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*The author of this computation has been verified*
R Software Module: /rwasp_decomposeloess.wasp (opens new window with default values)
Title produced by software: Decomposition by Loess
Date of computation: Thu, 25 Mar 2010 14:32:43 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk.htm/, Retrieved Thu, 25 Mar 2010 15:36:10 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
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
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132


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


Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
1112122.310369902516-25.4977183397736127.18734843725710.3103699025161
2118144.571402815284-35.2209348015702126.64953198628626.5714028152841
3132140.915762476461-3.02747801177543126.1117155353158.91576247646078
4129140.100122400179-8.29905418525078126.19893178507211.1001224001792
5121121.451140778362-5.73728881319017126.2861480348280.451140778361719
6135110.93034278152532.3366341296942126.733023088781-24.0696572184753
714898.576220320253370.243881537013127.179898142734-49.4237796797467
8148100.5343508239368.0494327275685127.416216448501-47.4656491760699
9136126.90913920834917.4383260373817127.652534754269-9.09086079165087
10119130.044842451944-21.0634315333585129.01858908141511.0448424519439
11104135.097207105093-57.4818505136532130.3846434085631.0972071050931
12118135.378679881299-31.7405155016501132.36183562035117.3786798812987
13115121.158690507631-25.4977183397736134.3390278321436.15869050763092
14126152.112577072273-35.2209348015702135.10835772929726.1125770722728
15141149.149790385323-3.02747801177543135.8776876264528.14979038532329
16135142.353648187575-8.29905418525078135.9454059976767.35364818757489
17125119.724164444291-5.73728881319017136.013124368900-5.27583555570945
18149128.45404557282532.3366341296942137.209320297481-20.5459544271750
19170131.35060223692570.243881537013138.405516226062-38.6493977630751
20170130.63916127125168.0494327275685141.311406001181-39.3608387287493
21158154.34437818631917.4383260373817144.217295776299-3.65562181368119
22133138.726366614332-21.0634315333585148.3370649190275.7263666143316
23114133.025016451899-57.4818505136532152.45683406175419.0250164518989
24140155.614859241740-31.7405155016501156.1256562599115.6148592417402
25145155.703239881708-25.4977183397736159.79447845806510.7032398817081
26150173.529500350016-35.2209348015702161.69143445155523.5295003500156
27178195.439087566732-3.02747801177543163.58839044504417.4390875667319
28163169.697380992963-8.29905418525078164.6016731922886.69738099296282
29172184.122332873658-5.73728881319017165.61495593953212.1223328736578
30178156.4349086371332.3366341296942167.228457233176-21.5650913628700
31199158.91415993616870.243881537013168.841958526819-40.0858400638321
32199158.74354400965668.0494327275685171.207023262775-40.2564559903438
33184176.98958596388717.4383260373817173.572087998732-7.01041403611322
34162168.510793822090-21.0634315333585176.5526377112696.51079382208968
35146169.948663089847-57.4818505136532179.53318742380623.9486630898471
36166181.112749390396-31.7405155016501182.62776611125415.1127493903959
37171181.775373541071-25.4977183397736185.72234479870210.7753735410714
38180207.404617284177-35.2209348015702187.81631751739327.4046172841769
39193199.117187775691-3.02747801177543189.9102902360846.11718777569118
40181179.167886761944-8.29905418525078191.131167423307-1.83211323805639
41183179.38524420266-5.73728881319017192.35204461053-3.61475579733994
42218209.59754925746432.3366341296942194.065816612842-8.40245074253599
43230193.97652984783470.243881537013195.779588615153-36.0234701521664
44242217.16918008428268.0494327275685198.781387188149-24.8308199157176
45209198.77848820147417.4383260373817201.783185761145-10.2215117985265
46191196.994743228647-21.0634315333585206.0686883047125.99474322864663
47172191.127659665374-57.4818505136532210.35419084827919.1276596653743
48194205.555637817977-31.7405155016501214.18487768367311.5556378179768
