Free Statistics

of Irreproducible Research!

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 computationThu, 01 Dec 2011 10:28:09 -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/Dec/01/t1322753322kbxmjygc6tyb409.htm/, Retrieved Thu, 28 Mar 2024 13:27:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=149807, Retrieved Thu, 28 Mar 2024 13:27:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact82
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
- RMPD  [Decomposition by Loess] [] [2011-11-26 21:27:22] [ee8c3a74bf3b349877806e9a50913c60]
- R PD      [Decomposition by Loess] [] [2011-12-01 15:28:09] [7dc03dd48c8acabd98b217fada4a6bc0] [Current]
Feedback Forum

Post a new message
Dataseries X:
274
291
280
258
252
251
224
225
234
233
229
208
224
226
223
205
201
202
183
188
200
206
211
201
299
244
251
241
244
252
234
246
265
277
287
275
320
338
342
322
323
343
315
334
359
362
378
345
422
430
443
431
425
432
387
396
411
421
424
410
464
486
490
459
454
446
406
412
428
429
425
396
429
439
424
379
370
353
322
322
338
348
350
312
358
378
352
312
310
292
276
269
286
292
288
255
304
299
293
275
272
264
234
231
263
264
264
245
297
317
318
315
312
310
306
313
350
354
371
357
419
425
424
399
393
378
371
364
384
377
383
352




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149807&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149807&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149807&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal13210133
Trend1912
Low-pass1312

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1321 & 0 & 133 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149807&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]1321[/C][C]0[/C][C]133[/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=149807&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149807&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
Seasonal13210133
Trend1912
Low-pass1312







Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
1274258.82596929793426.4236653861948262.750365315871-15.174030702066
2291291.07406571128331.2979190176708259.6280152710470.0740657112825716
3280276.04943471280427.4449000609741256.505665226222-3.9505652871961
4258258.2126343643514.67600235024529253.1113632854040.212634364350805
5252253.8303737530730.452564902341024249.7170613445861.83037375307325
6251259.136401466967-3.24364100523016246.1072395382648.13640146696659
7224233.533349901256-28.030767633197242.4974177319419.5333499012556
8225236.391724668407-25.1501097519631238.75838508355611.3917246684067
9234239.250102593327-6.26945502849838235.0193524351725.25010259332686
10233238.808370173524-3.26430176703221230.4559315935095.80837017352368
11229232.184825024964-0.0773357768091877225.8925107518463.18482502496363
12208218.819406060445-24.2594446230739221.44003856262910.8194060604446
13224204.58876824039226.4236653861948216.987566373413-19.4112317596078
14226207.04609218752131.2979190176708213.655988794808-18.9539078124792
15223208.23068872282227.4449000609741210.324411216204-14.769311277178
16205196.6997144485824.67600235024529208.624283201172-8.30028555141757
17201194.6232799115180.452564902341024206.924155186141-6.37672008848168
18202199.297444563401-3.24364100523016207.946196441829-2.70255543659889
19183185.06252993568-28.030767633197208.9682376975172.06252993567958
20188189.345534155014-25.1501097519631211.8045755969491.34553415501392
21200191.628541532117-6.26945502849838214.640913496381-8.3714584678826
22206197.389114317507-3.26430176703221217.875187449526-8.61088568249343
23211200.967874374139-0.0773357768091877221.10946140267-10.0321256258611
24201201.30198112077-24.2594446230739224.9574635023040.301981120769597
25299342.77086901186726.4236653861948228.80546560193843.7708690118669
26244223.03287867312231.2979190176708233.669202309207-20.9671213268776
27251236.02216092255127.4449000609741238.532939016475-14.9778390774493
28241233.3538519555434.67600235024529243.970145694212-7.64614804445725
29244238.140082725710.452564902341024249.407352371949-5.85991727428964
30252252.220130901067-3.24364100523016255.0235101041630.220130901067392
31234235.39109979682-28.030767633197260.6396678363771.39109979682013
32246250.233914402013-25.1501097519631266.916195349954.23391440201272
33265263.076732164974-6.26945502849838273.192722863524-1.92326783502557
34277277.185614884768-3.26430176703221280.0786868822640.185614884768427
35287287.112684875805-0.0773357768091877286.9646509010040.112684875805485
36275280.380009963114-24.2594446230739293.879434659965.38000996311411
37320312.78211619488926.4236653861948300.794218418916-7.21788380511066
38338336.662918819531.2979190176708308.039162162829-1.33708118049992
39342341.27099403228427.4449000609741315.284105906742-0.729005967716489
40322316.6287012182874.67600235024529322.695296431467-5.37129878171265
41323315.4409481414670.452564902341024330.106486956192-7.55905185853334
42343351.69690644127-3.24364100523016337.546734563968.69690644126996
43315313.043785461469-28.030767633197344.986982171728-1.95621453853107
44334340.251178329765-25.1501097519631352.8989314221986.2511783297648
45359363.45857435583-6.26945502849838360.8108806726694.45857435582985
46362358.237759334306-3.26430176703221369.026542432726-3.76224066569392
47378378.835131584025-0.0773357768091877377.2422041927840.835131584025419
48345329.573236907489-24.2594446230739384.686207715585-15.4267630925113
49422425.44612337541926.4236653861948392.1302112383873.44612337541861
50430430.64005490522431.2979190176708398.0620260771050.640054905223906
51443454.56125902320227.4449000609741403.99384091582411.561259023202
52431448.6058034269084.67600235024529408.71819422284717.6058034269078
53425436.1048875677890.452564902341024413.4425475298711.1048875677891
54432449.872466923501-3.24364100523016417.37117408172917.8724669235008
55387380.730966999608-28.030767633197421.299800633589-6.26903300039191
56396392.480656576576-25.1501097519631424.669453175387-3.51934342342429
57411400.230349311313-6.26945502849838428.039105717186-10.7696506886875
58421414.31078730989-3.26430176703221430.953514457142-6.68921269010985
59424414.209412579711-0.0773357768091877433.867923197098-9.79058742028917
60410407.961424857112-24.2594446230739436.298019765962-2.03857514288848
61464462.84821827897926.4236653861948438.728116334826-1.15178172102111
62486500.22198771259431.2979190176708440.48009326973514.2219877125943
