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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decomposeloess.wasp
Title produced by softwareDecomposition by Loess
Date of computationFri, 25 Nov 2011 04:11:42 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/25/t1322212343yd5pqug9qp3z3du.htm/, Retrieved Thu, 18 Jul 2024 01:17:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147260, Retrieved Thu, 18 Jul 2024 01:17:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Decomposition by Loess] [WS 8 - Loess] [2011-11-25 09:11:42] [9afaf62527660fe62ab98f95fea710a5] [Current]
- R  D    [Decomposition by Loess] [WS 8 - Loess] [2011-11-25 09:18:48] [6a3e51c0c7ab195427042dfaef1df5a0]
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Dataseries X:
112
118
132
129
121
135
148
148
136
119
104
118
115
126
141
135
125
149
170
170
158
133
114
140
145
150
178
163
172
178
199
199
184
162
146
166
171
180
193
181
183
218
230
242
209
191
172
194
196
196
236
235
229
243
264
272
237
211
180
201
204
188
235
227
234
264
302
293
259
229
203
229
242
233
267
269
270
315
364
347
312
274
237
278
284
277
317
313
318
374
413
405
355
306
271
306
315
301
356
348
355
422
465
467
404
347
305
336
340
318
362
348
363
435
491
505
404
359
310
337
360
342
406
396
420
472
548
559
463
407
362
405
417
391
419
461
472
535
622
606
508
461
390
432




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147260&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147260&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net







Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal14410145
Trend1912
Low-pass1312

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1441 & 0 & 145 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147260&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]1441[/C][C]0[/C][C]145[/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=147260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147260&T=1

As an alternative you can also use a QR Code:  

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

Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal14410145
Trend1912
Low-pass1312







Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
1112122.310369902516-25.4977183397736127.18734843725810.310369902516
2118144.571402815284-35.2209348015702126.64953198628626.5714028152841
3132140.915762476461-3.02747801177545126.1117155353158.91576247646083
4129140.100122400179-8.29905418525078126.19893178507211.1001224001792
5121121.451140778362-5.73728881319014126.2861480348290.451140778361591
6135110.93034278152532.3366341296942126.733023088781-24.0696572184753
714898.576220320253370.243881537013127.179898142734-49.4237796797467
8148100.5343508239368.0494327275684127.416216448501-47.4656491760699
9136126.90913920834917.4383260373816127.652534754269-9.09086079165081
10119130.044842451944-21.0634315333585129.01858908141511.0448424519439
11104135.097207105093-57.4818505136532130.3846434085631.0972071050931
12118135.378679881299-31.7405155016499132.36183562035117.3786798812985
13115121.158690507631-25.4977183397736134.3390278321436.15869050763089
14126152.112577072273-35.2209348015702135.10835772929726.1125770722727
15141149.149790385323-3.02747801177545135.8776876264528.14979038532326
16135142.353648187575-8.29905418525078135.9454059976767.35364818757483
17125119.72416444429-5.73728881319014136.0131243689-5.27583555570953
18149128.45404557282532.3366341296942137.209320297481-20.5459544271751
19170131.35060223692570.243881537013138.405516226062-38.6493977630751
20170130.63916127125168.0494327275684141.311406001181-39.3608387287492
21158154.34437818631917.4383260373816144.217295776299-3.65562181368108
22133138.726366614332-21.0634315333585148.3370649190275.72636661433162
23114133.025016451899-57.4818505136532152.45683406175419.0250164518989
24140155.61485924174-31.7405155016499156.1256562599115.61485924174
25145155.703239881708-25.4977183397736159.79447845806510.7032398817081
26150173.529500350016-35.2209348015702161.69143445155523.5295003500156
27178195.439087566732-3.02747801177545163.58839044504417.4390875667318
28163169.697380992963-8.29905418525078164.6016731922886.69738099296276
29172184.122332873658-5.73728881319014165.61495593953212.1223328736577
30178156.4349086371332.3366341296942167.228457233176-21.5650913628699
31199158.91415993616870.243881537013168.841958526819-40.085840063832
32199158.74354400965668.0494327275684171.207023262775-40.2564559903437
33184176.98958596388717.4383260373816173.572087998732-7.01041403611319
34162168.51079382209-21.0634315333585176.5526377112696.51079382208965
35146169.948663089847-57.4818505136532179.53318742380623.9486630898471
36166181.112749390396-31.7405155016499182.62776611125415.1127493903957
37171181.775373541071-25.4977183397736185.72234479870210.7753735410714
38180207.404617284177-35.2209348015702187.81631751739327.4046172841769
39193199.117187775691-3.02747801177545189.9102902360846.11718777569118
40181179.167886761944-8.29905418525078191.131167423307-1.83211323805642
41183179.38524420266-5.73728881319014192.35204461053-3.61475579734
42218209.59754925746432.3366341296942194.065816612842-8.40245074253599
43230193.97652984783470.243881537013195.779588615153-36.0234701521665
44242217.16918008428268.0494327275684198.781387188149-24.8308199157175
45209198.77848820147417.4383260373816201.783185761145-10.2215117985264
46191196.994743228647-21.0634315333585206.0686883047125.99474322864674
47172191.127659665374-57.4818505136532210.35419084827919.1276596653744
48194205.555637817977-31.7405155016499214.18487768367311.5556378179767
49196199.482153820706-25.4977183397736218.0155645190683.48215382070597
50196207.094595379858-35.2209348015702220.12633942171211.0945953798577
51236252.790363687418-3.02747801177545222.23711432435716.7903636874181
52235255.361488098016-8.29905418525078222.93756608723520.361488098016