49196199.482153820706-25.4977183397736218.0155645190683.482153820706
50196207.094595379858-35.2209348015702220.12633942171211.0945953798577
51236252.790363687418-3.02747801177543222.23711432435716.7903636874181
52235255.361488098016-8.29905418525078222.93756608723520.361488098016
53229240.099270963078-5.73728881319017223.63801785011211.0992709630780
54243229.87054596364332.3366341296942223.792819906663-13.1294540363569
55264233.80849649977470.243881537013223.947621963213-30.1915035002262
56272252.00629227680068.0494327275685223.944274995632-19.9937077232004
57237232.62074593456817.4383260373817223.940928028051-4.37925406543229
58211218.468681624540-21.0634315333585224.5947499088197.46868162453964
59180192.233278724066-57.4818505136532225.24857178958712.2332787240661
60201206.719013989328-31.7405155016501227.0215015123225.71901398932818
61204204.703287104717-25.4977183397736228.7944312350570.703287104716935
62188180.667428897015-35.2209348015702230.553505904556-7.33257110298547
63235240.714897437721-3.02747801177543232.3125805740555.71489743772082
64227228.466222166896-8.29905418525078233.8328320183551.46622216689607
65234238.384205350535-5.73728881319017235.3530834626554.38420535053535
66264257.95926594350832.3366341296942237.704099926798-6.04073405649189
67302293.70100207204670.243881537013240.055116390940-8.2989979279535
68293274.70401830714568.0494327275685243.246548965287-18.2959816928552
69259254.12369242298517.4383260373817246.437981539633-4.87630757701459
70229228.959774829309-21.0634315333585250.103656704049-0.0402251706909169
71203209.712518645187-57.4818505136532253.7693318684666.71251864518734
72229231.656908610152-31.7405155016501258.0836068914982.65690861015162
73242247.099836425243-25.4977183397736262.3978819145315.09983642524259
74233234.466420806155-35.2209348015702266.7545139954151.46642080615493
75267265.916331935476-3.02747801177543271.111146076299-1.08366806452392
76269271.460644361895-8.29905418525078274.8384098233562.46064436189482
77270267.171615242778-5.73728881319017278.565673570413-2.82838475722247
78315315.57720166744432.3366341296942282.0861642028620.577201667444172
79364372.14946362767670.243881537013285.6066548353118.14946362767643
80347336.59906791886468.0494327275685289.351499353568-10.4009320811360
81312313.46533009079417.4383260373817293.0963438718251.46533009079377
82274271.987392513557-21.0634315333585297.076039019802-2.01260748644347
83237230.426116345874-57.4818505136532301.055734167779-6.57388365412612
84278282.334153061375-31.7405155016501305.4063624402754.33415306137465
85284283.740727627002-25.4977183397736309.756990712771-0.259272372997827
86277275.191453926064-35.2209348015702314.029480875506-1.80854607393582
87317318.725506973535-3.02747801177543318.3019710382401.72550697353495
88313312.591984804652-8.29905418525078321.707069380599-0.408015195348185
89318316.625121090233-5.73728881319017325.112167722957-1.37487890976729
90374388.01197714989932.3366341296942327.65138872040614.0119771498995
91413425.56550874513270.243881537013330.19060971785512.5655087451319
92405409.4674628264468.0494327275685332.4831044459924.46746282643971
93355357.7860747884917.4383260373817334.7755991741292.78607478848983
94306295.714136380013-21.0634315333585337.349295153346-10.2858636199874
95271259.55885938109-57.4818505136532339.922991132563-11.4411406189101
96306300.178745914256-31.7405155016501343.561769587394-5.82125408574382
97315308.297170297549-25.4977183397736347.200548042224-6.7028297024508
98301285.309649597637-35.2209348015702351.911285203933-15.6903504023633
99356358.405455646133-3.02747801177543356.6220223656422.40545564613296
100348343.309029557603-8.29905418525078360.990024627648-4.69097044239697
101355350.379261923537-5.73728881319017365.358026889653-4.62073807646289
102422443.43804701039632.3366341296942368.2253188599121.4380470103961
103465488.66350763282170.243881537013371.09261083016623.6635076328207
104467493.74885446647868.0494327275685372.20171280595326.7488544664784
105404417.25085918087817.4383260373817373.3108147817413.2508591808784
