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decompositie porto

*Unverified author*

R Software Module: /rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Mon, 25 Jan 2010 10:20:25 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob.htm/, Retrieved Mon, 25 Jan 2010 18:23:03 +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/Jan/25/t1264440177qfhlzvkndp7tzob.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:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

8,2 8,21 8,22 8,2 8,18 8,2 8,19 8,24 8,31 8,27 8,36 8,32 8,29 8,27 8,27 8,43 8,46 8,48 8,46 8,46 8,43 8,4 8,38 8,3 8,39 8,53 8,52 8,54 8,62 8,52 8,49 8,44 8,31 8,26 8,21 8,03 7,89 7,83 7,85 7,84 7,88 8,01 8,08 8,11 8,11 8,07 8,06 7,95 7,95 8,07 8,17 8,21 8,2 8,19 8,18 8,16 8,17 8,17 8,19 8,01 8,04 8,13 8,14 8,17 8,25 8,27 8,27 8,26 8,24 8,21 8,25 8,06 8,16 8,32 8,43 8,39 8,41

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
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.2	NA	NA	-0.113965277777777	NA
2	8.21	NA	NA	-0.0607986111111114	NA
3	8.22	NA	NA	-0.0363819444444442	NA
4	8.2	NA	NA	0.0127013888888886	NA
5	8.18	NA	NA	0.0581180555555551	NA
6	8.2	NA	NA	0.0732013888888888	NA
7	8.19	8.32386805555555	8.24541666666667	0.0784513888888885	-0.133868055555554
8	8.24	8.32078472222222	8.25166666666667	0.0691180555555553	-0.080784722222221
9	8.31	8.28961805555556	8.25625	0.0333680555555556	0.0203819444444449
10	8.27	8.27028472222222	8.26791666666667	0.00236805555555576	-0.0002847222222222
11	8.36	8.28828472222222	8.28916666666667	-0.000881944444444131	0.071715277777777
12	8.32	8.19720138888889	8.3125	-0.115298611111111	0.122798611111113
13	8.29	8.22145138888889	8.33541666666667	-0.113965277777777	0.0685486111111118
14	8.27	8.29503472222222	8.35583333333333	-0.0607986111111114	-0.0250347222222214
15	8.27	8.33361805555555	8.37	-0.0363819444444442	-0.0636180555555548
16	8.43	8.39311805555555	8.38041666666667	0.0127013888888886	0.0368819444444455
17	8.46	8.44478472222222	8.38666666666667	0.0581180555555551	0.0152152777777790
18	8.48	8.45986805555555	8.38666666666667	0.0732013888888888	0.0201319444444454
19	8.46	8.46845138888889	8.39	0.0784513888888885	-0.00845138888888819
20	8.46	8.47411805555555	8.405	0.0691180555555553	-0.0141180555555529
21	8.43	8.45961805555556	8.42625	0.0333680555555556	-0.0296180555555559
22	8.4	8.44361805555556	8.44125	0.00236805555555576	-0.0436180555555552
23	8.38	8.45161805555556	8.4525	-0.000881944444444131	-0.0716180555555557
24	8.3	8.34553472222222	8.46083333333333	-0.115298611111111	-0.0455347222222198
25	8.39	8.34978472222222	8.46375	-0.113965277777777	0.0402152777777811
26	8.53	8.40336805555556	8.46416666666667	-0.0607986111111114	0.126631944444444
27	8.52	8.42195138888889	8.45833333333333	-0.0363819444444442	0.0980486111111123
28	8.54	8.46020138888889	8.4475	0.0127013888888886	0.0797986111111104
29	8.62	8.49270138888889	8.43458333333333	0.0581180555555551	0.12729861111111
30	8.52	8.48945138888889	8.41625	0.0732013888888888	0.0305486111111115
31	8.49	8.46261805555555	8.38416666666667	0.0784513888888885	0.0273819444444463
32	8.44	8.40328472222222	8.33416666666667	0.0691180555555553	0.0367152777777786
33	8.31	8.31045138888889	8.27708333333333	0.0333680555555556	-0.000451388888887294
34	8.26	8.22236805555555	8.22	0.00236805555555576	0.0376319444444455
35	8.21	8.15911805555555	8.16	-0.000881944444444131	0.0508819444444466
36	8.03	7.99261805555556	8.10791666666667	-0.115298611111111	0.0373819444444443
37	7.89	7.95561805555556	8.06958333333333	-0.113965277777777	-0.0656180555555554
38	7.83	7.97795138888889	8.03875	-0.0607986111111114	-0.147951388888889
39	7.85	7.98028472222222	8.01666666666667	-0.0363819444444442	-0.130284722222222
40	7.84	8.01311805555556	8.00041666666667	0.0127013888888886	-0.173118055555555
41	7.88	8.04436805555555	7.98625	0.0581180555555551	-0.164368055555554
42	8.01	8.04986805555555	7.97666666666667	0.0732013888888888	-0.0398680555555551
43	8.08	8.05428472222222	7.97583333333333	0.0784513888888885	0.0257152777777776
44	8.11	8.05745138888889	7.98833333333333	0.0691180555555553	0.0525486111111109
45	8.11	8.04503472222222	8.01166666666667	0.0333680555555556	0.0649652777777767
46	8.07	8.04278472222222	8.04041666666667	0.00236805555555576	0.0272152777777777
47	8.06	8.06828472222222	8.06916666666667	-0.000881944444444131	-0.0082847222222231
48	7.95	7.97470138888889	8.09	-0.115298611111111	-0.0247013888888894
49	7.95	7.98770138888889	8.10166666666667	-0.113965277777777	-0.0377013888888893
50	8.07	8.04711805555555	8.10791666666667	-0.0607986111111114	0.0228819444444461
51	8.17	8.07611805555556	8.1125	-0.0363819444444442	0.093881944444444
52	8.21	8.13186805555556	8.11916666666667	0.0127013888888886	0.0781319444444453
53	8.2	8.18686805555556	8.12875	0.0581180555555551	0.013131944444444
54	8.19	8.20986805555555	8.13666666666667	0.0732013888888888	-0.0198680555555555
55	8.18	8.22136805555556	8.14291666666667	0.0784513888888885	-0.0413680555555569
56	8.16	8.21828472222222	8.14916666666667	0.0691180555555553	-0.0582847222222203
57	8.17	8.18378472222222	8.15041666666667	0.0333680555555556	-0.0137847222222227
58	8.17	8.14986805555555	8.1475	0.00236805555555576	0.0201319444444454
59	8.19	8.14703472222222	8.14791666666667	-0.000881944444444131	0.0429652777777783
60	8.01	8.03803472222222	8.15333333333333	-0.115298611111111	-0.0280347222222215
61	8.04	8.04645138888889	8.16041666666667	-0.113965277777777	-0.0064513888888893
62	8.13	8.10753472222222	8.16833333333333	-0.0607986111111114	0.0224652777777798
63	8.14	8.13903472222222	8.17541666666667	-0.0363819444444442	0.000965277777780216
64	8.17	8.19270138888889	8.18	0.0127013888888886	-0.0227013888888905
65	8.25	8.24228472222222	8.18416666666667	0.0581180555555551	0.0077152777777787
66	8.27	8.26195138888889	8.18875	0.0732013888888888	0.00804861111111244
67	8.27	8.27428472222222	8.19583333333333	0.0784513888888885	-0.00428472222222176
68	8.26	8.27786805555555	8.20875	0.0691180555555553	-0.0178680555555548
69	8.24	8.26211805555556	8.22875	0.0333680555555556	-0.0221180555555556
70	8.21	8.25236805555556	8.25	0.00236805555555576	-0.0423680555555546
71	8.25	8.26495138888889	8.26583333333333	-0.000881944444444131	-0.0149513888888890
72	8.06	NA	NA	-0.115298611111111	NA
73	8.16	NA	NA	NA	NA
74	8.32	NA	NA	NA	NA
75	8.43	NA	NA	NA	NA
76	8.39	NA	NA	NA	NA
77	8.41	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/1pd521264440023.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/1pd521264440023.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/29hla1264440023.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/29hla1264440023.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/33pe71264440023.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/33pe71264440023.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/4osye1264440023.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/25/t1264440177qfhlzvkndp7tzob/4osye1264440023.ps (open in new window)