53229240.099270963078-5.73728881319014223.63801785011211.0992709630779
54243229.87054596364332.3366341296942223.792819906663-13.1294540363569
55264233.80849649977470.243881537013223.947621963213-30.1915035002262
56272252.006292276868.0494327275684223.944274995632-19.9937077232004
57237232.62074593456817.4383260373816223.940928028051-4.37925406543229
58211218.46868162454-21.0634315333585224.5947499088197.46868162453961
59180192.233278724066-57.4818505136532225.24857178958712.2332787240661
60201206.719013989328-31.7405155016499227.0215015123225.71901398932795
61204204.703287104717-25.4977183397736228.7944312350570.703287104716821
62188180.667428897014-35.2209348015702230.553505904556-7.33257110298555
63235240.714897437721-3.02747801177545232.3125805740555.71489743772079
64227228.466222166896-8.29905418525078233.8328320183551.46622216689605
65234238.384205350535-5.73728881319014235.3530834626554.3842053505353
66264257.95926594350832.3366341296942237.704099926798-6.04073405649189
67302293.70100207204670.243881537013240.055116390941-8.2989979279535
68293274.70401830714568.0494327275684243.246548965287-18.2959816928551
69259254.12369242298617.4383260373816246.437981539633-4.87630757701444
70229228.959774829309-21.0634315333585250.103656704049-0.0402251706908316
71203209.712518645187-57.4818505136532253.7693318684666.71251864518737
72229231.656908610151-31.7405155016499258.0836068914982.65690861015145
73242247.099836425243-25.4977183397736262.3978819145315.09983642524253
74233234.466420806155-35.2209348015702266.7545139954151.46642080615493
75267265.916331935476-3.02747801177545271.111146076299-1.08366806452398
76269271.460644361895-8.29905418525078274.8384098233562.46064436189471
77270267.171615242777-5.73728881319014278.565673570413-2.82838475722252
78315315.57720166744432.3366341296942282.0861642028620.577201667444172
79364372.14946362767770.243881537013285.6066548353118.14946362767654
80347336.59906791886468.0494327275684289.351499353568-10.400932081136
81312313.46533009079417.4383260373816293.0963438718251.46533009079383
82274271.987392513557-21.0634315333585297.076039019802-2.01260748644341
83237230.426116345874-57.4818505136532301.055734167779-6.57388365412612
84278282.334153061374-31.7405155016499305.4063624402754.33415306137448
85284283.740727627002-25.4977183397736309.756990712771-0.259272372997941
86277275.191453926064-35.2209348015702314.029480875506-1.80854607393587
87317318.725506973535-3.02747801177545318.3019710382411.72550697353483
88313312.591984804652-8.29905418525078321.707069380599-0.408015195348241
89318316.625121090233-5.73728881319014325.112167722957-1.37487890976729
90374388.01197714989932.3366341296942327.65138872040614.0119771498995
91413425.56550874513270.243881537013330.19060971785512.5655087451319
92405409.4674628264468.0494327275684332.4831044459924.46746282643971
93355357.7860747884917.4383260373816334.7755991741292.78607478848983
94306295.714136380013-21.0634315333585337.349295153346-10.2858636199874
95271259.55885938109-57.4818505136532339.922991132563-11.4411406189101
96306300.178745914256-31.7405155016499343.561769587394-5.82125408574393
97315308.297170297549-25.4977183397736347.200548042224-6.70282970245074
98301285.309649597637-35.2209348015702351.911285203933-15.6903504023632
99356358.405455646133-3.02747801177545356.6220223656422.40545564613308
100348343.309029557603-8.29905418525078360.990024627648-4.69097044239692
101355350.379261923537-5.73728881319014365.358026889653-4.62073807646283
102422443.43804701039632.3366341296942368.2253188599121.4380470103961
103465488.66350763282170.243881537013371.09261083016623.6635076328208
104467493.74885446647868.0494327275684372.20171280595326.7488544664784
105404417.25085918087817.4383260373816373.3108147817413.2508591808784
106347341.994502619741-21.0634315333585373.068928913618-5.0054973802595
107305294.654807468157-57.4818505136532372.827043045496-10.3451925318428
108336330.574168419744-31.7405155016499373.166347081905-5.42583158025559
109340331.992067221459-25.4977183397736373.505651118315-8.00793277854137
110318295.917234796298-35.2209348015702375.303700005273-22.0827652037024
111362349.925729119545-3.02747801177545377.10174889223-12.0742708804546
112348325.122465855012-8.29905418525078379.176588330239-22.877534144988
113363350.485861044943-5.73728881319014381.251427768248-12.5141389550575
114435454.78995191088132.3366341296942382.87341395942519.7899519108811
115491527.26071831238670.243881537013384.49540015060236.2607183123855
116505555.53766559061168.0494327275684386.4129016818250.5376655906112
117404402.23127074957917.4383260373816388.330403213039-1.76872925042085
118359348.388866476376-21.0634315333585390.674565056982-10.6111335236239
119310284.463123612728-57.4818505136532393.018726900926-25.5368763872724
120337309.398913673082-31.7405155016499396.341601828568-27.6010863269179
121360345.833241583564-25.4977183397736399.66447675621-14.1667584164365
122342314.317448303322-35.2209348015702404.903486498249-27.6825516966784
123406404.884981771488-3.02747801177545410.142496240287-1.11501822851153
124396383.954091264659-8.29905418525078416.344962920592-12.0459087353409
125420423.189859212294-5.73728881319014422.5474296008963.18985921229381
126472483.87371231805632.3366341296942427.7896535522511.8737123180562
127548592.72424095938470.243881537013433.03187750360344.7242409593842
128559613.51433013643368.0494327275684436.43623713599854.5143301364333
129463468.72107719422517.4383260373816439.8405967683945.72107719422468
130407392.687931319752-21.0634315333585442.375500213607-14.3120686802483
131362336.571446854833-57.4818505136532444.91040365882-25.4285531451667
132405393.100333883737-31.7405155016499448.640181617913-11.8996661162627
133417407.127758762768-25.4977183397736452.369959577005-9.87224123723178
134391359.408804900782-35.2209348015702457.812129900788-31.5911950992178