106347341.994502619741-21.0634315333585373.068928913618-5.00549738025944
107305294.654807468157-57.4818505136532372.827043045496-10.3451925318427
108336330.574168419745-31.7405155016501373.166347081905-5.42583158025531
109340331.992067221459-25.4977183397736373.505651118315-8.00793277854126
110318295.917234796298-35.2209348015702375.303700005273-22.0827652037024
111362349.925729119545-3.02747801177543377.10174889223-12.0742708804547
112348325.122465855012-8.29905418525078379.176588330239-22.8775341449881
113363350.485861044942-5.73728881319017381.251427768248-12.5141389550575
114435454.78995191088132.3366341296942382.87341395942519.7899519108811
115491527.26071831238670.243881537013384.49540015060136.2607183123855
116505555.53766559061168.0494327275685386.4129016818250.5376655906113
117404402.23127074957917.4383260373817388.330403213039-1.76872925042073
118359348.388866476376-21.0634315333585390.674565056982-10.6111335236239
119310284.463123612728-57.4818505136532393.018726900926-25.5368763872724
120337309.398913673082-31.7405155016501396.341601828568-27.6010863269179
121360345.833241583563-25.4977183397736399.66447675621-14.1667584164366
122342314.317448303322-35.2209348015702404.903486498249-27.6825516966784
123406404.884981771489-3.02747801177543410.142496240287-1.11501822851147
124396383.954091264659-8.29905418525078416.344962920592-12.0459087353409
125420423.189859212294-5.73728881319017422.5474296008963.1898592122937
126472483.87371231805632.3366341296942427.7896535522511.8737123180561
127548592.72424095938470.243881537013433.03187750360344.7242409593841
128559613.51433013643368.0494327275685436.43623713599854.5143301364332
129463468.72107719422517.4383260373817439.8405967683945.72107719422462
130407392.687931319752-21.0634315333585442.375500213607-14.3120686802483
131362336.571446854833-57.4818505136532444.91040365882-25.4285531451666
132405393.100333883737-31.7405155016501448.640181617913-11.8996661162626
133417407.127758762768-25.4977183397736452.369959577005-9.87224123723178
134391359.408804900782-35.2209348015702457.812129900788-31.5911950992179
135419377.773177787205-3.02747801177543463.254300224571-41.2268222127952
136461462.688631105858-8.29905418525078467.6104230793921.68863110585846
137472477.770742878976-5.73728881319017471.9665459342145.77074287897614
138535562.05506690831932.3366341296942475.60829896198727.0550669083188
139622694.50606647322770.243881537013479.2500519897672.506066473227
140606660.76116520260368.0494327275685483.18940206982954.7611652026028
141508511.43292181272117.4383260373817487.1287521498973.43292181272085
142461452.310411781539-21.0634315333585490.75301975182-8.6895882184611
143390343.104563159912-57.4818505136532494.377287353742-46.8954368400885
144432398.310610449871-31.7405155016501497.429905051779-33.6893895501286
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/1yo7n1269527561.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/1yo7n1269527561.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/2yo7n1269527561.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/2yo7n1269527561.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/3rf7q1269527561.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/3rf7q1269527561.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/4rf7q1269527561.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Mar/25/t1269527764lpk7kydeoqkt0dk/4rf7q1269527561.ps (open in new window)


 
Parameters (Session):
 
Parameters (R input):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; 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')
 




Copyright

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa


Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.


Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

  • personalize online software applications according to your needs
  • enforce strict security rules with respect to the data that you upload (e.g. statistical data)
  • manage user sessions of online applications
  • alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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