]10.2641476523792[/C][C]-0.0316960099752538[/C][C]9.65374835759606[/C][C]0.321047652379189[/C][/ROW]
[ROW][C]107[/C][C]10.1152[/C][C]10.5482210352138[/C][C]0.000849536531861234[/C][C]9.68132942825435[/C][C]0.433021035213793[/C][/ROW]
[ROW][C]108[/C][C]10.1827[/C][C]10.7249083376183[/C][C]0.00638333069206466[/C][C]9.63410833168963[/C][C]0.542208337618307[/C][/ROW]
[ROW][C]109[/C][C]9.9777[/C][C]10.2898862108763[/C][C]0.0786265539988212[/C][C]9.58688723512491[/C][C]0.312186210876268[/C][/ROW]
[ROW][C]110[/C][C]9.7436[/C][C]9.91792875111132[/C][C]0.0822453624857993[/C][C]9.48702588640288[/C][C]0.174328751111322[/C][/ROW]
[ROW][C]111[/C][C]9.3462[/C][C]9.34611117678806[/C][C]-0.0408757144689129[/C][C]9.38716453768085[/C][C]-8.88232119375942e-05[/C][/ROW]
[ROW][C]112[/C][C]9.2623[/C][C]9.23107697246837[/C][C]-0.00499209913591109[/C][C]9.29851512666754[/C][C]-0.0312230275316328[/C][/ROW]
[ROW][C]113[/C][C]9.1505[/C][C]9.11739277897443[/C][C]-0.0262584946286676[/C][C]9.20986571565424[/C][C]-0.0331072210255723[/C][/ROW]
[ROW][C]114[/C][C]8.5794[/C][C]8.02459245445172[/C][C]0.00469814207787817[/C][C]9.1295094034704[/C][C]-0.554807545548284[/C][/ROW]
[ROW][C]115[/C][C]8.3245[/C][C]7.64967231549264[/C][C]-0.0498254067792157[/C][C]9.04915309128657[/C][C]-0.674827684507358[/C][/ROW]
[ROW][C]116[/C][C]8.6538[/C][C]8.33128099238552[/C][C]0.00815649503218206[/C][C]8.9681625125823[/C][C]-0.322519007614478[/C][/ROW]
[ROW][C]117[/C][C]8.752[/C][C]8.64413967095455[/C][C]-0.0273116048325628[/C][C]8.88717193387802[/C][C]-0.107860329045453[/C][/ROW]
[ROW][C]118[/C][C]8.8104[/C][C]8.84054931712284[/C][C]-0.0316960099752538[/C][C]8.81194669285241[/C][C]0.0301493171228433[/C][/ROW]
[ROW][C]119[/C][C]9.2665[/C][C]9.79542901164134[/C][C]0.000849536531861234[/C][C]8.7367214518268[/C][C]0.528929011641335[/C][/ROW]
[ROW][C]120[/C][C]9.0895[/C][C]9.50363956657505[/C][C]0.00638333069206466[/C][C]8.66897710273289[/C][C]0.414139566575049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115594&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115594&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
17.42717.271537288098230.07862655399882127.50403615790295-0.155562711901767
27.76627.964942744115580.08224536248579937.485211893398630.198742744115576
37.62897.83228808557461-0.04087571446891297.46638762889430.203388085574608
47.52817.6113132649108-0.004992099135911097.449878834225110.0832132649108033
57.38317.35908845507276-0.02625849462866767.43337003955591-0.0240115449272436
67.23557.048819865619610.004698142077878177.41748199230251-0.186680134380389
77.06176.7716314617301-0.04982540677921577.40159394504911-0.290068538269897
87.12376.857010385991740.008156495032182067.38223311897608-0.266689614008262
97.45337.57103931192951-0.02731160483256287.362872292903050.117739311929515
107.54117.76429793730326-0.03169600997525387.3495980726720.223197937303262
117.49787.65842661102720.0008495365318612347.336323852440940.160626611027202
127.35257.338663417117620.006383330692064667.35995325219032-0.0138365828823828
137.38627.310190794061480.07862655399882127.3835826519397-0.0760092059385213
147.3117.10349803336050.08224536248579937.4362566041537-0.207501966639502
157.20136.95454515810121-0.04087571446891297.4889305563677-0.246754841898793
167.2496.94856662627712-0.004992099135911097.55442547285879-0.300433373722876
177.33217.0705381052788-0.02625849462866767.61992038934987-0.261561894721200
187.597.46858477075960.004698142077878177.70671708716252-0.121415229240395
197.90828.07271162180405-0.04982540677921577.793513784975170.164511621804047
208.21238.505712996032020.008156495032182067.91073050893580.293412996032017
218.09298.18516437193613-0.02731160483256288.027947232896440.0922643719361282
228.1188.10515420212657-0.03169600997525388.16254180784869-0.0128457978734353
238.12067.943214080667190.0008495365318612348.29713638280095-0.177385919332808
248.28838.134937930110220.006383330692064668.43527873919771-0.153362069889779
258.42818.20415235040670.07862655399882128.57342109559448-0.223947649593301
268.79178.8016969050730.08224536248579938.699457732441210.00999690507299178
278.91689.04898134518097-0.04087571446891298.825494369287940.132181345180975
288.94468.95019464506892-0.004992099135911098.943997454066990.00559464506892304
298.97868.92095795578263-0.02625849462866769.06250053884604-0.0576420442173688
309.58629.985882924834930.004698142077878179.18181893308720.399682924834929
319.653310.0552880794509-0.04982540677921579.301137327328350.401988079450867
329.41259.395019369514440.008156495032182069.42182413545338-0.0174806304855615
339.21958.92380066125415-0.02731160483256289.5425109435784-0.295699338745846
349.28828.96756992857378-0.03169600997525389.64052608140147-0.320630071426219
359.67749.61540924424360.0008495365318612349.73854121922454-0.0619907557563977
369.68579.55780009293490.006383330692064669.80721657637303-0.127899907065091
3710.168810.38308151247970.07862655399882129.875891933521520.214281512479662
3810.439910.86262412172740.08224536248579939.934930515786830.422724121727368
3910.467510.9819066164168-0.04087571446891299.993969098052150.514406616416764
4010.14910.2511817127294-0.0049920991359110910.05181038640650.102181712729385
419.91639.74920681986776-0.026258494628667610.1096516747609-0.167093180132236
429.92689.686679234614030.0046981420778781710.1622226233081-0.240120765385971
4310.05299.94083183492393-0.049825406779215710.2147935718553-0.112068165076069
4410.162210.04717763645720.0081564950321820610.2690658685106-0.115022363542773
4510.0839.86997343966666-0.027311604832562810.3233381651659-0.213026560333336
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1209.08959.503639566575050.006383330692064668.668977102732890.414139566575049


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')