135419377.773177787205-3.02747801177545463.25430022457-41.226822212795
136461462.688631105859-8.29905418525078467.6104230793921.68863110585852
137472477.770742878976-5.73728881319014471.9665459342145.77074287897614
138535562.05506690831832.3366341296942475.60829896198727.0550669083185
139622694.50606647322670.243881537013479.25005198976172.5060664732265
140606660.76116520260268.0494327275684483.1894020698354.7611652026018
141508511.43292181271917.4383260373816487.1287521498993.43292181271931
142461452.310411781538-21.0634315333585490.753019751821-8.6895882184624
143390343.10456315991-57.4818505136532494.377287353743-46.8954368400896
144432398.310610449872-31.7405155016499497.429905051778-33.6893895501282

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 112 & 122.310369902516 & -25.4977183397736 & 127.187348437258 & 10.310369902516 \tabularnewline
2 & 118 & 144.571402815284 & -35.2209348015702 & 126.649531986286 & 26.5714028152841 \tabularnewline
3 & 132 & 140.915762476461 & -3.02747801177545 & 126.111715535315 & 8.91576247646083 \tabularnewline
4 & 129 & 140.100122400179 & -8.29905418525078 & 126.198931785072 & 11.1001224001792 \tabularnewline
5 & 121 & 121.451140778362 & -5.73728881319014 & 126.286148034829 & 0.451140778361591 \tabularnewline
6 & 135 & 110.930342781525 & 32.3366341296942 & 126.733023088781 & -24.0696572184753 \tabularnewline
7 & 148 & 98.5762203202533 & 70.243881537013 & 127.179898142734 & -49.4237796797467 \tabularnewline
8 & 148 & 100.53435082393 & 68.0494327275684 & 127.416216448501 & -47.4656491760699 \tabularnewline
9 & 136 & 126.909139208349 & 17.4383260373816 & 127.652534754269 & -9.09086079165081 \tabularnewline
10 & 119 & 130.044842451944 & -21.0634315333585 & 129.018589081415 & 11.0448424519439 \tabularnewline
11 & 104 & 135.097207105093 & -57.4818505136532 & 130.38464340856 & 31.0972071050931 \tabularnewline
12 & 118 & 135.378679881299 & -31.7405155016499 & 132.361835620351 & 17.3786798812985 \tabularnewline
13 & 115 & 121.158690507631 & -25.4977183397736 & 134.339027832143 & 6.15869050763089 \tabularnewline
14 & 126 & 152.112577072273 & -35.2209348015702 & 135.108357729297 & 26.1125770722727 \tabularnewline
15 & 141 & 149.149790385323 & -3.02747801177545 & 135.877687626452 & 8.14979038532326 \tabularnewline
16 & 135 & 142.353648187575 & -8.29905418525078 & 135.945405997676 & 7.35364818757483 \tabularnewline
17 & 125 & 119.72416444429 & -5.73728881319014 & 136.0131243689 & -5.27583555570953 \tabularnewline
18 & 149 & 128.454045572825 & 32.3366341296942 & 137.209320297481 & -20.5459544271751 \tabularnewline
19 & 170 & 131.350602236925 & 70.243881537013 & 138.405516226062 & -38.6493977630751 \tabularnewline
20 & 170 & 130.639161271251 & 68.0494327275684 & 141.311406001181 & -39.3608387287492 \tabularnewline
21 & 158 & 154.344378186319 & 17.4383260373816 & 144.217295776299 & -3.65562181368108 \tabularnewline
22 & 133 & 138.726366614332 & -21.0634315333585 & 148.337064919027 & 5.72636661433162 \tabularnewline
23 & 114 & 133.025016451899 & -57.4818505136532 & 152.456834061754 & 19.0250164518989 \tabularnewline
24 & 140 & 155.61485924174 & -31.7405155016499 & 156.12565625991 & 15.61485924174 \tabularnewline
25 & 145 & 155.703239881708 & -25.4977183397736 & 159.794478458065 & 10.7032398817081 \tabularnewline
26 & 150 & 173.529500350016 & -35.2209348015702 & 161.691434451555 & 23.5295003500156 \tabularnewline
27 & 178 & 195.439087566732 & -3.02747801177545 & 163.588390445044 & 17.4390875667318 \tabularnewline
28 & 163 & 169.697380992963 & -8.29905418525078 & 164.601673192288 & 6.69738099296276 \tabularnewline
29 & 172 & 184.122332873658 & -5.73728881319014 & 165.614955939532 & 12.1223328736577 \tabularnewline
30 & 178 & 156.43490863713 & 32.3366341296942 & 167.228457233176 & -21.5650913628699 \tabularnewline
31 & 199 & 158.914159936168 & 70.243881537013 & 168.841958526819 & -40.085840063832 \tabularnewline
32 & 199 & 158.743544009656 & 68.0494327275684 & 171.207023262775 & -40.2564559903437 \tabularnewline
33 & 184 & 176.989585963887 & 17.4383260373816 & 173.572087998732 & -7.01041403611319 \tabularnewline
34 & 162 & 168.51079382209 & -21.0634315333585 & 176.552637711269 & 6.51079382208965 \tabularnewline
35 & 146 & 169.948663089847 & -57.4818505136532 & 179.533187423806 & 23.9486630898471 \tabularnewline
36 & 166 & 181.112749390396 & -31.7405155016499 & 182.627766111254 & 15.1127493903957 \tabularnewline
37 & 171 & 181.775373541071 & -25.4977183397736 & 185.722344798702 & 10.7753735410714 \tabularnewline
38 & 180 & 207.404617284177 & -35.2209348015702 & 187.816317517393 & 27.4046172841769 \tabularnewline
39 & 193 & 199.117187775691 & -3.02747801177545 & 189.910290236084 & 6.11718777569118 \tabularnewline
40 & 181 & 179.167886761944 & -8.29905418525078 & 191.131167423307 & -1.83211323805642 \tabularnewline
41 & 183 & 179.38524420266 & -5.73728881319014 & 192.35204461053 & -3.61475579734 \tabularnewline
42 & 218 & 209.597549257464 & 32.3366341296942 & 194.065816612842 & -8.40245074253599 \tabularnewline
43 & 230 & 193.976529847834 & 70.243881537013 & 195.779588615153 & -36.0234701521665 \tabularnewline
44 & 242 & 217.169180084282 & 68.0494327275684 & 198.781387188149 & -24.8308199157175 \tabularnewline
45 & 209 & 198.778488201474 & 17.4383260373816 & 201.783185761145 & -10.2215117985264 \tabularnewline
46 & 191 & 196.994743228647 & -21.0634315333585 & 206.068688304712 & 5.99474322864674 \tabularnewline
47 & 172 & 191.127659665374 & -57.4818505136532 & 210.354190848279 & 19.1276596653744 \tabularnewline
48 & 194 & 205.555637817977 & -31.7405155016499 & 214.184877683673 & 11.5556378179767 \tabularnewline
49 & 196 & 199.482153820706 & -25.4977183397736 & 218.015564519068 & 3.48215382070597 \tabularnewline
50 & 196 & 207.094595379858 & -35.2209348015702 & 220.126339421712 & 11.0945953798577 \tabularnewline
