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*The author of this computation has been verified*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 01 Dec 2009 12:00:39 -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/01/t12596940825vd9xi4gh3vli3k.htm/, Retrieved Tue, 01 Dec 2009 20:01:27 +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/01/t12596940825vd9xi4gh3vli3k.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 «

8.9 8.8 8.3 7.5 7.2 7.4 8.8 9.3 9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8 8.2 8.1 8.1 8 7.9 7.9 8 8 7.9 8 7.7 7.2 7.5 7.3 7 7 7 7.2 7.3 7.1 6.8 6.4 6.1 6.5 7.7 7.9 7.5 6.9 6.6 6.9

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	7 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.9	NA	NA	0.152083333333333	NA
2	8.8	NA	NA	0.153125	NA
3	8.3	NA	NA	0.0364583333333331	NA
4	7.5	NA	NA	-0.101041666666667	NA
5	7.2	NA	NA	-0.290625	NA
6	7.4	NA	NA	-0.409375	NA
7	8.8	8.51770833333333	8.375	0.142708333333333	0.282291666666667
8	9.3	8.60208333333333	8.35	0.252083333333333	0.697916666666668
9	9.3	8.56041666666667	8.35	0.210416666666667	0.739583333333334
10	8.7	8.4	8.3875	0.0125000000000001	0.300000000000001
11	8.2	8.31458333333333	8.45416666666667	-0.139583333333334	-0.114583333333334
12	8.3	8.49375	8.5125	-0.0187499999999997	-0.193750000000000
13	8.5	8.67708333333333	8.525	0.152083333333333	-0.177083333333334
14	8.6	8.64479166666666	8.49166666666667	0.153125	-0.044791666666665
15	8.5	8.478125	8.44166666666666	0.0364583333333331	0.0218750000000014
16	8.2	8.30729166666667	8.40833333333333	-0.101041666666667	-0.107291666666667
17	8.1	8.11770833333333	8.40833333333333	-0.290625	-0.0177083333333332
18	7.9	8.015625	8.425	-0.409375	-0.115624999999998
19	8.6	8.584375	8.44166666666666	0.142708333333333	0.0156250000000018
20	8.7	8.70625	8.45416666666667	0.252083333333333	-0.00624999999999964
21	8.7	8.67291666666666	8.4625	0.210416666666667	0.0270833333333353
22	8.5	8.49166666666667	8.47916666666667	0.0125000000000001	0.00833333333333464
23	8.4	8.36041666666667	8.5	-0.139583333333334	0.0395833333333346
24	8.5	8.49375	8.5125	-0.0187499999999997	0.00624999999999964
25	8.7	8.65208333333333	8.5	0.152083333333333	0.0479166666666675
26	8.7	8.61145833333333	8.45833333333333	0.153125	0.0885416666666679
27	8.6	8.44479166666667	8.40833333333333	0.0364583333333331	0.155208333333333
28	8.5	8.26145833333333	8.3625	-0.101041666666667	0.23854166666667
29	8.3	8.03020833333333	8.32083333333333	-0.290625	0.26979166666667
30	8	7.865625	8.275	-0.409375	0.134375000000002
31	8.2	8.36354166666667	8.22083333333333	0.142708333333333	-0.163541666666667
32	8.1	8.41458333333333	8.1625	0.252083333333333	-0.314583333333333
33	8.1	8.31458333333333	8.10416666666667	0.210416666666667	-0.214583333333334
34	8	8.06666666666666	8.05416666666667	0.0125000000000001	-0.0666666666666655
35	7.9	7.86875	8.00833333333333	-0.139583333333334	0.03125
36	7.9	7.93125	7.95	-0.0187499999999997	-0.0312499999999991
37	8	8.03958333333333	7.8875	0.152083333333333	-0.0395833333333329
38	8	7.978125	7.825	0.153125	0.0218749999999996
39	7.9	7.78229166666667	7.74583333333333	0.0364583333333331	0.117708333333333
40	8	7.55729166666667	7.65833333333333	-0.101041666666667	0.442708333333334
41	7.7	7.28854166666667	7.57916666666667	-0.290625	0.411458333333334
42	7.2	7.103125	7.5125	-0.409375	0.096874999999999
43	7.5	7.596875	7.45416666666667	0.142708333333333	-0.096874999999999
44	7.3	7.63958333333333	7.3875	0.252083333333333	-0.339583333333332
45	7	7.51458333333333	7.30416666666667	0.210416666666667	-0.514583333333333
46	7	7.20416666666667	7.19166666666667	0.0125000000000001	-0.204166666666666
47	7	6.91875	7.05833333333333	-0.139583333333334	0.0812500000000025
48	7.2	6.94375	6.9625	-0.0187499999999997	0.256250000000001
49	7.3	7.09375	6.94166666666667	0.152083333333333	0.206250000000001
50	7.1	7.128125	6.975	0.153125	-0.0281249999999984
51	6.8	7.05729166666667	7.02083333333333	0.0364583333333331	-0.257291666666665
52	6.4	6.93645833333333	7.0375	-0.101041666666667	-0.536458333333333
53	6.1	6.72604166666667	7.01666666666667	-0.290625	-0.626041666666667
54	6.5	6.578125	6.9875	-0.409375	-0.0781249999999991
55	7.7	NA	NA	0.142708333333333	NA
56	7.9	NA	NA	0.252083333333333	NA
57	7.5	NA	NA	0.210416666666667	NA
58	6.9	NA	NA	0.0125000000000001	NA
59	6.6	NA	NA	-0.139583333333334	NA
60	6.9	NA	NA	-0.0187499999999997	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/1oxuv1259694031.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/1oxuv1259694031.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/2lyw01259694031.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/2lyw01259694031.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/3035a1259694031.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/3035a1259694031.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/4r7wt1259694031.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/01/t12596940825vd9xi4gh3vli3k/4r7wt1259694031.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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