WS9

*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: Sun, 06 Dec 2009 08:07:47 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj.htm/, Retrieved Sun, 06 Dec 2009 16:08:58 +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/2009/Dec/06/t12601121324jopem2csrditwj.htm/}, year = {2009}, } @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 = {2009}, 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 «

10414,9 12476,8 12384,6 12266,7 12919,9 11497,3 12142 13919,4 12656,8 12034,1 13199,7 10881,3 11301,2 13643,9 12517 13981,1 14275,7 13435 13565,7 16216,3 12970 14079,9 14235 12213,4 12581 14130,4 14210,8 14378,5 13142,8 13714,7 13621,9 15379,8 13306,3 14391,2 14909,9 14025,4 12951,2 14344,3 16093,4 15413,6 14705,7 15972,8 16241,4 16626,4 17136,2 15622,9 18003,9 16136,1 14423,7 16789,4 16782,2 14133,8 12607 12004,5 12175,4 13268 12299,3 11800,6 13873,3 12269,6

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Seasonal Decomposition by Loess - Parameters Component Window Degree Jump Seasonal 601 0 61 Trend 19 1 2 Low-pass 13 1 2 Seasonal Decomposition by Loess - Time Series Components t Observed Fitted Seasonal Trend Remainder 1 10414.9 10247.0018017559 -1457.24905752876 12040.0472557728 -167.898198244071 2 12476.8 12386.4227946853 478.056301812734 12089.120903502 -90.3772053147313 3 12384.6 12039.5633951958 591.442053573007 12138.1945512312 -345.036604804163 4 12266.7 12135.3454047883 213.783647602437 12184.2709476093 -131.354595211722 5 12919.9 13914.9884325209 -305.535776508278 12230.3473439874 995.088432520864 6 11497.3 11240.9134019336 -524.45215099644 12278.1387490629 -256.386598066412 7 12142 12271.6592912118 -313.589445350125 12325.9301541383 129.659291211834 8 13919.4 14231.8996657059 1227.53077908099 12379.3695552131 312.499665705869 9 12656.8 13053.1004626671 -172.309418955097 12432.808956288 396.300462667103 10 12034.1 11781.9792980923 -219.426692251774 12505.6473941595 -252.120701907679 11 13199.7 12740.8590369671 1080.05513100199 12578.4858320309 -458.840963032901 12 10881.3 9655.46866995175 -598.304878214088 12705.4362082623 -1225.83133004825 13 11301.2 11227.262473035 -1457.24905752876 12832.3865844938 -73.937526964999 14 13643.9 13822.3672503528 478.056301812734 12987.3764478345 178.467250352805 15 12517 11300.1916352518 591.442053573007 13142.3663111752 -1216.80836474816 16 13981.1 14462.8109752447 213.783647602437 13285.6053771528 481.710975244730 17 14275.7 15428.0913333778 -305.535776508278 13428.8444431305 1152.39133337777 18 13435 13855.5220312167 -524.45215099644 13538.9301197797 420.522031216733 19 13565.7 13795.9736489212 -313.589445350125 13649.0157964289 230.273648921226 20 16216.3 17499.0728856334 1227.53077908099 13705.9963352856 1282.77288563344 21 12970 12349.3325448129 -172.309418955097 13762.9768741422 -620.667455187146 22 14079.9 14608.4331941257 -219.426692251774 13770.7934981261 528.533194125668 23 14235 13611.3347468880 1080.05513100199 13778.6101221100 -623.665253111958 24 12213.4 11264.4912810460 -598.304878214088 13760.6135971681 -948.908718954019 25 12581 12876.6319853025 -1457.24905752876 13742.6170722262 295.631985302522 26 14130.4 14035.8471584663 478.056301812734 13746.8965397210 -94.5528415336958 27 14210.8 14078.9819392113 591.442053573007 13751.1760072157 -131.818060788688 28 14378.5 14748.2094465924 213.783647602437 13795.0069058052 369.709446592407 29 13142.8 12752.2979721136 -305.535776508278 13838.8378043946 -390.502027886350 30 13714.7 14049.0674644436 -524.45215099644 13904.7846865528 334.367464443591 31 13621.9 13586.6578766391 -313.589445350125 13970.7315687111 -35.2421233609475 32 15379.8 15487.3809215932 1227.53077908099 14044.6882993258 107.580921593219 33 13306.3 12666.2643890146 -172.309418955097 14118.6450299405 -640.035610985416 34 14391.2 14775.0222943416 -219.426692251774 14226.8043979102 383.822294341591 35 14909.9 14404.7811031182 1080.05513100199 14334.9637658799 -505.118896881842 36 14025.4 14152.093997748 -598.304878214088 14497.0108804661 126.693997747991 37 12951.2 12700.5910624764 -1457.24905752876 14659.0579950523 -250.608937523575 38 14344.3 13351.9661537261 478.056301812734 14858.5775444612 -992.33384627391 39 16093.4 16537.2608525570 591.442053573007 15058.09709387 443.860852556985 40 15413.6 15341.9799275424 213.783647602437 15271.4364248552 -71.6200724576083 41 14705.7 14232.1600206679 -305.535776508278 15484.7757558403 -473.539979332054 42 15972.8 16793.6052274390 -524.45215099644 15676.4469235575 820.80522743897 43 16241.4 16928.2713540755 -313.589445350125 15868.1180912746 686.871354075522 44 16626.4 16037.9996958070 1227.53077908099 15987.2695251120 -588.400304193035 45 17136.2 18338.2884600056 -172.309418955097 16106.4209589495 1202.08846000560 46 15622.9 15417.0191949916 -219.426692251774 16048.2074972602 -205.880805008377 47 18003.9 18937.7508334272 1080.05513100199 15989.9940355708 933.850833427208 48 16136.1 17131.2523028599 -598.304878214088 15739.2525753542 995.15230285989 49 14423.7 14816.1379423912 -1457.24905752876 15488.5111151376 392.437942391176 50 16789.4 17977.983509633 478.056301812734 15122.7601885543 1188.58350963300 51 16782.2 18215.9486844560 591.442053573007 14757.0092619710 1433.74868445604 52 14133.8 13662.9854852249 213.783647602437 14390.8308671727 -470.814514775118 53 12607 11494.8833041339 -305.535776508278 14024.6524723744 -1112.11669586613 54 12004.5 10858.3634959954 -524.45215099644 13675.0886550011 -1146.13650400461 55 12175.4 11338.8646077224 -313.589445350125 13325.5248376277 -836.535392277568 56 13268 12337.3502159282 1227.53077908099 12971.1190049908 -930.649784071773 57 12299.3 12154.1962466012 -172.309418955097 12616.7131723539 -145.103753398784 58 11800.6 11549.1626217067 -219.426692251774 12271.4640705451 -251.437378293283 59 13873.3 14740.3299002618 1080.05513100199 11926.2149687362 867.029900261778 60 12269.6 13541.8707181037 -598.304878214088 11595.6341601104 1272.27071810368

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/1fcfo1260112065.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/1fcfo1260112065.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/2onzp1260112065.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/2onzp1260112065.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/3jgil1260112065.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/3jgil1260112065.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/4x9rt1260112065.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/06/t12601121324jopem2csrditwj/4x9rt1260112065.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

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

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.

FreeStatistics.org is powered by