51 & 236 & 252.790363687418 & -3.02747801177545 & 222.237114324357 & 16.7903636874181 \tabularnewline
52 & 235 & 255.361488098016 & -8.29905418525078 & 222.937566087235 & 20.361488098016 \tabularnewline
53 & 229 & 240.099270963078 & -5.73728881319014 & 223.638017850112 & 11.0992709630779 \tabularnewline
54 & 243 & 229.870545963643 & 32.3366341296942 & 223.792819906663 & -13.1294540363569 \tabularnewline
55 & 264 & 233.808496499774 & 70.243881537013 & 223.947621963213 & -30.1915035002262 \tabularnewline
56 & 272 & 252.0062922768 & 68.0494327275684 & 223.944274995632 & -19.9937077232004 \tabularnewline
57 & 237 & 232.620745934568 & 17.4383260373816 & 223.940928028051 & -4.37925406543229 \tabularnewline
58 & 211 & 218.46868162454 & -21.0634315333585 & 224.594749908819 & 7.46868162453961 \tabularnewline
59 & 180 & 192.233278724066 & -57.4818505136532 & 225.248571789587 & 12.2332787240661 \tabularnewline
60 & 201 & 206.719013989328 & -31.7405155016499 & 227.021501512322 & 5.71901398932795 \tabularnewline
61 & 204 & 204.703287104717 & -25.4977183397736 & 228.794431235057 & 0.703287104716821 \tabularnewline
62 & 188 & 180.667428897014 & -35.2209348015702 & 230.553505904556 & -7.33257110298555 \tabularnewline
63 & 235 & 240.714897437721 & -3.02747801177545 & 232.312580574055 & 5.71489743772079 \tabularnewline
64 & 227 & 228.466222166896 & -8.29905418525078 & 233.832832018355 & 1.46622216689605 \tabularnewline
65 & 234 & 238.384205350535 & -5.73728881319014 & 235.353083462655 & 4.3842053505353 \tabularnewline
66 & 264 & 257.959265943508 & 32.3366341296942 & 237.704099926798 & -6.04073405649189 \tabularnewline
67 & 302 & 293.701002072046 & 70.243881537013 & 240.055116390941 & -8.2989979279535 \tabularnewline
68 & 293 & 274.704018307145 & 68.0494327275684 & 243.246548965287 & -18.2959816928551 \tabularnewline
69 & 259 & 254.123692422986 & 17.4383260373816 & 246.437981539633 & -4.87630757701444 \tabularnewline
70 & 229 & 228.959774829309 & -21.0634315333585 & 250.103656704049 & -0.0402251706908316 \tabularnewline
71 & 203 & 209.712518645187 & -57.4818505136532 & 253.769331868466 & 6.71251864518737 \tabularnewline
72 & 229 & 231.656908610151 & -31.7405155016499 & 258.083606891498 & 2.65690861015145 \tabularnewline
73 & 242 & 247.099836425243 & -25.4977183397736 & 262.397881914531 & 5.09983642524253 \tabularnewline
74 & 233 & 234.466420806155 & -35.2209348015702 & 266.754513995415 & 1.46642080615493 \tabularnewline
75 & 267 & 265.916331935476 & -3.02747801177545 & 271.111146076299 & -1.08366806452398 \tabularnewline
76 & 269 & 271.460644361895 & -8.29905418525078 & 274.838409823356 & 2.46064436189471 \tabularnewline
77 & 270 & 267.171615242777 & -5.73728881319014 & 278.565673570413 & -2.82838475722252 \tabularnewline
78 & 315 & 315.577201667444 & 32.3366341296942 & 282.086164202862 & 0.577201667444172 \tabularnewline
79 & 364 & 372.149463627677 & 70.243881537013 & 285.606654835311 & 8.14946362767654 \tabularnewline
80 & 347 & 336.599067918864 & 68.0494327275684 & 289.351499353568 & -10.400932081136 \tabularnewline
81 & 312 & 313.465330090794 & 17.4383260373816 & 293.096343871825 & 1.46533009079383 \tabularnewline
82 & 274 & 271.987392513557 & -21.0634315333585 & 297.076039019802 & -2.01260748644341 \tabularnewline
83 & 237 & 230.426116345874 & -57.4818505136532 & 301.055734167779 & -6.57388365412612 \tabularnewline
84 & 278 & 282.334153061374 & -31.7405155016499 & 305.406362440275 & 4.33415306137448 \tabularnewline
85 & 284 & 283.740727627002 & -25.4977183397736 & 309.756990712771 & -0.259272372997941 \tabularnewline
86 & 277 & 275.191453926064 & -35.2209348015702 & 314.029480875506 & -1.80854607393587 \tabularnewline
87 & 317 & 318.725506973535 & -3.02747801177545 & 318.301971038241 & 1.72550697353483 \tabularnewline
88 & 313 & 312.591984804652 & -8.29905418525078 & 321.707069380599 & -0.408015195348241 \tabularnewline
89 & 318 & 316.625121090233 & -5.73728881319014 & 325.112167722957 & -1.37487890976729 \tabularnewline
90 & 374 & 388.011977149899 & 32.3366341296942 & 327.651388720406 & 14.0119771498995 \tabularnewline
91 & 413 & 425.565508745132 & 70.243881537013 & 330.190609717855 & 12.5655087451319 \tabularnewline
92 & 405 & 409.46746282644 & 68.0494327275684 & 332.483104445992 & 4.46746282643971 \tabularnewline
93 & 355 & 357.78607478849 & 17.4383260373816 & 334.775599174129 & 2.78607478848983 \tabularnewline
94 & 306 & 295.714136380013 & -21.0634315333585 & 337.349295153346 & -10.2858636199874 \tabularnewline
95 & 271 & 259.55885938109 & -57.4818505136532 & 339.922991132563 & -11.4411406189101 \tabularnewline
96 & 306 & 300.178745914256 & -31.7405155016499 & 343.561769587394 & -5.82125408574393 \tabularnewline
97 & 315 & 308.297170297549 & -25.4977183397736 & 347.200548042224 & -6.70282970245074 \tabularnewline
98 & 301 & 285.309649597637 & -35.2209348015702 & 351.911285203933 & -15.6903504023632 \tabularnewline
99 & 356 & 358.405455646133 & -3.02747801177545 & 356.622022365642 & 2.40545564613308 \tabularnewline
100 & 348 & 343.309029557603 & -8.29905418525078 & 360.990024627648 & -4.69097044239692 \tabularnewline
101 & 355 & 350.379261923537 & -5.73728881319014 & 365.358026889653 & -4.62073807646283 \tabularnewline
102 & 422 & 443.438047010396 & 32.3366341296942 & 368.22531885991 & 21.4380470103961 \tabularnewline
103 & 465 & 488.663507632821 & 70.243881537013 & 371.092610830166 & 23.6635076328208 \tabularnewline
104 & 467 & 493.748854466478 & 68.0494327275684 & 372.201712805953 & 26.7488544664784 \tabularnewline
105 & 404 & 417.250859180878 & 17.4383260373816 & 373.31081478174 & 13.2508591808784 \tabularnewline
106 & 347 & 341.994502619741 & -21.0634315333585 & 373.068928913618 & -5.0054973802595 \tabularnewline
107 & 305 & 294.654807468157 & -57.4818505136532 & 372.827043045496 & -10.3451925318428 \tabularnewline
108 & 336 & 330.574168419744 & -31.7405155016499 & 373.166347081905 & -5.42583158025559 \tabularnewline
