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Faillissementen detailhandel Denemarken

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 10 Dec 2010 14:31:58 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v.htm/, Retrieved Fri, 10 Dec 2010 15:31:36 +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/Dec/10/t12919914914eemnrh508do89v.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:

KDGP2W92 - PAUWELS

Dataseries X:

» Textbox « » Textfile « » CSV «

12 13 23 24 21 20 18 13 12 25 21 17 10 15 23 12 10 21 9 13 17 14 20 12 13 14 23 14 21 21 21 7 15 28 28 18 22 30 1 26 29 24 26 19 19 41 36 54 49 33 50 43 51 46 45 23 56 41 48 43

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	12	NA	NA	0.184895833333335	NA
2	13	NA	NA	-0.700520833333334	NA
3	23	NA	NA	-0.0130208333333296	NA
4	24	NA	NA	-1.13802083333333	NA
5	21	NA	NA	2.4140625	NA
6	20	NA	NA	2.11197916666667	NA
7	18	16.5598958333333	18.1666666666667	-1.60677083333334	1.44010416666667
8	13	10.4661458333333	18.1666666666667	-7.70052083333334	2.53385416666667
9	12	12.8098958333333	18.25	-5.44010416666667	-0.809895833333329
10	25	23.0807291666667	17.75	5.33072916666667	1.91927083333334
11	21	20.8619791666667	16.7916666666667	4.0703125	0.138020833333336
12	17	18.8619791666667	16.375	2.48697916666667	-1.86197916666667
13	10	16.2265625	16.0416666666667	0.184895833333335	-6.2265625
14	15	14.9661458333333	15.6666666666667	-0.700520833333334	0.0338541666666679
15	23	15.8619791666667	15.875	-0.0130208333333296	7.13802083333333
16	12	14.4869791666667	15.625	-1.13802083333333	-2.48697916666666
17	10	17.5390625	15.125	2.4140625	-7.5390625
18	21	16.9869791666667	14.875	2.11197916666667	4.01302083333333
19	9	13.1848958333333	14.7916666666667	-1.60677083333334	-4.18489583333333
20	13	7.17447916666666	14.875	-7.70052083333334	5.82552083333334
21	17	9.39322916666667	14.8333333333333	-5.44010416666667	7.60677083333333
22	14	20.2473958333333	14.9166666666667	5.33072916666667	-6.24739583333333
23	20	19.5286458333333	15.4583333333333	4.0703125	0.471354166666668
24	12	18.4036458333333	15.9166666666667	2.48697916666667	-6.40364583333333
25	13	16.6015625	16.4166666666667	0.184895833333335	-3.6015625
26	14	15.9661458333333	16.6666666666667	-0.700520833333334	-1.96614583333333
27	23	16.3203125	16.3333333333333	-0.0130208333333296	6.6796875
28	14	15.6953125	16.8333333333333	-1.13802083333333	-1.69531250000000
29	21	20.1640625	17.75	2.4140625	0.835937500000004
30	21	20.4453125	18.3333333333333	2.11197916666667	0.5546875
31	21	17.3515625	18.9583333333333	-1.60677083333334	3.6484375
32	7	12.2994791666667	20	-7.70052083333334	-5.29947916666667
33	15	14.3098958333333	19.75	-5.44010416666667	0.690104166666668
34	28	24.6640625	19.3333333333333	5.33072916666667	3.33593750000000
35	28	24.2369791666667	20.1666666666667	4.0703125	3.76302083333334
36	18	23.1119791666667	20.625	2.48697916666667	-5.11197916666666
37	22	21.1432291666667	20.9583333333333	0.184895833333335	0.856770833333332
38	30	20.9661458333333	21.6666666666667	-0.700520833333334	9.03385416666666
39	1	22.3203125	22.3333333333333	-0.0130208333333296	-21.3203125
40	26	21.9036458333333	23.0416666666667	-1.13802083333333	4.09635416666667
41	29	26.3307291666667	23.9166666666667	2.4140625	2.66927083333334
42	24	27.8619791666667	25.75	2.11197916666667	-3.86197916666667
43	26	26.7682291666667	28.375	-1.60677083333334	-0.768229166666668
44	19	21.9244791666667	29.625	-7.70052083333334	-2.92447916666666
45	19	26.3515625	31.7916666666667	-5.44010416666667	-7.3515625
46	41	39.8723958333333	34.5416666666667	5.33072916666667	1.12760416666667
47	36	40.2369791666667	36.1666666666667	4.0703125	-4.23697916666666
48	54	40.4869791666667	38	2.48697916666667	13.5130208333333
49	49	39.8932291666667	39.7083333333333	0.184895833333335	9.10677083333334
50	33	39.9661458333333	40.6666666666667	-0.700520833333334	-6.96614583333333
51	50	42.3619791666667	42.375	-0.0130208333333296	7.63802083333334
52	43	42.7786458333333	43.9166666666667	-1.13802083333333	0.221354166666664
53	51	46.8307291666667	44.4166666666667	2.4140625	4.16927083333334
54	46	46.5703125	44.4583333333333	2.11197916666667	-0.570312499999993
55	45	NA	NA	-1.60677083333334	NA
56	23	NA	NA	-7.70052083333334	NA
57	56	NA	NA	-5.44010416666667	NA
58	41	NA	NA	5.33072916666667	NA
59	48	NA	NA	4.0703125	NA
60	43	NA	NA	2.48697916666667	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/15qve1291991515.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/15qve1291991515.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/25qve1291991515.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/25qve1291991515.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/35qve1291991515.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/35qve1291991515.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/4yhuh1291991515.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/10/t12919914914eemnrh508do89v/4yhuh1291991515.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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