63490510.32302973438227.4449000609741442.23207020464420.3230297343824
64459470.6625054641684.67600235024529442.66149218558711.6625054641681
65454464.4565209311290.452564902341024443.0909141665310.4565209311294
66446453.905909070272-3.24364100523016441.3377319349587.90590907027206
67406400.44621792981-28.030767633197439.584549703387-5.55378207018958
68412413.725304411208-25.1501097519631435.4248053407551.72530441120836
69428431.004394050375-6.26945502849838431.2650609781233.00439405037548
70429436.04677737402-3.26430176703221425.2175243930137.04677737401954
71425430.907347968907-0.0773357768091877419.1699878079025.90734796890678
72396404.263131901301-24.2594446230739411.9963127217738.26313190130094
73429426.75369697816226.4236653861948404.822637635643-2.24630302183817
74439449.54844953204731.2979190176708397.15363145028210.5484495320469
75424431.07047467410527.4449000609741389.4846252649217.07047467410462
76379371.1774228492114.67600235024529382.146574800543-7.82257715078867
77370364.7389107614940.452564902341024374.808524336165-5.26108923850643
78353340.925770581175-3.24364100523016368.317870424055-12.0742294188252
79322310.203551121252-28.030767633197361.827216511945-11.7964488787481
80322312.813110314646-25.1501097519631356.336999437317-9.18688968535366
81338331.42267266581-6.26945502849838350.846782362688-6.57732733418999
82348353.305919340063-3.26430176703221345.9583824269695.3059193400631
83350359.007353285559-0.0773357768091877341.069982491259.00735328555925
84312311.803446859452-24.2594446230739336.455997763622-0.196553140548474
85358357.7343215778126.4236653861948331.842013035995-0.26567842218958
86378397.58497457090131.2979190176708327.11710641142819.5849745709013
87352354.16290015216527.4449000609741322.3921997868612.16290015216487
88312301.8545272268494.67600235024529317.469470422905-10.1454727731508
89310307.0006940387090.452564902341024312.54674105895-2.99930596129093
90292279.718127475333-3.24364100523016307.525513529898-12.2818725246674
91276277.526481632352-28.030767633197302.5042860008451.52648163235176
92269265.426095192001-25.1501097519631297.724014559962-3.57390480799938
93286285.325711909419-6.26945502849838292.94374311908-0.674288090581342
94292298.181810459289-3.26430176703221289.0824913077436.18181045928901
95288290.856096280402-0.0773357768091877285.2212394964072.85609628040243
96255252.203693453886-24.2594446230739282.055751169188-2.79630654611429
97304302.68607177183626.4236653861948278.89026284197-1.3139282281644
98299290.63359978196431.2979190176708276.068481200366-8.36640021803646
99293285.30840038026427.4449000609741273.246699558762-7.69159961973583
100275274.1768209415924.67600235024529271.147176708163-0.823179058408414
101272274.4997812400940.452564902341024269.0476538575652.49978124009448
102264263.059390619822-3.24364100523016268.184250385408-0.940609380178046
103234228.709920719945-28.030767633197267.320846913252-5.29007928005484
104231218.995141542205-25.1501097519631268.154968209758-12.0048584577947
105263263.280365522234-6.26945502849838268.9890895062640.28036552223449
106264259.556699251239-3.26430176703221271.707602515793-4.44330074876081
107264253.651220251487-0.0773357768091877274.426115525322-10.348779748513
108245235.207207950387-24.2594446230739279.052236672687-9.79279204961341
109297283.89797679375326.4236653861948283.678357820052-13.1020232062472
110317312.44300298078231.2979190176708290.259078001547-4.55699701921753
111318311.71530175598527.4449000609741296.839798183041-6.2846982440152
112315320.3436927119294.67600235024529304.9803049378265.34369271192884
113312310.4266234050480.452564902341024313.120811692611-1.57337659495164
114310300.888610357863-3.24364100523016322.355030647367-9.11138964213688
115306308.441518031074-28.030767633197331.5892496021232.44151803107354
116313310.416618571051-25.1501097519631340.733491180912-2.58338142894894
117350356.391722268798-6.26945502849838349.8777327597016.39172226879776
118354353.521072899121-3.26430176703221357.743228867911-0.478927100878593
119371376.468610800688-0.0773357768091877365.6087249761215.46861080068823
120357366.59329110528-24.2594446230739371.6661535177949.59329110527977
121419433.85275255433826.4236653861948377.72358205946714.8527525543379
122425437.00984320109231.2979190176708381.69223778123712.0098432010923
123424434.89420643601927.4449000609741385.66089350300710.8942064360194
124399407.1264617451174.67600235024529386.1975359046378.12646174511747
125393398.8132567913910.452564902341024386.7341783062685.81325679139115
126378372.354470058853-3.24364100523016386.889170946377-5.64552994114678
127371382.986604046711-28.030767633197387.04416358648611.986604046711
128364366.199063706569-25.1501097519631386.9510460453942.19906370656878
129384387.411526524196-6.26945502849838386.8579285043033.41152652419578
130377370.756927114394-3.26430176703221386.507374652638-6.24307288560584
131383379.920514975836-0.0773357768091877386.156820800973-3.07948502416428
132352342.645037288947-24.2594446230739385.614407334126-9.35496271105256

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 274 & 258.825969297934 & 26.4236653861948 & 262.750365315871 & -15.174030702066 \tabularnewline
2 & 291 & 291.074065711283 & 31.2979190176708 & 259.628015271047 & 0.0740657112825716 \tabularnewline
3 & 280 & 276.049434712804 & 27.4449000609741 & 256.505665226222 & -3.9505652871961 \tabularnewline
4 & 258 & 258.212634364351 & 4.67600235024529 & 253.111363285404 & 0.212634364350805 \tabularnewline
5 & 252 & 253.830373753073 & 0.452564902341024 & 249.717061344586 & 1.83037375307325 \tabularnewline
6 & 251 & 259.136401466967 & -3.24364100523016 & 246.107239538264 & 8.13640146696659 \tabularnewline
7 & 224 & 233.533349901256 & -28.030767633197 & 242.497417731941 & 9.5333499012556 \tabularnewline
8 & 225 & 236.391724668407 & -25.1501097519631 & 238.758385083556 & 11.3917246684067 \tabularnewline
9 & 234 & 239.250102593327 & -6.26945502849838 & 235.019352435172 & 5.25010259332686 \tabularnewline
10 & 233 & 238.808370173524 & -3.26430176703221 & 230.455931593509 & 5.80837017352368 \tabularnewline
11 & 229 & 232.184825024964 & -0.0773357768091877 & 225.892510751846 & 3.18482502496363 \tabularnewline
12 & 208 & 218.819406060445 & -24.2594446230739 & 221.440038562629 & 10.8194060604446 \tabularnewline
13 & 224 & 204.588768240392 & 26.4236653861948 & 216.987566373413 & -19.4112317596078 \tabularnewline