109 & 340 & 331.992067221459 & -25.4977183397736 & 373.505651118315 & -8.00793277854137 \tabularnewline
110 & 318 & 295.917234796298 & -35.2209348015702 & 375.303700005273 & -22.0827652037024 \tabularnewline
111 & 362 & 349.925729119545 & -3.02747801177545 & 377.10174889223 & -12.0742708804546 \tabularnewline
112 & 348 & 325.122465855012 & -8.29905418525078 & 379.176588330239 & -22.877534144988 \tabularnewline
113 & 363 & 350.485861044943 & -5.73728881319014 & 381.251427768248 & -12.5141389550575 \tabularnewline
114 & 435 & 454.789951910881 & 32.3366341296942 & 382.873413959425 & 19.7899519108811 \tabularnewline
115 & 491 & 527.260718312386 & 70.243881537013 & 384.495400150602 & 36.2607183123855 \tabularnewline
116 & 505 & 555.537665590611 & 68.0494327275684 & 386.41290168182 & 50.5376655906112 \tabularnewline
117 & 404 & 402.231270749579 & 17.4383260373816 & 388.330403213039 & -1.76872925042085 \tabularnewline
118 & 359 & 348.388866476376 & -21.0634315333585 & 390.674565056982 & -10.6111335236239 \tabularnewline
119 & 310 & 284.463123612728 & -57.4818505136532 & 393.018726900926 & -25.5368763872724 \tabularnewline
120 & 337 & 309.398913673082 & -31.7405155016499 & 396.341601828568 & -27.6010863269179 \tabularnewline
121 & 360 & 345.833241583564 & -25.4977183397736 & 399.66447675621 & -14.1667584164365 \tabularnewline
122 & 342 & 314.317448303322 & -35.2209348015702 & 404.903486498249 & -27.6825516966784 \tabularnewline
123 & 406 & 404.884981771488 & -3.02747801177545 & 410.142496240287 & -1.11501822851153 \tabularnewline
124 & 396 & 383.954091264659 & -8.29905418525078 & 416.344962920592 & -12.0459087353409 \tabularnewline
125 & 420 & 423.189859212294 & -5.73728881319014 & 422.547429600896 & 3.18985921229381 \tabularnewline
126 & 472 & 483.873712318056 & 32.3366341296942 & 427.78965355225 & 11.8737123180562 \tabularnewline
127 & 548 & 592.724240959384 & 70.243881537013 & 433.031877503603 & 44.7242409593842 \tabularnewline
128 & 559 & 613.514330136433 & 68.0494327275684 & 436.436237135998 & 54.5143301364333 \tabularnewline
129 & 463 & 468.721077194225 & 17.4383260373816 & 439.840596768394 & 5.72107719422468 \tabularnewline
130 & 407 & 392.687931319752 & -21.0634315333585 & 442.375500213607 & -14.3120686802483 \tabularnewline
131 & 362 & 336.571446854833 & -57.4818505136532 & 444.91040365882 & -25.4285531451667 \tabularnewline
132 & 405 & 393.100333883737 & -31.7405155016499 & 448.640181617913 & -11.8996661162627 \tabularnewline
133 & 417 & 407.127758762768 & -25.4977183397736 & 452.369959577005 & -9.87224123723178 \tabularnewline
134 & 391 & 359.408804900782 & -35.2209348015702 & 457.812129900788 & -31.5911950992178 \tabularnewline
135 & 419 & 377.773177787205 & -3.02747801177545 & 463.25430022457 & -41.226822212795 \tabularnewline
136 & 461 & 462.688631105859 & -8.29905418525078 & 467.610423079392 & 1.68863110585852 \tabularnewline
137 & 472 & 477.770742878976 & -5.73728881319014 & 471.966545934214 & 5.77074287897614 \tabularnewline
138 & 535 & 562.055066908318 & 32.3366341296942 & 475.608298961987 & 27.0550669083185 \tabularnewline
139 & 622 & 694.506066473226 & 70.243881537013 & 479.250051989761 & 72.5060664732265 \tabularnewline
140 & 606 & 660.761165202602 & 68.0494327275684 & 483.18940206983 & 54.7611652026018 \tabularnewline
141 & 508 & 511.432921812719 & 17.4383260373816 & 487.128752149899 & 3.43292181271931 \tabularnewline
142 & 461 & 452.310411781538 & -21.0634315333585 & 490.753019751821 & -8.6895882184624 \tabularnewline
143 & 390 & 343.10456315991 & -57.4818505136532 & 494.377287353743 & -46.8954368400896 \tabularnewline
144 & 432 & 398.310610449872 & -31.7405155016499 & 497.429905051778 & -33.6893895501282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147260&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]112[/C][C]122.310369902516[/C][C]-25.4977183397736[/C][C]127.187348437258[/C][C]10.310369902516[/C][/ROW]
[ROW][C]2[/C][C]118[/C][C]144.571402815284[/C][C]-35.2209348015702[/C][C]126.649531986286[/C][C]26.5714028152841[/C][/ROW]
[ROW][C]3[/C][C]132[/C][C]140.915762476461[/C][C]-3.02747801177545[/C][C]126.111715535315[/C][C]8.91576247646083[/C][/ROW]
[ROW][C]4[/C][C]129[/C][C]140.100122400179[/C][C]-8.29905418525078[/C][C]126.198931785072[/C][C]11.1001224001792[/C][/ROW]
[ROW][C]5[/C][C]121[/C][C]121.451140778362[/C][C]-5.73728881319014[/C][C]126.286148034829[/C][C]0.451140778361591[/C][/ROW]
[ROW][C]6[/C][C]135[/C][C]110.930342781525[/C][C]32.3366341296942[/C][C]126.733023088781[/C][C]-24.0696572184753[/C][/ROW]
[ROW][C]7[/C][C]148[/C][C]98.5762203202533[/C][C]70.243881537013[/C][C]127.179898142734[/C][C]-49.4237796797467[/C][/ROW]
[ROW][C]8[/C][C]148[/C][C]100.53435082393[/C][C]68.0494327275684[/C][C]127.416216448501[/C][C]-47.4656491760699[/C][/ROW]
[ROW][C]9[/C][C]136[/C][C]126.909139208349[/C][C]17.4383260373816[/C][C]127.652534754269[/C][C]-9.09086079165081[/C][/ROW]
[ROW][C]10[/C][C]119[/C][C]130.044842451944[/C][C]-21.0634315333585[/C][C]129.018589081415[/C][C]11.0448424519439[/C][/ROW]
[ROW][C]11[/C][C]104[/C][C]135.097207105093[/C][C]-57.4818505136532[/C][C]130.38464340856[/C][C]31.0972071050931[/C][/ROW]
[ROW][C]12[/C][C]118[/C][C]135.378679881299[/C][C]-31.7405155016499[/C][C]132.361835620351[/C][C]17.3786798812985[/C][/ROW]
[ROW][C]13[/C][C]115[/C][C]121.158690507631[/C][C]-25.4977183397736[/C][C]134.339027832143[/C][C]6.15869050763089[/C][/ROW]
[ROW][C]14[/C][C]126[/C][C]152.112577072273[/C][C]-35.2209348015702[/C][C]135.108357729297[/C][C]26.1125770722727[/C][/ROW]
[ROW][C]15[/C][C]141[/C][C]149.149790385323[/C][C]-3.02747801177545[/C][C]135.877687626452[/C][C]8.14979038532326[/C][/ROW]
[ROW][C]16[/C][C]135[/C][C]142.353648187575[/C][C]-8.29905418525078[/C][C]135.945405997676[/C][C]7.35364818757483[/C][/ROW]
[ROW][C]17[/C][C]125[/C][C]119.72416444429[/C][C]-5.73728881319014[/C][C]136.0131243689[/C][C]-5.27583555570953[/C][/ROW]
