Home » date » 2009 » May » 31 »

Additief decompositiemodel - Omzetcijfers Carrefour Burcht - Jeroen Van Eeckhoven

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 31 May 2009 06:30:27 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0.htm/, Retrieved Sun, 31 May 2009 14:31:46 +0200

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/May/31/t1243773106czpyvxcpmozqkj0.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 «

2291180 1971664 2193270 2197733 2345324 2195121 2170583 2241521 2154945 2912568 2392562 3336621 4080642 3735329 4018383 4171360 3855698 4101316 4199346 3959646 3960841 4784025 4105467 5929558 4048642 3828808 4268127 4171816 4004783 4295447 3968177 3918480 4040260 4530715 4103330 6025506 4632308 4133863 4519182 4151573 4486595 4504699 4180443 4222193 4373727 4734738 4403232 5903985 4414074 4061816 4504697 3994176 4114925 4485120 4171230 4476075 4179369 4823185 4585751 6110454 4279575 3782118 4098678 4065616 4413733 4481214 4345018 4294488 4361269 4535031 4318397 6040168

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2291180	NA	NA	96664.1145833333	NA
2	1971664	NA	NA	-321225.635416667	NA
3	2193270	NA	NA	16706.8729166666	NA
4	2197733	NA	NA	-186104.885416667	NA
5	2345324	NA	NA	-151435.435416667	NA
6	2195121	NA	NA	8398.7812499998	NA
7	2170583	2185384.66458333	2441485.25	-256100.585416667	-14801.6645833338
8	2241521	2327401.74791667	2589532.20833333	-262130.460416666	-85880.7479166668
9	2154945	2424214.04791667	2739064.625	-314850.577083333	-269269.047916667
10	2912568	3166268.58958333	2897345.45833333	268923.13125	-253700.589583333
11	2392562	2839655.06458333	3042512.16666667	-202857.102083333	-447093.064583333
12	3336621	4488880.98958333	3184869.20833333	1304011.78125	-1152259.98958333
13	4080642	3445489.90625	3348825.79166667	96664.1145833333	635152.09375
14	3735329	3183720.48958333	3504946.125	-321225.635416667	551608.510416667
15	4018383	3668487.20625	3651780.33333333	16706.8729166666	349895.79375
16	4171360	3618898.48958333	3805003.375	-186104.885416667	552461.510416667
17	3855698	3802916.35625	3954351.79166667	-151435.435416667	52781.6437499998
18	4101316	4142160.65625	4133761.875	8398.7812499998	-40844.65625
19	4199346	3984366.99791667	4240467.58333333	-256100.585416667	214979.002083334
20	3959646	3980898.74791667	4243029.20833333	-262130.460416666	-21252.7479166668
21	3960841	3942479.58958333	4257330.16666667	-314850.577083333	18361.4104166664
22	4784025	4536678.29791667	4267755.16666667	268923.13125	247346.702083333
23	4105467	4071128.93958333	4273986.04166667	-202857.102083333	34338.0604166668
24	5929558	5592298.48958333	4288286.70833333	1304011.78125	337259.510416667
25	4048642	4383407.57291667	4286743.45833333	96664.1145833333	-334765.572916667
26	3828808	3954170.53125	4275396.16666667	-321225.635416667	-125362.53125
27	4268127	4293696.91458333	4276990.04166667	16706.8729166666	-25569.9145833338
28	4171816	4083639.69791667	4269744.58333333	-186104.885416667	88176.302083333
29	4004783	4107665.52291667	4259100.95833333	-151435.435416667	-102882.522916668
30	4295447	4271408.53125	4263009.75	8398.7812499998	24038.46875
31	3968177	4035226.41458333	4291327	-256100.585416667	-67049.4145833328
32	3918480	4066226.58125	4328357.04166667	-262130.460416666	-147746.581250000
33	4040260	4036677.71458333	4351528.29166667	-314850.577083333	3582.28541666735
34	4530715	4630068.58958333	4361145.45833333	268923.13125	-99353.5895833327
35	4103330	4177520.39791667	4380377.5	-202857.102083333	-74190.3979166662
36	6025506	5713183.61458333	4409171.83333333	1304011.78125	312322.385416667
37	4632308	4523399.19791667	4426735.08333333	96664.1145833333	108908.802083334
38	4133863	4127008.57291667	4448234.20833333	-321225.635416667	6854.42708333395
39	4519182	4491490.24791667	4474783.375	16706.8729166666	27691.7520833332
40	4151573	4311073.90625	4497178.79166667	-186104.885416667	-159500.90625
41	4486595	4366740.23125	4518175.66666667	-151435.435416667	119854.768750001
42	4504699	4534006.98958333	4525608.20833333	8398.7812499998	-29307.989583333
43	4180443	4255351.16458333	4511451.75	-256100.585416667	-74908.1645833319
44	4222193	4237226.24791667	4499356.70833333	-262130.460416666	-15033.2479166668
45	4373727	4180900.63125	4495751.20833333	-314850.577083333	192826.368750000
46	4734738	4757512.58958333	4488589.45833333	268923.13125	-22774.5895833327
47	4403232	4263687.89791667	4466545	-202857.102083333	139544.102083335
48	5903985	5754254.73958333	4450242.95833333	1304011.78125	149730.260416667
49	4414074	4545707.40625	4449043.29166667	96664.1145833333	-131633.406249999
50	4061816	4138012.19791667	4459237.83333333	-321225.635416667	-76196.197916666
51	4504697	4478424.87291667	4461718	16706.8729166666	26272.1270833332
52	3994176	4271200.15625	4457305.04166667	-186104.885416667	-277024.156249999
53	4114925	4317159.85625	4468595.29166667	-151435.435416667	-202234.856249999
54	4485120	4493201.90625	4484803.125	8398.7812499998	-8081.90625
55	4171230	4231701.28958333	4487801.875	-256100.585416667	-60471.2895833328
56	4476075	4208413.20625	4470543.66666667	-262130.460416666	267661.79375
57	4179369	4127121.54791667	4441972.125	-314850.577083333	52247.4520833343
58	4823185	4696954.46458333	4428031.33333333	268923.13125	126230.535416667
59	4585751	4240601.23125	4443458.33333333	-202857.102083333	345149.768750001
60	6110454	5759757.69791667	4455745.91666667	1304011.78125	350696.302083334
61	4279575	4559488.44791667	4462824.33333333	96664.1145833333	-279913.447916667
62	3782118	4141273.73958333	4462499.375	-321225.635416667	-359155.739583333
63	4098678	4479219.28958333	4462512.41666667	16706.8729166666	-380541.289583333
64	4065616	4271980.28125	4458085.16666667	-186104.885416667	-206364.28125
65	4413733	4283503.56458333	4434939	-151435.435416667	130229.435416668
66	4481214	4429269.44791667	4420870.66666667	8398.7812499998	51944.552083333
67	4345018	NA	NA	-256100.585416667	NA
68	4294488	NA	NA	-262130.460416666	NA
69	4361269	NA	NA	-314850.577083333	NA
70	4535031	NA	NA	268923.13125	NA
71	4318397	NA	NA	-202857.102083333	NA
72	6040168	NA	NA	1304011.78125	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/1k0c11243773022.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/1k0c11243773022.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/24pbj1243773022.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/24pbj1243773022.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/3gh7a1243773022.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/3gh7a1243773022.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/44am31243773022.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/31/t1243773106czpyvxcpmozqkj0/44am31243773022.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; 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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