14 & 226 & 207.046092187521 & 31.2979190176708 & 213.655988794808 & -18.9539078124792 \tabularnewline
15 & 223 & 208.230688722822 & 27.4449000609741 & 210.324411216204 & -14.769311277178 \tabularnewline
16 & 205 & 196.699714448582 & 4.67600235024529 & 208.624283201172 & -8.30028555141757 \tabularnewline
17 & 201 & 194.623279911518 & 0.452564902341024 & 206.924155186141 & -6.37672008848168 \tabularnewline
18 & 202 & 199.297444563401 & -3.24364100523016 & 207.946196441829 & -2.70255543659889 \tabularnewline
19 & 183 & 185.06252993568 & -28.030767633197 & 208.968237697517 & 2.06252993567958 \tabularnewline
20 & 188 & 189.345534155014 & -25.1501097519631 & 211.804575596949 & 1.34553415501392 \tabularnewline
21 & 200 & 191.628541532117 & -6.26945502849838 & 214.640913496381 & -8.3714584678826 \tabularnewline
22 & 206 & 197.389114317507 & -3.26430176703221 & 217.875187449526 & -8.61088568249343 \tabularnewline
23 & 211 & 200.967874374139 & -0.0773357768091877 & 221.10946140267 & -10.0321256258611 \tabularnewline
24 & 201 & 201.30198112077 & -24.2594446230739 & 224.957463502304 & 0.301981120769597 \tabularnewline
25 & 299 & 342.770869011867 & 26.4236653861948 & 228.805465601938 & 43.7708690118669 \tabularnewline
26 & 244 & 223.032878673122 & 31.2979190176708 & 233.669202309207 & -20.9671213268776 \tabularnewline
27 & 251 & 236.022160922551 & 27.4449000609741 & 238.532939016475 & -14.9778390774493 \tabularnewline
28 & 241 & 233.353851955543 & 4.67600235024529 & 243.970145694212 & -7.64614804445725 \tabularnewline
29 & 244 & 238.14008272571 & 0.452564902341024 & 249.407352371949 & -5.85991727428964 \tabularnewline
30 & 252 & 252.220130901067 & -3.24364100523016 & 255.023510104163 & 0.220130901067392 \tabularnewline
31 & 234 & 235.39109979682 & -28.030767633197 & 260.639667836377 & 1.39109979682013 \tabularnewline
32 & 246 & 250.233914402013 & -25.1501097519631 & 266.91619534995 & 4.23391440201272 \tabularnewline
33 & 265 & 263.076732164974 & -6.26945502849838 & 273.192722863524 & -1.92326783502557 \tabularnewline
34 & 277 & 277.185614884768 & -3.26430176703221 & 280.078686882264 & 0.185614884768427 \tabularnewline
35 & 287 & 287.112684875805 & -0.0773357768091877 & 286.964650901004 & 0.112684875805485 \tabularnewline
36 & 275 & 280.380009963114 & -24.2594446230739 & 293.87943465996 & 5.38000996311411 \tabularnewline
37 & 320 & 312.782116194889 & 26.4236653861948 & 300.794218418916 & -7.21788380511066 \tabularnewline
38 & 338 & 336.6629188195 & 31.2979190176708 & 308.039162162829 & -1.33708118049992 \tabularnewline
39 & 342 & 341.270994032284 & 27.4449000609741 & 315.284105906742 & -0.729005967716489 \tabularnewline
40 & 322 & 316.628701218287 & 4.67600235024529 & 322.695296431467 & -5.37129878171265 \tabularnewline
41 & 323 & 315.440948141467 & 0.452564902341024 & 330.106486956192 & -7.55905185853334 \tabularnewline
42 & 343 & 351.69690644127 & -3.24364100523016 & 337.54673456396 & 8.69690644126996 \tabularnewline
43 & 315 & 313.043785461469 & -28.030767633197 & 344.986982171728 & -1.95621453853107 \tabularnewline
44 & 334 & 340.251178329765 & -25.1501097519631 & 352.898931422198 & 6.2511783297648 \tabularnewline
45 & 359 & 363.45857435583 & -6.26945502849838 & 360.810880672669 & 4.45857435582985 \tabularnewline
46 & 362 & 358.237759334306 & -3.26430176703221 & 369.026542432726 & -3.76224066569392 \tabularnewline
47 & 378 & 378.835131584025 & -0.0773357768091877 & 377.242204192784 & 0.835131584025419 \tabularnewline
48 & 345 & 329.573236907489 & -24.2594446230739 & 384.686207715585 & -15.4267630925113 \tabularnewline
49 & 422 & 425.446123375419 & 26.4236653861948 & 392.130211238387 & 3.44612337541861 \tabularnewline
50 & 430 & 430.640054905224 & 31.2979190176708 & 398.062026077105 & 0.640054905223906 \tabularnewline
51 & 443 & 454.561259023202 & 27.4449000609741 & 403.993840915824 & 11.561259023202 \tabularnewline
52 & 431 & 448.605803426908 & 4.67600235024529 & 408.718194222847 & 17.6058034269078 \tabularnewline
53 & 425 & 436.104887567789 & 0.452564902341024 & 413.44254752987 & 11.1048875677891 \tabularnewline
54 & 432 & 449.872466923501 & -3.24364100523016 & 417.371174081729 & 17.8724669235008 \tabularnewline
55 & 387 & 380.730966999608 & -28.030767633197 & 421.299800633589 & -6.26903300039191 \tabularnewline
56 & 396 & 392.480656576576 & -25.1501097519631 & 424.669453175387 & -3.51934342342429 \tabularnewline
57 & 411 & 400.230349311313 & -6.26945502849838 & 428.039105717186 & -10.7696506886875 \tabularnewline
58 & 421 & 414.31078730989 & -3.26430176703221 & 430.953514457142 & -6.68921269010985 \tabularnewline
59 & 424 & 414.209412579711 & -0.0773357768091877 & 433.867923197098 & -9.79058742028917 \tabularnewline
60 & 410 & 407.961424857112 & -24.2594446230739 & 436.298019765962 & -2.03857514288848 \tabularnewline
61 & 464 & 462.848218278979 & 26.4236653861948 & 438.728116334826 & -1.15178172102111 \tabularnewline
62 & 486 & 500.221987712594 & 31.2979190176708 & 440.480093269735 & 14.2219877125943 \tabularnewline
63 & 490 & 510.323029734382 & 27.4449000609741 & 442.232070204644 & 20.3230297343824 \tabularnewline
64 & 459 & 470.662505464168 & 4.67600235024529 & 442.661492185587 & 11.6625054641681 \tabularnewline
65 & 454 & 464.456520931129 & 0.452564902341024 & 443.09091416653 & 10.4565209311294 \tabularnewline
66 & 446 & 453.905909070272 & -3.24364100523016 & 441.337731934958 & 7.90590907027206 \tabularnewline
67 & 406 & 400.44621792981 & -28.030767633197 & 439.584549703387 & -5.55378207018958 \tabularnewline
68 & 412 & 413.725304411208 & -25.1501097519631 & 435.424805340755 & 1.72530441120836 \tabularnewline
69 & 428 & 431.004394050375 & -6.26945502849838 & 431.265060978123 & 3.00439405037548 \tabularnewline
70 & 429 & 436.04677737402 & -3.26430176703221 & 425.217524393013 & 7.04677737401954 \tabularnewline
71 & 425 & 430.907347968907 & -0.0773357768091877 & 419.169987807902 & 5.90734796890678 \tabularnewline
72 & 396 & 404.263131901301 & -24.2594446230739 & 411.996312721773 & 8.26313190130094 \tabularnewline
73 & 429 & 426.753696978162 & 26.4236653861948 & 404.822637635643 & -2.24630302183817 \tabularnewline
74 & 439 & 449.548449532047 & 31.2979190176708 & 397.153631450282 & 10.5484495320469 \tabularnewline
75 & 424 & 431.070474674105 & 27.4449000609741 & 389.484625264921 & 7.07047467410462 \tabularnewline
76 & 379 & 371.177422849211 & 4.67600235024529 & 382.146574800543 & -7.82257715078867 \tabularnewline
