Home » date » 2009 » Dec » 03 »

Ad hoc forecasting 2

*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, 03 Dec 2009 10:20:44 -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/03/t12598609304yhq6grx3bff63i.htm/, Retrieved Thu, 03 Dec 2009 18:22:15 +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/03/t12598609304yhq6grx3bff63i.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:

Uitleg in Word document

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

96.96 93.11 95.62 98.30 96.38 100.82 99.06 94.03 102.07 99.31 98.64 101.82 99.14 97.63 100.06 101.32 101.49 105.43 105.09 99.48 108.53 104.34 106.10 107.35 103.00 104.50 105.17 104.84 106.18 108.86 107.77 102.74 112.63 106.26 108.86 111.38 106.85 107.86 107.94 111.38 111.29 113.72 111.88 109.87 113.72 111.71 114.81 112.05 111.54 110.87 110.87 115.48 111.63 116.24 113.56 106.01 110.45 107.77 108.61 108.19

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	1 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	96.96	98.8618114181477	-1.53228158025078	96.590470162103	1.90181141814772
2	93.11	91.8544777226643	-2.48067788538229	96.846200162718	-1.25552227733567
3	95.62	95.7251456883997	-1.58707585173258	97.1019301633329	0.105145688399716
4	98.3	98.6332579927074	0.598901142819897	97.3678408644727	0.333257992707374
5	96.38	95.5433670503845	-0.417118615997089	97.6337515656126	-0.836632949615492
6	100.82	100.662442365603	3.07134958939907	97.9062080449982	-0.157557634397293
7	99.06	98.5435162574794	1.39781921813674	98.1786645243839	-0.516483742520592
8	94.03	93.3758600506391	-3.77678718452309	98.460927133884	-0.654139949360896
9	102.07	102.248203812430	3.14860644418605	98.7431897433841	0.178203812429828
10	99.31	100.131994975942	-0.601542900441971	99.0895479245003	0.82199497594165
11	98.64	97.067783815577	0.77631007880653	99.4359061056165	-1.57221618442307
12	101.82	102.390331896416	1.40249658374846	99.8471715198356	0.570331896415908
13	99.14	99.553844646196	-1.53228158025078	100.258436934055	0.413844646196054
14	97.63	97.0152417303699	-2.48067788538229	100.725436155012	-0.61475826963013
15	100.06	100.514640475762	-1.58707585173258	101.192435375970	0.454640475762474
16	101.32	100.347341443794	0.598901142819897	101.693757413386	-0.972658556205516
17	101.49	101.202039165196	-0.417118615997089	102.195079450801	-0.287960834804039
18	105.43	105.099007592981	3.07134958939907	102.689642817620	-0.330992407018726
19	105.09	105.597974597425	1.39781921813674	103.184206184438	0.507974597425076
20	99.48	99.0937544083436	-3.77678718452309	103.643032776179	-0.386245591656404
21	108.53	109.809534187893	3.14860644418605	104.101859367921	1.27953418789318
22	104.34	104.795275661898	-0.601542900441971	104.486267238544	0.455275661897829
23	106.1	106.553014812026	0.77631007880653	104.870675109168	0.453014812025941
24	107.35	108.142161974916	1.40249658374846	105.155341441335	0.79216197491641
25	103	102.092273806748	-1.53228158025078	105.440007773503	-0.907726193251946
26	104.5	105.804956072695	-2.48067788538229	105.675721812687	1.30495607269529
27	105.17	106.015639999861	-1.58707585173258	105.911435851871	0.845639999861305
28	104.84	102.932215119881	0.598901142819897	106.148883737299	-1.90778488011925
29	106.18	106.390786993270	-0.417118615997089	106.386331622727	0.210786993269650
30	108.86	107.983676412098	3.07134958939907	106.664973998503	-0.876323587901837
31	107.77	107.198564407585	1.39781921813674	106.943616374278	-0.571435592414815
32	102.74	101.979251762594	-3.77678718452309	107.277535421929	-0.760748237405807
33	112.63	114.499939086234	3.14860644418605	107.611454469580	1.86993908623427
34	106.26	105.104272534902	-0.601542900441971	108.017270365539	-1.15572746509751
35	108.86	108.520603659694	0.77631007880653	108.423086261499	-0.339396340305825
36	111.38	112.514760346310	1.40249658374846	108.842743069941	1.13476034631044
37	106.85	105.969881701868	-1.53228158025078	109.262399878383	-0.880118298132132
38	107.86	108.552889406246	-2.48067788538229	109.647788479137	0.692889406245598
39	107.94	107.433898771842	-1.58707585173258	110.033177079890	-0.506101228157888
40	111.38	111.777549105477	0.598901142819897	110.383549751703	0.397549105476799
41	111.29	112.263196192481	-0.417118615997089	110.733922423516	0.97319619248094
42	113.72	113.329282600190	3.07134958939907	111.039367810411	-0.390717399810171
43	111.88	111.017367584557	1.39781921813674	111.344813197306	-0.862632415442775
44	109.87	111.908825413066	-3.77678718452309	111.607961771457	2.03882541306633
45	113.72	112.420283210206	3.14860644418605	111.871110345607	-1.29971678979351
46	111.71	111.930453620389	-0.601542900441971	112.091089280053	0.220453620389435
47	114.81	116.532621706696	0.77631007880653	112.311068214498	1.72262170669589
48	112.05	110.265898514554	1.40249658374846	112.431604901698	-1.78410148544617
49	111.54	112.060139991353	-1.53228158025078	112.552141588898	0.520139991352934
50	110.87	111.771958629940	-2.48067788538229	112.448719255443	0.901958629939585
51	110.87	110.981778929745	-1.58707585173258	112.345296921988	0.111778929745029
52	115.48	118.492884285825	0.598901142819897	111.868214571355	3.01288428582498
53	111.63	112.285986395274	-0.417118615997089	111.391132220723	0.655986395274383
54	116.24	118.504102710343	3.07134958939907	110.904547700258	2.26410271034305
55	113.56	115.304217602070	1.39781921813674	110.417963179793	1.74421760207022
56	106.01	105.895091242703	-3.77678718452309	109.901695941820	-0.114908757297286
57	110.45	108.365964851966	3.14860644418605	109.385428703848	-2.08403514803375
58	107.77	107.317813537045	-0.601542900441971	108.823729363397	-0.452186462955069
59	108.61	108.181659898247	0.77631007880653	108.262030022946	-0.428340101752909
60	108.19	107.309264771779	1.40249658374846	107.668238644473	-0.88073522822144

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/1yjpy1259860842.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/1yjpy1259860842.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/2071n1259860842.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/2071n1259860842.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/3abyq1259860842.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/3abyq1259860842.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/4wjuw1259860842.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/03/t12598609304yhq6grx3bff63i/4wjuw1259860842.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