Blog & Share Statistical Computations at FreeStatistics.org

Home » date » 2009 » Dec » 04 »

*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: Fri, 04 Dec 2009 10:38:14 -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/04/t1259948334ocezgodyrdio9th.htm/, Retrieved Fri, 04 Dec 2009 18:39:00 +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/04/t1259948334ocezgodyrdio9th.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 «

92.9 107.7 103.5 91.1 79.8 71.9 82.9 90.1 100.7 90.7 108.8 44.1 93.6 107.4 96.5 93.6 76.5 76.7 84 103.3 88.5 99 105.9 44.7 94 107.1 104.8 102.5 77.7 85.2 91.3 106.5 92.4 97.5 107 51.1 98.6 102.2 114.3 99.4 72.5 92.3 99.4 85.9 109.4 97.6 104.7 56.9 86.7 108.5 103.4 86.2 71 75.9 87.1 102 88.5 87.8 100.8 50.6 85.9

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	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Seasonal Decomposition by Loess - Parameters
Component	Window	Degree	Jump
Seasonal	611	0	62
Trend	19	1	2
Low-pass	13	1	2

Seasonal Decomposition by Loess - Time Series Components
t	Observed	Fitted	Seasonal	Trend	Remainder
1	92.9	94.089030504534	1.96374260515108	89.747226890315	1.18903050453393
2	107.7	110.024726465300	15.8226260201951	89.5526475145053	2.32472646529963
3	103.5	103.874030279635	13.7679015816693	89.3580681386955	0.374030279635207
4	91.1	89.12697679363	3.86757172508962	89.2054514812804	-1.97302320637003
5	79.8	85.6999329376615	-15.1527677615268	89.0528348238653	5.89993293766149
6	71.9	65.0846393014848	-10.2028726749487	88.9182333734639	-6.81536069851519
7	82.9	78.629352981149	-1.61298490421155	88.7836319230625	-4.27064701885094
8	90.1	84.476510689957	7.10005530534104	88.623434004702	-5.62348931004306
9	100.7	107.403669107957	5.53309480570152	88.4632360863415	6.70366910795694
10	90.7	88.7047425735892	4.25842386391336	88.4368335624974	-1.99525742641076
11	108.8	113.905823442156	15.2837455191904	88.4104310386533	5.10582344215629
12	44.1	40.2667515864325	-40.6285343064881	88.5617827200556	-3.83324841356749
13	93.6	96.523122993391	1.96374260515108	88.713134401458	2.92312299339093
14	107.4	110.126190101638	15.8226260201951	88.8511838781664	2.72619010163849
15	96.5	90.242865063456	13.7679015816693	88.9892333548748	-6.25713493654408
16	93.6	94.3187783065757	3.86757172508962	89.0136499683347	0.7187783065757
17	76.5	79.1147011797322	-15.1527677615268	89.0380665817946	2.61470117973222
18	76.7	74.4923463332722	-10.2028726749487	89.1105263416765	-2.20765366672779
19	84	80.4299988026531	-1.61298490421155	89.1829861015584	-3.5700011973469
20	103.3	110.095008341835	7.10005530534104	89.404936352824	6.79500834183493
21	88.5	81.8400185902089	5.53309480570152	89.6268866040896	-6.65998140979111
22	99	103.671382938326	4.25842386391336	90.0701931977609	4.67138293832578
23	105.9	106.002754689377	15.2837455191904	90.5134997914322	0.102754689377434
24	44.7	39.0035452507058	-40.6285343064881	91.0249890557823	-5.69645474929416
25	94	94.4997790747165	1.96374260515108	91.5364783201325	0.499779074716457
26	107.1	106.418779137035	15.8226260201951	91.95859484277	-0.681220862965048
27	104.8	103.451387052923	13.7679015816693	92.3807113654074	-1.34861294707666
28	102.5	108.487493538872	3.86757172508962	92.6449347360383	5.98749353887213
29	77.7	77.6436096548577	-15.1527677615268	92.9091581066691	-0.0563903451423329
30	85.2	87.5223673240288	-10.2028726749487	93.0805053509199	2.32236732402885
31	91.3	90.961132309041	-1.61298490421155	93.2518525951706	-0.338867690959049
32	106.5	112.575106148121	7.10005530534104	93.324838546538	6.07510614812097
33	92.4	85.8690806963931	5.53309480570152	93.3978244979054	-6.53091930360692
34	97.5	97.3493739055858	4.25842386391336	93.3922022305009	-0.150626094414250
35	107	105.329674517713	15.2837455191904	93.3865799630964	-1.67032548228681
36	51.1	49.351010761898	-40.6285343064881	93.4775235445901	-1.74898923810198
37	98.6	101.667790268765	1.96374260515108	93.5684671260839	3.06779026876504
38	102.2	94.8670055095507	15.8226260201951	93.7103684702542	-7.33299449044932
39	114.3	120.979828603906	13.7679015816693	93.8522698144245	6.67982860390619
40	99.4	100.920777250856	3.86757172508962	94.0116510240547	1.52077725085564
41	72.5	65.9817355278418	-15.1527677615268	94.171032233685	-6.51826447215815
42	92.3	100.685635374884	-10.2028726749487	94.1172373000648	8.38563537488386
43	99.4	106.349542537767	-1.61298490421155	94.0634423664447	6.9495425377668
44	85.9	70.9951704927344	7.10005530534104	93.7047742019245	-14.9048295072656
45	109.4	119.920799156894	5.53309480570152	93.3461060374043	10.5207991568942
46	97.6	98.302934777586	4.25842386391336	92.6386413585006	0.702934777585995
47	104.7	102.185077801213	15.2837455191904	91.931176679597	-2.51492219878740
48	56.9	63.229580657253	-40.6285343064881	91.198953649235	6.32958065725305
49	86.7	80.9695267759758	1.96374260515108	90.4667306188732	-5.73047322402425
50	108.5	111.314135305670	15.8226260201951	89.8632386741351	2.81413530566977
51	103.4	103.772351688934	13.7679015816693	89.2597467293971	0.372351688933662
52	86.2	79.7649664867013	3.86757172508962	88.7674617882091	-6.43503351329873
53	71	68.8775909145056	-15.1527677615268	88.2751768470212	-2.12240908549438
54	75.9	74.0981228611814	-10.2028726749487	87.9047498137673	-1.80187713881860
55	87.1	88.2786621236981	-1.61298490421155	87.5343227805134	1.17866212369809
56	102	109.695064507541	7.10005530534104	87.2048801871177	7.6950645075413
57	88.5	84.5914676005766	5.53309480570152	86.8754375937219	-3.90853239942339
58	87.8	84.763816517776	4.25842386391336	86.5777596183106	-3.03618348222399
59	100.8	100.036172837910	15.2837455191904	86.2800816428994	-0.763827162089825
60	50.6	55.8214789652396	-40.6285343064881	86.0070553412485	5.22147896523961
61	85.9	84.1022283552513	1.96374260515108	85.7340290395977	-1.79777164474875

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/1j1as1259948291.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/1j1as1259948291.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/2egzb1259948291.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/2egzb1259948291.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/3zupp1259948291.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/3zupp1259948291.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/4wept1259948291.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259948334ocezgodyrdio9th/4wept1259948291.ps (open in new window)

Parameters (Session):

par1 = 12 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;

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')

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.

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