77 & 370 & 364.738910761494 & 0.452564902341024 & 374.808524336165 & -5.26108923850643 \tabularnewline
78 & 353 & 340.925770581175 & -3.24364100523016 & 368.317870424055 & -12.0742294188252 \tabularnewline
79 & 322 & 310.203551121252 & -28.030767633197 & 361.827216511945 & -11.7964488787481 \tabularnewline
80 & 322 & 312.813110314646 & -25.1501097519631 & 356.336999437317 & -9.18688968535366 \tabularnewline
81 & 338 & 331.42267266581 & -6.26945502849838 & 350.846782362688 & -6.57732733418999 \tabularnewline
82 & 348 & 353.305919340063 & -3.26430176703221 & 345.958382426969 & 5.3059193400631 \tabularnewline
83 & 350 & 359.007353285559 & -0.0773357768091877 & 341.06998249125 & 9.00735328555925 \tabularnewline
84 & 312 & 311.803446859452 & -24.2594446230739 & 336.455997763622 & -0.196553140548474 \tabularnewline
85 & 358 & 357.73432157781 & 26.4236653861948 & 331.842013035995 & -0.26567842218958 \tabularnewline
86 & 378 & 397.584974570901 & 31.2979190176708 & 327.117106411428 & 19.5849745709013 \tabularnewline
87 & 352 & 354.162900152165 & 27.4449000609741 & 322.392199786861 & 2.16290015216487 \tabularnewline
88 & 312 & 301.854527226849 & 4.67600235024529 & 317.469470422905 & -10.1454727731508 \tabularnewline
89 & 310 & 307.000694038709 & 0.452564902341024 & 312.54674105895 & -2.99930596129093 \tabularnewline
90 & 292 & 279.718127475333 & -3.24364100523016 & 307.525513529898 & -12.2818725246674 \tabularnewline
91 & 276 & 277.526481632352 & -28.030767633197 & 302.504286000845 & 1.52648163235176 \tabularnewline
92 & 269 & 265.426095192001 & -25.1501097519631 & 297.724014559962 & -3.57390480799938 \tabularnewline
93 & 286 & 285.325711909419 & -6.26945502849838 & 292.94374311908 & -0.674288090581342 \tabularnewline
94 & 292 & 298.181810459289 & -3.26430176703221 & 289.082491307743 & 6.18181045928901 \tabularnewline
95 & 288 & 290.856096280402 & -0.0773357768091877 & 285.221239496407 & 2.85609628040243 \tabularnewline
96 & 255 & 252.203693453886 & -24.2594446230739 & 282.055751169188 & -2.79630654611429 \tabularnewline
97 & 304 & 302.686071771836 & 26.4236653861948 & 278.89026284197 & -1.3139282281644 \tabularnewline
98 & 299 & 290.633599781964 & 31.2979190176708 & 276.068481200366 & -8.36640021803646 \tabularnewline
99 & 293 & 285.308400380264 & 27.4449000609741 & 273.246699558762 & -7.69159961973583 \tabularnewline
100 & 275 & 274.176820941592 & 4.67600235024529 & 271.147176708163 & -0.823179058408414 \tabularnewline
101 & 272 & 274.499781240094 & 0.452564902341024 & 269.047653857565 & 2.49978124009448 \tabularnewline
102 & 264 & 263.059390619822 & -3.24364100523016 & 268.184250385408 & -0.940609380178046 \tabularnewline
103 & 234 & 228.709920719945 & -28.030767633197 & 267.320846913252 & -5.29007928005484 \tabularnewline
104 & 231 & 218.995141542205 & -25.1501097519631 & 268.154968209758 & -12.0048584577947 \tabularnewline
105 & 263 & 263.280365522234 & -6.26945502849838 & 268.989089506264 & 0.28036552223449 \tabularnewline
106 & 264 & 259.556699251239 & -3.26430176703221 & 271.707602515793 & -4.44330074876081 \tabularnewline
107 & 264 & 253.651220251487 & -0.0773357768091877 & 274.426115525322 & -10.348779748513 \tabularnewline
108 & 245 & 235.207207950387 & -24.2594446230739 & 279.052236672687 & -9.79279204961341 \tabularnewline
109 & 297 & 283.897976793753 & 26.4236653861948 & 283.678357820052 & -13.1020232062472 \tabularnewline
110 & 317 & 312.443002980782 & 31.2979190176708 & 290.259078001547 & -4.55699701921753 \tabularnewline
111 & 318 & 311.715301755985 & 27.4449000609741 & 296.839798183041 & -6.2846982440152 \tabularnewline
112 & 315 & 320.343692711929 & 4.67600235024529 & 304.980304937826 & 5.34369271192884 \tabularnewline
113 & 312 & 310.426623405048 & 0.452564902341024 & 313.120811692611 & -1.57337659495164 \tabularnewline
114 & 310 & 300.888610357863 & -3.24364100523016 & 322.355030647367 & -9.11138964213688 \tabularnewline
115 & 306 & 308.441518031074 & -28.030767633197 & 331.589249602123 & 2.44151803107354 \tabularnewline
116 & 313 & 310.416618571051 & -25.1501097519631 & 340.733491180912 & -2.58338142894894 \tabularnewline
117 & 350 & 356.391722268798 & -6.26945502849838 & 349.877732759701 & 6.39172226879776 \tabularnewline
118 & 354 & 353.521072899121 & -3.26430176703221 & 357.743228867911 & -0.478927100878593 \tabularnewline
119 & 371 & 376.468610800688 & -0.0773357768091877 & 365.608724976121 & 5.46861080068823 \tabularnewline
120 & 357 & 366.59329110528 & -24.2594446230739 & 371.666153517794 & 9.59329110527977 \tabularnewline
121 & 419 & 433.852752554338 & 26.4236653861948 & 377.723582059467 & 14.8527525543379 \tabularnewline
122 & 425 & 437.009843201092 & 31.2979190176708 & 381.692237781237 & 12.0098432010923 \tabularnewline
123 & 424 & 434.894206436019 & 27.4449000609741 & 385.660893503007 & 10.8942064360194 \tabularnewline
124 & 399 & 407.126461745117 & 4.67600235024529 & 386.197535904637 & 8.12646174511747 \tabularnewline
125 & 393 & 398.813256791391 & 0.452564902341024 & 386.734178306268 & 5.81325679139115 \tabularnewline
126 & 378 & 372.354470058853 & -3.24364100523016 & 386.889170946377 & -5.64552994114678 \tabularnewline
127 & 371 & 382.986604046711 & -28.030767633197 & 387.044163586486 & 11.986604046711 \tabularnewline
128 & 364 & 366.199063706569 & -25.1501097519631 & 386.951046045394 & 2.19906370656878 \tabularnewline
129 & 384 & 387.411526524196 & -6.26945502849838 & 386.857928504303 & 3.41152652419578 \tabularnewline
130 & 377 & 370.756927114394 & -3.26430176703221 & 386.507374652638 & -6.24307288560584 \tabularnewline
131 & 383 & 379.920514975836 & -0.0773357768091877 & 386.156820800973 & -3.07948502416428 \tabularnewline
132 & 352 & 342.645037288947 & -24.2594446230739 & 385.614407334126 & -9.35496271105256 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=149807&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]274[/C][C]258.825969297934[/C][C]26.4236653861948[/C][C]262.750365315871[/C][C]-15.174030702066[/C][/ROW]
[ROW][C]2[/C][C]291[/C][C]291.074065711283[/C][C]31.2979190176708[/C][C]259.628015271047[/C][C]0.0740657112825716[/C][/ROW]
[ROW][C]3[/C][C]280[/C][C]276.049434712804[/C][C]27.4449000609741[/C][C]256.505665226222[/C][C]-3.9505652871961[/C][/ROW]
[ROW][C]4[/C][C]258[/C][C]258.212634364351[/C][C]4.67600235024529[/C][C]253.111363285404[/C][C]0.212634364350805[/C][/ROW]