[ROW][C]18[/C][C]149[/C][C]128.454045572825[/C][C]32.3366341296942[/C][C]137.209320297481[/C][C]-20.5459544271751[/C][/ROW]
[ROW][C]19[/C][C]170[/C][C]131.350602236925[/C][C]70.243881537013[/C][C]138.405516226062[/C][C]-38.6493977630751[/C][/ROW]
[ROW][C]20[/C][C]170[/C][C]130.639161271251[/C][C]68.0494327275684[/C][C]141.311406001181[/C][C]-39.3608387287492[/C][/ROW]
[ROW][C]21[/C][C]158[/C][C]154.344378186319[/C][C]17.4383260373816[/C][C]144.217295776299[/C][C]-3.65562181368108[/C][/ROW]
[ROW][C]22[/C][C]133[/C][C]138.726366614332[/C][C]-21.0634315333585[/C][C]148.337064919027[/C][C]5.72636661433162[/C][/ROW]
[ROW][C]23[/C][C]114[/C][C]133.025016451899[/C][C]-57.4818505136532[/C][C]152.456834061754[/C][C]19.0250164518989[/C][/ROW]
[ROW][C]24[/C][C]140[/C][C]155.61485924174[/C][C]-31.7405155016499[/C][C]156.12565625991[/C][C]15.61485924174[/C][/ROW]
[ROW][C]25[/C][C]145[/C][C]155.703239881708[/C][C]-25.4977183397736[/C][C]159.794478458065[/C][C]10.7032398817081[/C][/ROW]
[ROW][C]26[/C][C]150[/C][C]173.529500350016[/C][C]-35.2209348015702[/C][C]161.691434451555[/C][C]23.5295003500156[/C][/ROW]
[ROW][C]27[/C][C]178[/C][C]195.439087566732[/C][C]-3.02747801177545[/C][C]163.588390445044[/C][C]17.4390875667318[/C][/ROW]
[ROW][C]28[/C][C]163[/C][C]169.697380992963[/C][C]-8.29905418525078[/C][C]164.601673192288[/C][C]6.69738099296276[/C][/ROW]
[ROW][C]29[/C][C]172[/C][C]184.122332873658[/C][C]-5.73728881319014[/C][C]165.614955939532[/C][C]12.1223328736577[/C][/ROW]
[ROW][C]30[/C][C]178[/C][C]156.43490863713[/C][C]32.3366341296942[/C][C]167.228457233176[/C][C]-21.5650913628699[/C][/ROW]
[ROW][C]31[/C][C]199[/C][C]158.914159936168[/C][C]70.243881537013[/C][C]168.841958526819[/C][C]-40.085840063832[/C][/ROW]
[ROW][C]32[/C][C]199[/C][C]158.743544009656[/C][C]68.0494327275684[/C][C]171.207023262775[/C][C]-40.2564559903437[/C][/ROW]
[ROW][C]33[/C][C]184[/C][C]176.989585963887[/C][C]17.4383260373816[/C][C]173.572087998732[/C][C]-7.01041403611319[/C][/ROW]
[ROW][C]34[/C][C]162[/C][C]168.51079382209[/C][C]-21.0634315333585[/C][C]176.552637711269[/C][C]6.51079382208965[/C][/ROW]
[ROW][C]35[/C][C]146[/C][C]169.948663089847[/C][C]-57.4818505136532[/C][C]179.533187423806[/C][C]23.9486630898471[/C][/ROW]
[ROW][C]36[/C][C]166[/C][C]181.112749390396[/C][C]-31.7405155016499[/C][C]182.627766111254[/C][C]15.1127493903957[/C][/ROW]
[ROW][C]37[/C][C]171[/C][C]181.775373541071[/C][C]-25.4977183397736[/C][C]185.722344798702[/C][C]10.7753735410714[/C][/ROW]
[ROW][C]38[/C][C]180[/C][C]207.404617284177[/C][C]-35.2209348015702[/C][C]187.816317517393[/C][C]27.4046172841769[/C][/ROW]
[ROW][C]39[/C][C]193[/C][C]199.117187775691[/C][C]-3.02747801177545[/C][C]189.910290236084[/C][C]6.11718777569118[/C][/ROW]
[ROW][C]40[/C][C]181[/C][C]179.167886761944[/C][C]-8.29905418525078[/C][C]191.131167423307[/C][C]-1.83211323805642[/C][/ROW]
[ROW][C]41[/C][C]183[/C][C]179.38524420266[/C][C]-5.73728881319014[/C][C]192.35204461053[/C][C]-3.61475579734[/C][/ROW]
[ROW][C]42[/C][C]218[/C][C]209.597549257464[/C][C]32.3366341296942[/C][C]194.065816612842[/C][C]-8.40245074253599[/C][/ROW]
[ROW][C]43[/C][C]230[/C][C]193.976529847834[/C][C]70.243881537013[/C][C]195.779588615153[/C][C]-36.0234701521665[/C][/ROW]
[ROW][C]44[/C][C]242[/C][C]217.169180084282[/C][C]68.0494327275684[/C][C]198.781387188149[/C][C]-24.8308199157175[/C][/ROW]
[ROW][C]45[/C][C]209[/C][C]198.778488201474[/C][C]17.4383260373816[/C][C]201.783185761145[/C][C]-10.2215117985264[/C][/ROW]
[ROW][C]46[/C][C]191[/C][C]196.994743228647[/C][C]-21.0634315333585[/C][C]206.068688304712[/C][C]5.99474322864674[/C][/ROW]
[ROW][C]47[/C][C]172[/C][C]191.127659665374[/C][C]-57.4818505136532[/C][C]210.354190848279[/C][C]19.1276596653744[/C][/ROW]
[ROW][C]48[/C][C]194[/C][C]205.555637817977[/C][C]-31.7405155016499[/C][C]214.184877683673[/C][C]11.5556378179767[/C][/ROW]
[ROW][C]49[/C][C]196[/C][C]199.482153820706[/C][C]-25.4977183397736[/C][C]218.015564519068[/C][C]3.48215382070597[/C][/ROW]
[ROW][C]50[/C][C]196[/C][C]207.094595379858[/C][C]-35.2209348015702[/C][C]220.126339421712[/C][C]11.0945953798577[/C][/ROW]
[ROW][C]51[/C][C]236[/C][C]252.790363687418[/C][C]-3.02747801177545[/C][C]222.237114324357[/C][C]16.7903636874181[/C][/ROW]
[ROW][C]52[/C][C]235[/C][C]255.361488098016[/C][C]-8.29905418525078[/C][C]222.937566087235[/C][C]20.361488098016[/C][/ROW]
[ROW][C]53[/C][C]229[/C][C]240.099270963078[/C][C]-5.73728881319014[/C][C]223.638017850112[/C][C]11.0992709630779[/C][/ROW]
[ROW][C]54[/C][C]243[/C][C]229.870545963643[/C][C]32.3366341296942[/C][C]223.792819906663[/C][C]-13.1294540363569[/C][/ROW]
[ROW][C]55[/C][C]264[/C][C]233.808496499774[/C][C]70.243881537013[/C][C]223.947621963213[/C][C]-30.1915035002262[/C][/ROW]
[ROW][C]56[/C][C]272[/C][C]252.0062922768[/C][C]68.0494327275684[/C][C]223.944274995632[/C][C]-19.9937077232004[/C][/ROW]
[ROW][C]57[/C][C]237[/C][C]232.620745934568[/C][C]17.4383260373816[/C][C]223.940928028051[/C][C]-4.37925406543229[/C][/ROW]
[ROW][C]58[/C][C]211[/C][C]218.46868162454[/C][C]-21.0634315333585[/C][C]224.594749908819[/C][C]7.46868162453961[/C][/ROW]
[ROW][C]59[/C][C]180[/C][C]192.233278724066[/C][C]-57.4818505136532[/C][C]225.248571789587[/C][C]12.2332787240661[/C][/ROW]
[ROW][C]60[/C][C]201[/C][C]206.719013989328[/C][C]-31.7405155016499[/C][C]227.021501512322[/C][C]5.71901398932795[/C][/ROW]
[ROW][C]61[/C][C]204[/C][C]204.703287104717[/C][C]-25.4977183397736[/C][C]228.794431235057[/C][C]0.703287104716821[/C][/ROW]
[ROW][C]62[/C][C]188[/C][C]180.667428897014[/C][C]-35.2209348015702[/C][C]230.553505904556[/C][C]-7.33257110298555[/C][/ROW]
[ROW][C]63[/C][C]235[/C][C]240.714897437721[/C][C]-3.02747801177545[/C][C]232.312580574055[/C][C]5.71489743772079[/C][/ROW]
[ROW][C]64[/C][C]227[/C][C]228.466222166896[/C][C]-8.29905418525078[/C][C]233.832832018355[/C][C]1.46622216689605[/C][/ROW]