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)

x <- ts(x,freq=par2)

m <- decompose(x,type=par1)

m$figure

bitmap(file='test1.png')

plot(m)

dev.off()

mylagmax <- length(x)/2

bitmap(file='test2.png')

op <- par(mfrow = c(2,2))

acf(as.numeric(x),lag.max = mylagmax,main='Observed')

acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')

acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')

acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')

par(op)

dev.off()

bitmap(file='test3.png')

op <- par(mfrow = c(2,2))

spectrum(as.numeric(x),main='Observed')

spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')

spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')

spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')

par(op)

dev.off()

bitmap(file='test4.png')

op <- par(mfrow = c(2,2))

cpgram(as.numeric(x),main='Observed')

cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')

cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')

cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')

par(op)

dev.off()

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'t',header=TRUE)

a<-table.element(a,'Observations',header=TRUE)

a<-table.element(a,'Fit',header=TRUE)

a<-table.element(a,'Trend',header=TRUE)

a<-table.element(a,'Seasonal',header=TRUE)

a<-table.element(a,'Random',header=TRUE)

a<-table.row.end(a)

for (i in 1:length(m$trend)) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,x[i])

if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])

a<-table.element(a,m$trend[i])

a<-table.element(a,m$seasonal[i])

a<-table.element(a,m$random[i])

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

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

Software written by Ed van Stee & Patrick Wessa

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