[ROW][C]5[/C][C]252[/C][C]253.830373753073[/C][C]0.452564902341024[/C][C]249.717061344586[/C][C]1.83037375307325[/C][/ROW]
[ROW][C]6[/C][C]251[/C][C]259.136401466967[/C][C]-3.24364100523016[/C][C]246.107239538264[/C][C]8.13640146696659[/C][/ROW]
[ROW][C]7[/C][C]224[/C][C]233.533349901256[/C][C]-28.030767633197[/C][C]242.497417731941[/C][C]9.5333499012556[/C][/ROW]
[ROW][C]8[/C][C]225[/C][C]236.391724668407[/C][C]-25.1501097519631[/C][C]238.758385083556[/C][C]11.3917246684067[/C][/ROW]
[ROW][C]9[/C][C]234[/C][C]239.250102593327[/C][C]-6.26945502849838[/C][C]235.019352435172[/C][C]5.25010259332686[/C][/ROW]
[ROW][C]10[/C][C]233[/C][C]238.808370173524[/C][C]-3.26430176703221[/C][C]230.455931593509[/C][C]5.80837017352368[/C][/ROW]
[ROW][C]11[/C][C]229[/C][C]232.184825024964[/C][C]-0.0773357768091877[/C][C]225.892510751846[/C][C]3.18482502496363[/C][/ROW]
[ROW][C]12[/C][C]208[/C][C]218.819406060445[/C][C]-24.2594446230739[/C][C]221.440038562629[/C][C]10.8194060604446[/C][/ROW]
[ROW][C]13[/C][C]224[/C][C]204.588768240392[/C][C]26.4236653861948[/C][C]216.987566373413[/C][C]-19.4112317596078[/C][/ROW]
[ROW][C]14[/C][C]226[/C][C]207.046092187521[/C][C]31.2979190176708[/C][C]213.655988794808[/C][C]-18.9539078124792[/C][/ROW]
[ROW][C]15[/C][C]223[/C][C]208.230688722822[/C][C]27.4449000609741[/C][C]210.324411216204[/C][C]-14.769311277178[/C][/ROW]
[ROW][C]16[/C][C]205[/C][C]196.699714448582[/C][C]4.67600235024529[/C][C]208.624283201172[/C][C]-8.30028555141757[/C][/ROW]
[ROW][C]17[/C][C]201[/C][C]194.623279911518[/C][C]0.452564902341024[/C][C]206.924155186141[/C][C]-6.37672008848168[/C][/ROW]
[ROW][C]18[/C][C]202[/C][C]199.297444563401[/C][C]-3.24364100523016[/C][C]207.946196441829[/C][C]-2.70255543659889[/C][/ROW]
[ROW][C]19[/C][C]183[/C][C]185.06252993568[/C][C]-28.030767633197[/C][C]208.968237697517[/C][C]2.06252993567958[/C][/ROW]
[ROW][C]20[/C][C]188[/C][C]189.345534155014[/C][C]-25.1501097519631[/C][C]211.804575596949[/C][C]1.34553415501392[/C][/ROW]
[ROW][C]21[/C][C]200[/C][C]191.628541532117[/C][C]-6.26945502849838[/C][C]214.640913496381[/C][C]-8.3714584678826[/C][/ROW]
[ROW][C]22[/C][C]206[/C][C]197.389114317507[/C][C]-3.26430176703221[/C][C]217.875187449526[/C][C]-8.61088568249343[/C][/ROW]
[ROW][C]23[/C][C]211[/C][C]200.967874374139[/C][C]-0.0773357768091877[/C][C]221.10946140267[/C][C]-10.0321256258611[/C][/ROW]
[ROW][C]24[/C][C]201[/C][C]201.30198112077[/C][C]-24.2594446230739[/C][C]224.957463502304[/C][C]0.301981120769597[/C][/ROW]
[ROW][C]25[/C][C]299[/C][C]342.770869011867[/C][C]26.4236653861948[/C][C]228.805465601938[/C][C]43.7708690118669[/C][/ROW]
[ROW][C]26[/C][C]244[/C][C]223.032878673122[/C][C]31.2979190176708[/C][C]233.669202309207[/C][C]-20.9671213268776[/C][/ROW]
[ROW][C]27[/C][C]251[/C][C]236.022160922551[/C][C]27.4449000609741[/C][C]238.532939016475[/C][C]-14.9778390774493[/C][/ROW]
[ROW][C]28[/C][C]241[/C][C]233.353851955543[/C][C]4.67600235024529[/C][C]243.970145694212[/C][C]-7.64614804445725[/C][/ROW]
[ROW][C]29[/C][C]244[/C][C]238.14008272571[/C][C]0.452564902341024[/C][C]249.407352371949[/C][C]-5.85991727428964[/C][/ROW]
[ROW][C]30[/C][C]252[/C][C]252.220130901067[/C][C]-3.24364100523016[/C][C]255.023510104163[/C][C]0.220130901067392[/C][/ROW]
[ROW][C]31[/C][C]234[/C][C]235.39109979682[/C][C]-28.030767633197[/C][C]260.639667836377[/C][C]1.39109979682013[/C][/ROW]
[ROW][C]32[/C][C]246[/C][C]250.233914402013[/C][C]-25.1501097519631[/C][C]266.91619534995[/C][C]4.23391440201272[/C][/ROW]
[ROW][C]33[/C][C]265[/C][C]263.076732164974[/C][C]-6.26945502849838[/C][C]273.192722863524[/C][C]-1.92326783502557[/C][/ROW]
[ROW][C]34[/C][C]277[/C][C]277.185614884768[/C][C]-3.26430176703221[/C][C]280.078686882264[/C][C]0.185614884768427[/C][/ROW]
[ROW][C]35[/C][C]287[/C][C]287.112684875805[/C][C]-0.0773357768091877[/C][C]286.964650901004[/C][C]0.112684875805485[/C][/ROW]
[ROW][C]36[/C][C]275[/C][C]280.380009963114[/C][C]-24.2594446230739[/C][C]293.87943465996[/C][C]5.38000996311411[/C][/ROW]
[ROW][C]37[/C][C]320[/C][C]312.782116194889[/C][C]26.4236653861948[/C][C]300.794218418916[/C][C]-7.21788380511066[/C][/ROW]
[ROW][C]38[/C][C]338[/C][C]336.6629188195[/C][C]31.2979190176708[/C][C]308.039162162829[/C][C]-1.33708118049992[/C][/ROW]
[ROW][C]39[/C][C]342[/C][C]341.270994032284[/C][C]27.4449000609741[/C][C]315.284105906742[/C][C]-0.729005967716489[/C][/ROW]
[ROW][C]40[/C][C]322[/C][C]316.628701218287[/C][C]4.67600235024529[/C][C]322.695296431467[/C][C]-5.37129878171265[/C][/ROW]
[ROW][C]41[/C][C]323[/C][C]315.440948141467[/C][C]0.452564902341024[/C][C]330.106486956192[/C][C]-7.55905185853334[/C][/ROW]
[ROW][C]42[/C][C]343[/C][C]351.69690644127[/C][C]-3.24364100523016[/C][C]337.54673456396[/C][C]8.69690644126996[/C][/ROW]
[ROW][C]43[/C][C]315[/C][C]313.043785461469[/C][C]-28.030767633197[/C][C]344.986982171728[/C][C]-1.95621453853107[/C][/ROW]
[ROW][C]44[/C][C]334[/C][C]340.251178329765[/C][C]-25.1501097519631[/C][C]352.898931422198[/C][C]6.2511783297648[/C][/ROW]
[ROW][C]45[/C][C]359[/C][C]363.45857435583[/C][C]-6.26945502849838[/C][C]360.810880672669[/C][C]4.45857435582985[/C][/ROW]
[ROW][C]46[/C][C]362[/C][C]358.237759334306[/C][C]-3.26430176703221[/C][C]369.026542432726[/C][C]-3.76224066569392[/C][/ROW]
[ROW][C]47[/C][C]378[/C][C]378.835131584025[/C][C]-0.0773357768091877[/C][C]377.242204192784[/C][C]0.835131584025419[/C][/ROW]
[ROW][C]48[/C][C]345[/C][C]329.573236907489[/C][C]-24.2594446230739[/C][C]384.686207715585[/C][C]-15.4267630925113[/C][/ROW]
[ROW][C]49[/C][C]422[/C][C]425.446123375419[/C][C]26.4236653861948[/C][C]392.130211238387[/C][C]3.44612337541861[/C][/ROW]
[ROW][C]50[/C][C]430[/C][C]430.640054905224[/C][C]31.2979190176708[/C][C]398.062026077105[/C][C]0.640054905223906[/C][/ROW]
[ROW][C]51[/C][C]443[/C][C]454.561259023202[/C][C]27.4449000609741[/C][C]403.993840915824[/C][C]11.561259023202[/C][/ROW]
[ROW][C]52[/C][C]431[/C][C]448.605803426908[/C][C]4.67600235024529[/C][C]408.718194222847[/C][C]17.6058034269078[/C][/ROW]
[ROW][C]53[/C][C]425[/C][C]436.104887567789[/C][C]0.452564902341024[/C][C]413.44254752987[/C][C]11.1048875677891[/C][/ROW]
[ROW][C]54[/C][C]432[/C][C]449.872466923501[/C][C]-3.24364100523016[/C][C]417.371174081729[/C][C]17.8724669235008[/C][/ROW]
[ROW][C]55[/C][C]387[/C][C]380.730966999608[/C][C]-28.030767633197[/C][C]421.299800633589[/C][C]-6.26903300039191[/C][/ROW]
[ROW][C]56[/C][C]396[/C][C]392.480656576576[/C][C]-25.1501097519631[/C][C]424.669453175387[/C][C]-3.51934342342429[/C][/ROW]