[ROW][C]65[/C][C]234[/C][C]238.384205350535[/C][C]-5.73728881319014[/C][C]235.353083462655[/C][C]4.3842053505353[/C][/ROW]
[ROW][C]66[/C][C]264[/C][C]257.959265943508[/C][C]32.3366341296942[/C][C]237.704099926798[/C][C]-6.04073405649189[/C][/ROW]
[ROW][C]67[/C][C]302[/C][C]293.701002072046[/C][C]70.243881537013[/C][C]240.055116390941[/C][C]-8.2989979279535[/C][/ROW]
[ROW][C]68[/C][C]293[/C][C]274.704018307145[/C][C]68.0494327275684[/C][C]243.246548965287[/C][C]-18.2959816928551[/C][/ROW]
[ROW][C]69[/C][C]259[/C][C]254.123692422986[/C][C]17.4383260373816[/C][C]246.437981539633[/C][C]-4.87630757701444[/C][/ROW]
[ROW][C]70[/C][C]229[/C][C]228.959774829309[/C][C]-21.0634315333585[/C][C]250.103656704049[/C][C]-0.0402251706908316[/C][/ROW]
[ROW][C]71[/C][C]203[/C][C]209.712518645187[/C][C]-57.4818505136532[/C][C]253.769331868466[/C][C]6.71251864518737[/C][/ROW]
[ROW][C]72[/C][C]229[/C][C]231.656908610151[/C][C]-31.7405155016499[/C][C]258.083606891498[/C][C]2.65690861015145[/C][/ROW]
[ROW][C]73[/C][C]242[/C][C]247.099836425243[/C][C]-25.4977183397736[/C][C]262.397881914531[/C][C]5.09983642524253[/C][/ROW]
[ROW][C]74[/C][C]233[/C][C]234.466420806155[/C][C]-35.2209348015702[/C][C]266.754513995415[/C][C]1.46642080615493[/C][/ROW]
[ROW][C]75[/C][C]267[/C][C]265.916331935476[/C][C]-3.02747801177545[/C][C]271.111146076299[/C][C]-1.08366806452398[/C][/ROW]
[ROW][C]76[/C][C]269[/C][C]271.460644361895[/C][C]-8.29905418525078[/C][C]274.838409823356[/C][C]2.46064436189471[/C][/ROW]
[ROW][C]77[/C][C]270[/C][C]267.171615242777[/C][C]-5.73728881319014[/C][C]278.565673570413[/C][C]-2.82838475722252[/C][/ROW]
[ROW][C]78[/C][C]315[/C][C]315.577201667444[/C][C]32.3366341296942[/C][C]282.086164202862[/C][C]0.577201667444172[/C][/ROW]
[ROW][C]79[/C][C]364[/C][C]372.149463627677[/C][C]70.243881537013[/C][C]285.606654835311[/C][C]8.14946362767654[/C][/ROW]
[ROW][C]80[/C][C]347[/C][C]336.599067918864[/C][C]68.0494327275684[/C][C]289.351499353568[/C][C]-10.400932081136[/C][/ROW]
[ROW][C]81[/C][C]312[/C][C]313.465330090794[/C][C]17.4383260373816[/C][C]293.096343871825[/C][C]1.46533009079383[/C][/ROW]
[ROW][C]82[/C][C]274[/C][C]271.987392513557[/C][C]-21.0634315333585[/C][C]297.076039019802[/C][C]-2.01260748644341[/C][/ROW]
[ROW][C]83[/C][C]237[/C][C]230.426116345874[/C][C]-57.4818505136532[/C][C]301.055734167779[/C][C]-6.57388365412612[/C][/ROW]
[ROW][C]84[/C][C]278[/C][C]282.334153061374[/C][C]-31.7405155016499[/C][C]305.406362440275[/C][C]4.33415306137448[/C][/ROW]
[ROW][C]85[/C][C]284[/C][C]283.740727627002[/C][C]-25.4977183397736[/C][C]309.756990712771[/C][C]-0.259272372997941[/C][/ROW]
[ROW][C]86[/C][C]277[/C][C]275.191453926064[/C][C]-35.2209348015702[/C][C]314.029480875506[/C][C]-1.80854607393587[/C][/ROW]
[ROW][C]87[/C][C]317[/C][C]318.725506973535[/C][C]-3.02747801177545[/C][C]318.301971038241[/C][C]1.72550697353483[/C][/ROW]
[ROW][C]88[/C][C]313[/C][C]312.591984804652[/C][C]-8.29905418525078[/C][C]321.707069380599[/C][C]-0.408015195348241[/C][/ROW]
[ROW][C]89[/C][C]318[/C][C]316.625121090233[/C][C]-5.73728881319014[/C][C]325.112167722957[/C][C]-1.37487890976729[/C][/ROW]
[ROW][C]90[/C][C]374[/C][C]388.011977149899[/C][C]32.3366341296942[/C][C]327.651388720406[/C][C]14.0119771498995[/C][/ROW]
[ROW][C]91[/C][C]413[/C][C]425.565508745132[/C][C]70.243881537013[/C][C]330.190609717855[/C][C]12.5655087451319[/C][/ROW]
[ROW][C]92[/C][C]405[/C][C]409.46746282644[/C][C]68.0494327275684[/C][C]332.483104445992[/C][C]4.46746282643971[/C][/ROW]
[ROW][C]93[/C][C]355[/C][C]357.78607478849[/C][C]17.4383260373816[/C][C]334.775599174129[/C][C]2.78607478848983[/C][/ROW]
[ROW][C]94[/C][C]306[/C][C]295.714136380013[/C][C]-21.0634315333585[/C][C]337.349295153346[/C][C]-10.2858636199874[/C][/ROW]
[ROW][C]95[/C][C]271[/C][C]259.55885938109[/C][C]-57.4818505136532[/C][C]339.922991132563[/C][C]-11.4411406189101[/C][/ROW]
[ROW][C]96[/C][C]306[/C][C]300.178745914256[/C][C]-31.7405155016499[/C][C]343.561769587394[/C][C]-5.82125408574393[/C][/ROW]
[ROW][C]97[/C][C]315[/C][C]308.297170297549[/C][C]-25.4977183397736[/C][C]347.200548042224[/C][C]-6.70282970245074[/C][/ROW]
[ROW][C]98[/C][C]301[/C][C]285.309649597637[/C][C]-35.2209348015702[/C][C]351.911285203933[/C][C]-15.6903504023632[/C][/ROW]
[ROW][C]99[/C][C]356[/C][C]358.405455646133[/C][C]-3.02747801177545[/C][C]356.622022365642[/C][C]2.40545564613308[/C][/ROW]
[ROW][C]100[/C][C]348[/C][C]343.309029557603[/C][C]-8.29905418525078[/C][C]360.990024627648[/C][C]-4.69097044239692[/C][/ROW]
[ROW][C]101[/C][C]355[/C][C]350.379261923537[/C][C]-5.73728881319014[/C][C]365.358026889653[/C][C]-4.62073807646283[/C][/ROW]
[ROW][C]102[/C][C]422[/C][C]443.438047010396[/C][C]32.3366341296942[/C][C]368.22531885991[/C][C]21.4380470103961[/C][/ROW]
[ROW][C]103[/C][C]465[/C][C]488.663507632821[/C][C]70.243881537013[/C][C]371.092610830166[/C][C]23.6635076328208[/C][/ROW]
[ROW][C]104[/C][C]467[/C][C]493.748854466478[/C][C]68.0494327275684[/C][C]372.201712805953[/C][C]26.7488544664784[/C][/ROW]
[ROW][C]105[/C][C]404[/C][C]417.250859180878[/C][C]17.4383260373816[/C][C]373.31081478174[/C][C]13.2508591808784[/C][/ROW]
[ROW][C]106[/C][C]347[/C][C]341.994502619741[/C][C]-21.0634315333585[/C][C]373.068928913618[/C][C]-5.0054973802595[/C][/ROW]
[ROW][C]107[/C][C]305[/C][C]294.654807468157[/C][C]-57.4818505136532[/C][C]372.827043045496[/C][C]-10.3451925318428[/C][/ROW]
[ROW][C]108[/C][C]336[/C][C]330.574168419744[/C][C]-31.7405155016499[/C][C]373.166347081905[/C][C]-5.42583158025559[/C][/ROW]
[ROW][C]109[/C][C]340[/C][C]331.992067221459[/C][C]-25.4977183397736[/C][C]373.505651118315[/C][C]-8.00793277854137[/C][/ROW]
[ROW][C]110[/C][C]318[/C][C]295.917234796298[/C][C]-35.2209348015702[/C][C]375.303700005273[/C][C]-22.0827652037024[/C][/ROW]
[ROW][C]111[/C][C]362[/C][C]349.925729119545[/C][C]-3.02747801177545[/C][C]377.10174889223[/C][C]-12.0742708804546[/C][/ROW]