[ROW][C]57[/C][C]411[/C][C]400.230349311313[/C][C]-6.26945502849838[/C][C]428.039105717186[/C][C]-10.7696506886875[/C][/ROW]
[ROW][C]58[/C][C]421[/C][C]414.31078730989[/C][C]-3.26430176703221[/C][C]430.953514457142[/C][C]-6.68921269010985[/C][/ROW]
[ROW][C]59[/C][C]424[/C][C]414.209412579711[/C][C]-0.0773357768091877[/C][C]433.867923197098[/C][C]-9.79058742028917[/C][/ROW]
[ROW][C]60[/C][C]410[/C][C]407.961424857112[/C][C]-24.2594446230739[/C][C]436.298019765962[/C][C]-2.03857514288848[/C][/ROW]
[ROW][C]61[/C][C]464[/C][C]462.848218278979[/C][C]26.4236653861948[/C][C]438.728116334826[/C][C]-1.15178172102111[/C][/ROW]
[ROW][C]62[/C][C]486[/C][C]500.221987712594[/C][C]31.2979190176708[/C][C]440.480093269735[/C][C]14.2219877125943[/C][/ROW]
[ROW][C]63[/C][C]490[/C][C]510.323029734382[/C][C]27.4449000609741[/C][C]442.232070204644[/C][C]20.3230297343824[/C][/ROW]
[ROW][C]64[/C][C]459[/C][C]470.662505464168[/C][C]4.67600235024529[/C][C]442.661492185587[/C][C]11.6625054641681[/C][/ROW]
[ROW][C]65[/C][C]454[/C][C]464.456520931129[/C][C]0.452564902341024[/C][C]443.09091416653[/C][C]10.4565209311294[/C][/ROW]
[ROW][C]66[/C][C]446[/C][C]453.905909070272[/C][C]-3.24364100523016[/C][C]441.337731934958[/C][C]7.90590907027206[/C][/ROW]
[ROW][C]67[/C][C]406[/C][C]400.44621792981[/C][C]-28.030767633197[/C][C]439.584549703387[/C][C]-5.55378207018958[/C][/ROW]
[ROW][C]68[/C][C]412[/C][C]413.725304411208[/C][C]-25.1501097519631[/C][C]435.424805340755[/C][C]1.72530441120836[/C][/ROW]
[ROW][C]69[/C][C]428[/C][C]431.004394050375[/C][C]-6.26945502849838[/C][C]431.265060978123[/C][C]3.00439405037548[/C][/ROW]
[ROW][C]70[/C][C]429[/C][C]436.04677737402[/C][C]-3.26430176703221[/C][C]425.217524393013[/C][C]7.04677737401954[/C][/ROW]
[ROW][C]71[/C][C]425[/C][C]430.907347968907[/C][C]-0.0773357768091877[/C][C]419.169987807902[/C][C]5.90734796890678[/C][/ROW]
[ROW][C]72[/C][C]396[/C][C]404.263131901301[/C][C]-24.2594446230739[/C][C]411.996312721773[/C][C]8.26313190130094[/C][/ROW]
[ROW][C]73[/C][C]429[/C][C]426.753696978162[/C][C]26.4236653861948[/C][C]404.822637635643[/C][C]-2.24630302183817[/C][/ROW]
[ROW][C]74[/C][C]439[/C][C]449.548449532047[/C][C]31.2979190176708[/C][C]397.153631450282[/C][C]10.5484495320469[/C][/ROW]
[ROW][C]75[/C][C]424[/C][C]431.070474674105[/C][C]27.4449000609741[/C][C]389.484625264921[/C][C]7.07047467410462[/C][/ROW]
[ROW][C]76[/C][C]379[/C][C]371.177422849211[/C][C]4.67600235024529[/C][C]382.146574800543[/C][C]-7.82257715078867[/C][/ROW]
[ROW][C]77[/C][C]370[/C][C]364.738910761494[/C][C]0.452564902341024[/C][C]374.808524336165[/C][C]-5.26108923850643[/C][/ROW]
[ROW][C]78[/C][C]353[/C][C]340.925770581175[/C][C]-3.24364100523016[/C][C]368.317870424055[/C][C]-12.0742294188252[/C][/ROW]
[ROW][C]79[/C][C]322[/C][C]310.203551121252[/C][C]-28.030767633197[/C][C]361.827216511945[/C][C]-11.7964488787481[/C][/ROW]
[ROW][C]80[/C][C]322[/C][C]312.813110314646[/C][C]-25.1501097519631[/C][C]356.336999437317[/C][C]-9.18688968535366[/C][/ROW]
[ROW][C]81[/C][C]338[/C][C]331.42267266581[/C][C]-6.26945502849838[/C][C]350.846782362688[/C][C]-6.57732733418999[/C][/ROW]
[ROW][C]82[/C][C]348[/C][C]353.305919340063[/C][C]-3.26430176703221[/C][C]345.958382426969[/C][C]5.3059193400631[/C][/ROW]
[ROW][C]83[/C][C]350[/C][C]359.007353285559[/C][C]-0.0773357768091877[/C][C]341.06998249125[/C][C]9.00735328555925[/C][/ROW]
[ROW][C]84[/C][C]312[/C][C]311.803446859452[/C][C]-24.2594446230739[/C][C]336.455997763622[/C][C]-0.196553140548474[/C][/ROW]
[ROW][C]85[/C][C]358[/C][C]357.73432157781[/C][C]26.4236653861948[/C][C]331.842013035995[/C][C]-0.26567842218958[/C][/ROW]
[ROW][C]86[/C][C]378[/C][C]397.584974570901[/C][C]31.2979190176708[/C][C]327.117106411428[/C][C]19.5849745709013[/C][/ROW]
[ROW][C]87[/C][C]352[/C][C]354.162900152165[/C][C]27.4449000609741[/C][C]322.392199786861[/C][C]2.16290015216487[/C][/ROW]
[ROW][C]88[/C][C]312[/C][C]301.854527226849[/C][C]4.67600235024529[/C][C]317.469470422905[/C][C]-10.1454727731508[/C][/ROW]
[ROW][C]89[/C][C]310[/C][C]307.000694038709[/C][C]0.452564902341024[/C][C]312.54674105895[/C][C]-2.99930596129093[/C][/ROW]
[ROW][C]90[/C][C]292[/C][C]279.718127475333[/C][C]-3.24364100523016[/C][C]307.525513529898[/C][C]-12.2818725246674[/C][/ROW]
[ROW][C]91[/C][C]276[/C][C]277.526481632352[/C][C]-28.030767633197[/C][C]302.504286000845[/C][C]1.52648163235176[/C][/ROW]
[ROW][C]92[/C][C]269[/C][C]265.426095192001[/C][C]-25.1501097519631[/C][C]297.724014559962[/C][C]-3.57390480799938[/C][/ROW]
[ROW][C]93[/C][C]286[/C][C]285.325711909419[/C][C]-6.26945502849838[/C][C]292.94374311908[/C][C]-0.674288090581342[/C][/ROW]
[ROW][C]94[/C][C]292[/C][C]298.181810459289[/C][C]-3.26430176703221[/C][C]289.082491307743[/C][C]6.18181045928901[/C][/ROW]
[ROW][C]95[/C][C]288[/C][C]290.856096280402[/C][C]-0.0773357768091877[/C][C]285.221239496407[/C][C]2.85609628040243[/C][/ROW]
[ROW][C]96[/C][C]255[/C][C]252.203693453886[/C][C]-24.2594446230739[/C][C]282.055751169188[/C][C]-2.79630654611429[/C][/ROW]
[ROW][C]97[/C][C]304[/C][C]302.686071771836[/C][C]26.4236653861948[/C][C]278.89026284197[/C][C]-1.3139282281644[/C][/ROW]
[ROW][C]98[/C][C]299[/C][C]290.633599781964[/C][C]31.2979190176708[/C][C]276.068481200366[/C][C]-8.36640021803646[/C][/ROW]
[ROW][C]99[/C][C]293[/C][C]285.308400380264[/C][C]27.4449000609741[/C][C]273.246699558762[/C][C]-7.69159961973583[/C][/ROW]
[ROW][C]100[/C][C]275[/C][C]274.176820941592[/C][C]4.67600235024529[/C][C]271.147176708163[/C][C]-0.823179058408414[/C][/ROW]
[ROW][C]101[/C][C]272[/C][C]274.499781240094[/C][C]0.452564902341024[/C][C]269.047653857565[/C][C]2.49978124009448[/C][/ROW]
[ROW][C]102[/C][C]264[/C][C]263.059390619822[/C][C]-3.24364100523016[/C][C]268.184250385408[/C][C]-0.940609380178046[/C][/ROW]
[ROW][C]103[/C][C]234[/C][C]228.709920719945[/C][C]-28.030767633197[/C][C]267.320846913252[/C][C]-5.29007928005484[/C][/ROW]
[ROW][C]104[/C][C]231[/C][C]218.995141542205[/C][C]-25.1501097519631[/C][C]268.154968209758[/C][C]-12.0048584577947[/C][/ROW]
[ROW][C]105[/C][C]263[/C][C]263.280365522234[/C][C]-6.26945502849838[/C][C]268.989089506264[/C][C]0.28036552223449[/C][/ROW]
[ROW][C]106[/C][C]264[/C][C]259.556699251239[/C][C]-3.26430176703221[/C][C]271.707602515793[/C][C]-4.44330074876081[/C][/ROW]
[ROW][C]107[/C][C]264[/C][C]253.651220251487[/C][C]-0.0773357768091877[/C][C]274.426115525322[/C][C]-10.348779748513[/C][/ROW]
[ROW][C]108[/C][C]245[/C][C]235.207207950387[/C][C]-24.2594446230739[/C][C]279.052236672687[/C][C]-9.79279204961341[/C][/ROW]
[ROW][C]109[/C][C]297[/C][C]283.897976793753[/C][C]26.4236653861948[/C][C]283.678357820052[/C][C]-13.1020232062472[/C][/ROW]
[ROW][C]110[/C][C]317[/C][C]312.443002980782[/C][C]31.2979190176708[/C][C]290.259078001547[/C][C]-4.55699701921753[/C][/ROW]
[ROW][C]111[/C][C]318[/C][C]311.715301755985[/C][C]27.4449000609741[/C][C]296.839798183041[/C][C]-6.2846982440152[/C][/ROW]
[ROW][C]112[/C][C]315[/C][C]320.343692711929[/C][C]4.67600235024529[/C][C]304.980304937826[/C][C]5.34369271192884[/C][/ROW]
[ROW][C]113[/C][C]312[/C][C]310.426623405048[/C][C]0.452564902341024[/C][C]313.120811692611[/C][C]-1.57337659495164[/C][/ROW]
[ROW][C]114[/C][C]310[/C][C]300.888610357863[/C][C]-3.24364100523016[/C][C]322.355030647367[/C][C]-9.11138964213688[/C][/ROW]
[ROW][C]115[/C][C]306[/C][C]308.441518031074[/C][C]-28.030767633197[/C][C]331.589249602123[/C][C]2.44151803107354[/C][/ROW]
[ROW][C]116[/C][C]313[/C][C]310.416618571051[/C][C]-25.1501097519631[/C][C]340.733491180912[/C][C]-2.58338142894894[/C][/ROW]
[ROW][C]117[/C][C]350[/C][C]356.391722268798[/C][C]-6.26945502849838[/C][C]349.877732759701[/C][C]6.39172226879776[/C][/ROW]
[ROW][C]118[/C][C]354[/C][C]353.521072899121[/C][C]-3.26430176703221[/C][C]357.743228867911[/C][C]-0.478927100878593[/C][/ROW]
[ROW][C]119[/C][C]371[/C][C]376.468610800688[/C][C]-0.0773357768091877[/C][C]365.608724976121[/C][C]5.46861080068823[/C][/ROW]
[ROW][C]120[/C][C]357[/C][C]366.59329110528[/C][C]-24.2594446230739[/C][C]371.666153517794[/C][C]9.59329110527977[/C][/ROW]
[ROW][C]121[/C][C]419[/C][C]433.852752554338[/C][C]26.4236653861948[/C][C]377.723582059467[/C][C]14.8527525543379[/C][/ROW]
[ROW][C]122[/C][C]425[/C][C]437.009843201092[/C][C]31.2979190176708[/C][C]381.692237781237[/C][C]12.0098432010923[/C][/ROW]
[ROW][C]123[/C][C]424[/C][C]434.894206436019[/C][C]27.4449000609741[/C][C]385.660893503007[/C][C]10.8942064360194[/C][/ROW]
[ROW][C]124[/C][C]399[/C][C]407.126461745117[/C][C]4.67600235024529[/C][C]386.197535904637[/C][C]8.12646174511747[/C][/ROW]
[ROW][C]125[/C][C]393[/C][C]398.813256791391[/C][C]0.452564902341024[/C][C]386.734178306268[/C][C]5.81325679139115[/C][/ROW]
[ROW][C]126[/C][C]378[/C][C]372.354470058853[/C][C]-3.24364100523016[/C][C]386.889170946377[/C][C]-5.64552994114678[/C][/ROW]
[ROW][C]127[/C][C]371[/C][C]382.986604046711[/C][C]-28.030767633197[/C][C]387.044163586486[/C][C]11.986604046711[/C][/ROW]
[ROW][C]128[/C][C]364[/C][C]366.199063706569[/C][C]-25.1501097519631[/C][C]386.951046045394[/C][C]2.19906370656878[/C][/ROW]
[ROW][C]129[/C][C]384[/C][C]387.411526524196[/C][C]-6.26945502849838[/C][C]386.857928504303[/C][C]3.41152652419578[/C][/ROW]
[ROW][C]130[/C][C]377[/C][C]370.756927114394[/C][C]-3.26430176703221[/C][C]386.507374652638[/C][C]-6.24307288560584[/C][/ROW]
[ROW][C]131[/C][C]383[/C][C]379.920514975836[/C][C]-0.0773357768091877[/C][C]386.156820800973[/C][C]-3.07948502416428[/C][/ROW]
[ROW][C]132[/C][C]352[/C][C]342.645037288947[/C][C]-24.2594446230739[/C][C]385.614407334126[/C][C]-9.35496271105256[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=149807&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=149807&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
1274258.82596929793426.4236653861948262.750365315871-15.174030702066
2291291.07406571128331.2979190176708259.6280152710470.0740657112825716
3280276.04943471280427.4449000609741256.505665226222-3.9505652871961
4258258.2126343643514.67600235024529253.1113632854040.212634364350805
5252253.8303737530730.452564902341024249.7170613445861.83037375307325
6251259.136401466967-3.24364100523016246.1072395382648.13640146696659
7224233.533349901256-28.030767633197242.4974177319419.5333499012556
8225236.391724668407-25.1501097519631238.75838508355611.3917246684067
9234239.250102593327-6.26945502849838235.0193524351725.25010259332686
10233238.808370173524-3.26430176703221230.4559315935095.80837017352368
11229232.184825024964-0.0773357768091877225.8925107518463.18482502496363
12208218.819406060445-24.2594446230739221.44003856262910.8194060604446
13224204.58876824039226.4236653861948216.987566373413-19.4112317596078
14226207.04609218752131.2979190176708213.655988794808-18.9539078124792
15223208.23068872282227.4449000609741210.324411216204-14.769311277178
16205196.6997144485824.67600235024529208.624283201172-8.30028555141757
17201194.6232799115180.452564902341024206.924155186141-6.37672008848168
18202199.297444563401-3.24364100523016207.946196441829-2.70255543659889
19183185.06252993568-28.030767633197208.9682376975172.06252993567958
20188189.345534155014-25.1501097519631211.8045755969491.34553415501392
21200191.628541532117-6.26945502849838214.640913496381-8.3714584678826
22206197.389114317507-3.26430176703221217.875187449526-8.61088568249343
23211200.967874374139-0.0773357768091877221.10946140267-10.0321256258611
24201201.30198112077-24.2594446230739224.9574635023040.301981120769597
25299342.77086901186726.4236653861948228.80546560193843.7708690118669
26244223.03287867312231.2979190176708233.669202309207-20.9671213268776
27251236.02216092255127.4449000609741238.532939016475-14.9778390774493
28241233.3538519555434.67600235024529243.970145694212-7.64614804445725
29244238.140082725710.452564902341024249.407352371949-5.85991727428964
30252252.220130901067-3.24364100523016255.0235101041630.220130901067392
31234235.39109979682-28.030767633197260.6396678363771.39109979682013
32246250.233914402013-25.1501097519631266.916195349954.23391440201272
33265263.076732164974-6.26945502849838273.192722863524-1.92326783502557
34277277.185614884768-3.26430176703221280.0786868822640.185614884768427
35287287.112684875805-0.0773357768091877286.9646509010040.112684875805485
36275280.380009963114-24.2594446230739293.879434659965.38000996311411
37320312.78211619488926.4236653861948300.794218418916-7.21788380511066
38338336.662918819531.2979190176708308.039162162829-1.33708118049992
39342341.27099403228427.4449000609741315.284105906742-0.729005967716489
40322316.6287012182874.67600235024529322.695296431467-5.37129878171265
41323315.4409481414670.452564902341024330.106486956192-7.55905185853334
42343351.69690644127-3.24364100523016337.546734563968.69690644126996
43315313.043785461469-28.030767633197344.986982171728-1.95621453853107
44334340.251178329765-25.1501097519631352.8989314221986.2511783297648