[ROW][C]112[/C][C]348[/C][C]325.122465855012[/C][C]-8.29905418525078[/C][C]379.176588330239[/C][C]-22.877534144988[/C][/ROW]
[ROW][C]113[/C][C]363[/C][C]350.485861044943[/C][C]-5.73728881319014[/C][C]381.251427768248[/C][C]-12.5141389550575[/C][/ROW]
[ROW][C]114[/C][C]435[/C][C]454.789951910881[/C][C]32.3366341296942[/C][C]382.873413959425[/C][C]19.7899519108811[/C][/ROW]
[ROW][C]115[/C][C]491[/C][C]527.260718312386[/C][C]70.243881537013[/C][C]384.495400150602[/C][C]36.2607183123855[/C][/ROW]
[ROW][C]116[/C][C]505[/C][C]555.537665590611[/C][C]68.0494327275684[/C][C]386.41290168182[/C][C]50.5376655906112[/C][/ROW]
[ROW][C]117[/C][C]404[/C][C]402.231270749579[/C][C]17.4383260373816[/C][C]388.330403213039[/C][C]-1.76872925042085[/C][/ROW]
[ROW][C]118[/C][C]359[/C][C]348.388866476376[/C][C]-21.0634315333585[/C][C]390.674565056982[/C][C]-10.6111335236239[/C][/ROW]
[ROW][C]119[/C][C]310[/C][C]284.463123612728[/C][C]-57.4818505136532[/C][C]393.018726900926[/C][C]-25.5368763872724[/C][/ROW]
[ROW][C]120[/C][C]337[/C][C]309.398913673082[/C][C]-31.7405155016499[/C][C]396.341601828568[/C][C]-27.6010863269179[/C][/ROW]
[ROW][C]121[/C][C]360[/C][C]345.833241583564[/C][C]-25.4977183397736[/C][C]399.66447675621[/C][C]-14.1667584164365[/C][/ROW]
[ROW][C]122[/C][C]342[/C][C]314.317448303322[/C][C]-35.2209348015702[/C][C]404.903486498249[/C][C]-27.6825516966784[/C][/ROW]
[ROW][C]123[/C][C]406[/C][C]404.884981771488[/C][C]-3.02747801177545[/C][C]410.142496240287[/C][C]-1.11501822851153[/C][/ROW]
[ROW][C]124[/C][C]396[/C][C]383.954091264659[/C][C]-8.29905418525078[/C][C]416.344962920592[/C][C]-12.0459087353409[/C][/ROW]
[ROW][C]125[/C][C]420[/C][C]423.189859212294[/C][C]-5.73728881319014[/C][C]422.547429600896[/C][C]3.18985921229381[/C][/ROW]
[ROW][C]126[/C][C]472[/C][C]483.873712318056[/C][C]32.3366341296942[/C][C]427.78965355225[/C][C]11.8737123180562[/C][/ROW]
[ROW][C]127[/C][C]548[/C][C]592.724240959384[/C][C]70.243881537013[/C][C]433.031877503603[/C][C]44.7242409593842[/C][/ROW]
[ROW][C]128[/C][C]559[/C][C]613.514330136433[/C][C]68.0494327275684[/C][C]436.436237135998[/C][C]54.5143301364333[/C][/ROW]
[ROW][C]129[/C][C]463[/C][C]468.721077194225[/C][C]17.4383260373816[/C][C]439.840596768394[/C][C]5.72107719422468[/C][/ROW]
[ROW][C]130[/C][C]407[/C][C]392.687931319752[/C][C]-21.0634315333585[/C][C]442.375500213607[/C][C]-14.3120686802483[/C][/ROW]
[ROW][C]131[/C][C]362[/C][C]336.571446854833[/C][C]-57.4818505136532[/C][C]444.91040365882[/C][C]-25.4285531451667[/C][/ROW]
[ROW][C]132[/C][C]405[/C][C]393.100333883737[/C][C]-31.7405155016499[/C][C]448.640181617913[/C][C]-11.8996661162627[/C][/ROW]
[ROW][C]133[/C][C]417[/C][C]407.127758762768[/C][C]-25.4977183397736[/C][C]452.369959577005[/C][C]-9.87224123723178[/C][/ROW]
[ROW][C]134[/C][C]391[/C][C]359.408804900782[/C][C]-35.2209348015702[/C][C]457.812129900788[/C][C]-31.5911950992178[/C][/ROW]
[ROW][C]135[/C][C]419[/C][C]377.773177787205[/C][C]-3.02747801177545[/C][C]463.25430022457[/C][C]-41.226822212795[/C][/ROW]
[ROW][C]136[/C][C]461[/C][C]462.688631105859[/C][C]-8.29905418525078[/C][C]467.610423079392[/C][C]1.68863110585852[/C][/ROW]
[ROW][C]137[/C][C]472[/C][C]477.770742878976[/C][C]-5.73728881319014[/C][C]471.966545934214[/C][C]5.77074287897614[/C][/ROW]
[ROW][C]138[/C][C]535[/C][C]562.055066908318[/C][C]32.3366341296942[/C][C]475.608298961987[/C][C]27.0550669083185[/C][/ROW]
[ROW][C]139[/C][C]622[/C][C]694.506066473226[/C][C]70.243881537013[/C][C]479.250051989761[/C][C]72.5060664732265[/C][/ROW]
[ROW][C]140[/C][C]606[/C][C]660.761165202602[/C][C]68.0494327275684[/C][C]483.18940206983[/C][C]54.7611652026018[/C][/ROW]
[ROW][C]141[/C][C]508[/C][C]511.432921812719[/C][C]17.4383260373816[/C][C]487.128752149899[/C][C]3.43292181271931[/C][/ROW]
[ROW][C]142[/C][C]461[/C][C]452.310411781538[/C][C]-21.0634315333585[/C][C]490.753019751821[/C][C]-8.6895882184624[/C][/ROW]
[ROW][C]143[/C][C]390[/C][C]343.10456315991[/C][C]-57.4818505136532[/C][C]494.377287353743[/C][C]-46.8954368400896[/C][/ROW]
[ROW][C]144[/C][C]432[/C][C]398.310610449872[/C][C]-31.7405155016499[/C][C]497.429905051778[/C][C]-33.6893895501282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147260&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147260&T=2

As an alternative you can also use a QR Code:  

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

Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
1112122.310369902516-25.4977183397736127.18734843725810.310369902516
2118144.571402815284-35.2209348015702126.64953198628626.5714028152841
3132140.915762476461-3.02747801177545126.1117155353158.91576247646083
4129140.100122400179-8.29905418525078126.19893178507211.1001224001792
5121121.451140778362-5.73728881319014126.2861480348290.451140778361591
6135110.93034278152532.3366341296942126.733023088781-24.0696572184753
714898.576220320253370.243881537013127.179898142734-49.4237796797467
8148100.5343508239368.0494327275684127.416216448501-47.4656491760699
9136126.90913920834917.4383260373816127.652534754269-9.09086079165081
10119130.044842451944-21.0634315333585129.01858908141511.0448424519439
11104135.097207105093-57.4818505136532130.3846434085631.0972071050931
12118135.378679881299-31.7405155016499132.36183562035117.3786798812985
13115121.158690507631-25.4977183397736134.3390278321436.15869050763089
14126152.112577072273-35.2209348015702135.10835772929726.1125770722727
15141149.149790385323-3.02747801177545135.8776876264528.14979038532326
16135142.353648187575-8.29905418525078135.9454059976767.35364818757483
17125119.72416444429-5.73728881319014136.0131243689-5.27583555570953
18149128.45404557282532.3366341296942137.209320297481-20.5459544271751
19170131.35060223692570.243881537013138.405516226062-38.6493977630751
20170130.63916127125168.0494327275684141.311406001181-39.3608387287492
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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')