45359363.45857435583-6.26945502849838360.8108806726694.45857435582985
46362358.237759334306-3.26430176703221369.026542432726-3.76224066569392
47378378.835131584025-0.0773357768091877377.2422041927840.835131584025419
48345329.573236907489-24.2594446230739384.686207715585-15.4267630925113
49422425.44612337541926.4236653861948392.1302112383873.44612337541861
50430430.64005490522431.2979190176708398.0620260771050.640054905223906
51443454.56125902320227.4449000609741403.99384091582411.561259023202
52431448.6058034269084.67600235024529408.71819422284717.6058034269078
53425436.1048875677890.452564902341024413.4425475298711.1048875677891
54432449.872466923501-3.24364100523016417.37117408172917.8724669235008
55387380.730966999608-28.030767633197421.299800633589-6.26903300039191
56396392.480656576576-25.1501097519631424.669453175387-3.51934342342429
57411400.230349311313-6.26945502849838428.039105717186-10.7696506886875
58421414.31078730989-3.26430176703221430.953514457142-6.68921269010985
59424414.209412579711-0.0773357768091877433.867923197098-9.79058742028917
60410407.961424857112-24.2594446230739436.298019765962-2.03857514288848
61464462.84821827897926.4236653861948438.728116334826-1.15178172102111
62486500.22198771259431.2979190176708440.48009326973514.2219877125943
63490510.32302973438227.4449000609741442.23207020464420.3230297343824
64459470.6625054641684.67600235024529442.66149218558711.6625054641681
65454464.4565209311290.452564902341024443.0909141665310.4565209311294
66446453.905909070272-3.24364100523016441.3377319349587.90590907027206
67406400.44621792981-28.030767633197439.584549703387-5.55378207018958
68412413.725304411208-25.1501097519631435.4248053407551.72530441120836
69428431.004394050375-6.26945502849838431.2650609781233.00439405037548
70429436.04677737402-3.26430176703221425.2175243930137.04677737401954
71425430.907347968907-0.0773357768091877419.1699878079025.90734796890678
72396404.263131901301-24.2594446230739411.9963127217738.26313190130094
73429426.75369697816226.4236653861948404.822637635643-2.24630302183817
74439449.54844953204731.2979190176708397.15363145028210.5484495320469
75424431.07047467410527.4449000609741389.4846252649217.07047467410462
76379371.1774228492114.67600235024529382.146574800543-7.82257715078867
77370364.7389107614940.452564902341024374.808524336165-5.26108923850643
78353340.925770581175-3.24364100523016368.317870424055-12.0742294188252
79322310.203551121252-28.030767633197361.827216511945-11.7964488787481
80322312.813110314646-25.1501097519631356.336999437317-9.18688968535366
81338331.42267266581-6.26945502849838350.846782362688-6.57732733418999
82348353.305919340063-3.26430176703221345.9583824269695.3059193400631
83350359.007353285559-0.0773357768091877341.069982491259.00735328555925
84312311.803446859452-24.2594446230739336.455997763622-0.196553140548474
85358357.7343215778126.4236653861948331.842013035995-0.26567842218958
86378397.58497457090131.2979190176708327.11710641142819.5849745709013
87352354.16290015216527.4449000609741322.3921997868612.16290015216487
88312301.8545272268494.67600235024529317.469470422905-10.1454727731508
89310307.0006940387090.452564902341024312.54674105895-2.99930596129093
90292279.718127475333-3.24364100523016307.525513529898-12.2818725246674
91276277.526481632352-28.030767633197302.5042860008451.52648163235176
92269265.426095192001-25.1501097519631297.724014559962-3.57390480799938
93286285.325711909419-6.26945502849838292.94374311908-0.674288090581342
94292298.181810459289-3.26430176703221289.0824913077436.18181045928901
95288290.856096280402-0.0773357768091877285.2212394964072.85609628040243
96255252.203693453886-24.2594446230739282.055751169188-2.79630654611429
97304302.68607177183626.4236653861948278.89026284197-1.3139282281644
98299290.63359978196431.2979190176708276.068481200366-8.36640021803646
99293285.30840038026427.4449000609741273.246699558762-7.69159961973583
100275274.1768209415924.67600235024529271.147176708163-0.823179058408414
101272274.4997812400940.452564902341024269.0476538575652.49978124009448
102264263.059390619822-3.24364100523016268.184250385408-0.940609380178046
103234228.709920719945-28.030767633197267.320846913252-5.29007928005484
104231218.995141542205-25.1501097519631268.154968209758-12.0048584577947
105263263.280365522234-6.26945502849838268.9890895062640.28036552223449
106264259.556699251239-3.26430176703221271.707602515793-4.44330074876081
107264253.651220251487-0.0773357768091877274.426115525322-10.348779748513
108245235.207207950387-24.2594446230739279.052236672687-9.79279204961341
109297283.89797679375326.4236653861948283.678357820052-13.1020232062472
110317312.44300298078231.2979190176708290.259078001547-4.55699701921753
111318311.71530175598527.4449000609741296.839798183041-6.2846982440152
112315320.3436927119294.67600235024529304.9803049378265.34369271192884
113312310.4266234050480.452564902341024313.120811692611-1.57337659495164
114310300.888610357863-3.24364100523016322.355030647367-9.11138964213688
115306308.441518031074-28.030767633197331.5892496021232.44151803107354
116313310.416618571051-25.1501097519631340.733491180912-2.58338142894894
117350356.391722268798-6.26945502849838349.8777327597016.39172226879776
118354353.521072899121-3.26430176703221357.743228867911-0.478927100878593
119371376.468610800688-0.0773357768091877365.6087249761215.46861080068823
120357366.59329110528-24.2594446230739371.6661535177949.59329110527977
121419433.85275255433826.4236653861948377.72358205946714.8527525543379
122425437.00984320109231.2979190176708381.69223778123712.0098432010923
123424434.89420643601927.4449000609741385.66089350300710.8942064360194
124399407.1264617451174.67600235024529386.1975359046378.12646174511747
125393398.8132567913910.452564902341024386.7341783062685.81325679139115
126378372.354470058853-3.24364100523016386.889170946377-5.64552994114678
127371382.986604046711-28.030767633197387.04416358648611.986604046711
128364366.199063706569-25.1501097519631386.9510460453942.19906370656878
129384387.411526524196-6.26945502849838386.8579285043033.41152652419578
130377370.756927114394-3.26430176703221386.507374652638-6.24307288560584
131383379.920514975836-0.0773357768091877386.156820800973-3.07948502416428
132352342.645037288947-24.2594446230739385.614407334126-9.35496271105256



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')