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werkloosheid

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 13 Jan 2011 08:41:05 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1.htm/, Retrieved Thu, 13 Jan 2011 09:40:38 +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/2011/Jan/13/t1294908038ilb3x2s3gqemxf1.htm/},
    year = {2011},
}
@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 = {2011},
    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

Dataseries X:

» Textbox « » Textfile « » CSV «

8,6 8,5 8,4 8,0 7,9 8,1 8,6 8,8 8,8 8,6 8,3 8,3 8,3 8,4 8,4 8,5 8,6 8,6 8,6 8,6 8,6 8,5 8,4 8,4 8,4 8,5 8,5 8,6 8,6 8,4 8,2 8,0 8,0 8,0 8,0 7,9 7,9 7,8 7,9 8,0 7,9 7,4 7,2 7,0 7,0 7,1 7,2 7,2 7,0 6,9 6,8 6,8 6,8 6,9 7,2 7,3 7,2 7,1 7,1 7,3 7,5 7,6 7,7 7,7 7,7 7,8 8,0 8,1 8,1 8,0 8,1 8,2 8,3 8,4 8,6 8,6 8,7 8,8 8,9

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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.6	NA	NA	-0.0374305555555549	NA
2	8.5	NA	NA	-0.00659722222222189	NA
3	8.4	NA	NA	0.0250694444444449	NA
4	8	NA	NA	0.0959027777777776	NA
5	7.9	NA	NA	0.102569444444444	NA
6	8.1	NA	NA	0.00506944444444411	NA
7	8.6	8.42173611111111	8.39583333333333	0.0259027777777773	0.178263888888891
8	8.8	8.36506944444444	8.37916666666667	-0.0140972222222225	0.434930555555557
9	8.8	8.33923611111111	8.375	-0.0357638888888889	0.46076388888889
10	8.6	8.31756944444444	8.39583333333333	-0.0782638888888891	0.282430555555555
11	8.3	8.38590277777778	8.44583333333333	-0.0599305555555554	-0.085902777777779
12	8.3	8.47340277777778	8.49583333333333	-0.0224305555555557	-0.173402777777776
13	8.3	8.47923611111111	8.51666666666666	-0.0374305555555549	-0.179236111111109
14	8.4	8.50173611111111	8.50833333333333	-0.00659722222222189	-0.101736111111110
15	8.4	8.51673611111111	8.49166666666667	0.0250694444444449	-0.116736111111109
16	8.5	8.57506944444444	8.47916666666667	0.0959027777777776	-0.0750694444444431
17	8.6	8.58173611111111	8.47916666666667	0.102569444444444	0.0182638888888889
18	8.6	8.49256944444445	8.4875	0.00506944444444411	0.107430555555554
19	8.6	8.52173611111111	8.49583333333333	0.0259027777777773	0.0782638888888894
20	8.6	8.49006944444444	8.50416666666667	-0.0140972222222225	0.109930555555556
21	8.6	8.47673611111111	8.5125	-0.0357638888888889	0.123263888888889
22	8.5	8.44256944444444	8.52083333333333	-0.0782638888888891	0.0574305555555572
23	8.4	8.46506944444444	8.525	-0.0599305555555554	-0.0650694444444433
24	8.4	8.49423611111111	8.51666666666667	-0.0224305555555557	-0.09423611111111
25	8.4	8.45423611111111	8.49166666666667	-0.0374305555555549	-0.0542361111111109
26	8.5	8.44340277777778	8.45	-0.00659722222222189	0.0565972222222246
27	8.5	8.42506944444444	8.4	0.0250694444444449	0.0749305555555573
28	8.6	8.45006944444444	8.35416666666667	0.0959027777777776	0.149930555555557
29	8.6	8.41923611111111	8.31666666666667	0.102569444444444	0.180763888888889
30	8.4	8.28423611111111	8.27916666666667	0.00506944444444411	0.115763888888889
31	8.2	8.26340277777778	8.2375	0.0259027777777773	-0.0634027777777764
32	8	8.17340277777778	8.1875	-0.0140972222222225	-0.173402777777778
33	8	8.09756944444444	8.13333333333333	-0.0357638888888889	-0.097569444444444
34	8	8.00506944444444	8.08333333333333	-0.0782638888888891	-0.00506944444444457
35	8	7.96923611111111	8.02916666666667	-0.0599305555555554	0.0307638888888881
36	7.9	7.93590277777778	7.95833333333333	-0.0224305555555557	-0.0359027777777774
37	7.9	7.83756944444445	7.875	-0.0374305555555549	0.0624305555555544
38	7.8	7.78506944444444	7.79166666666667	-0.00659722222222189	0.0149305555555559
39	7.9	7.73340277777778	7.70833333333333	0.0250694444444449	0.166597222222222
40	8	7.72506944444444	7.62916666666667	0.0959027777777776	0.274930555555556
41	7.9	7.66090277777778	7.55833333333333	0.102569444444444	0.239097222222223
42	7.4	7.50090277777778	7.49583333333333	0.00506944444444411	-0.100902777777776
43	7.2	7.45506944444444	7.42916666666667	0.0259027777777773	-0.255069444444444
44	7	7.34006944444444	7.35416666666667	-0.0140972222222225	-0.340069444444444
45	7	7.23506944444444	7.27083333333333	-0.0357638888888889	-0.235069444444443
46	7.1	7.09673611111111	7.175	-0.0782638888888891	0.00326388888889095
47	7.2	7.01923611111111	7.07916666666666	-0.0599305555555554	0.180763888888891
48	7.2	6.99006944444444	7.0125	-0.0224305555555557	0.209930555555557
49	7	6.95423611111111	6.99166666666667	-0.0374305555555549	0.0457638888888896
50	6.9	6.99756944444444	7.00416666666667	-0.00659722222222189	-0.097569444444443
51	6.8	7.05006944444444	7.025	0.0250694444444449	-0.250069444444444
52	6.8	7.12923611111111	7.03333333333333	0.0959027777777776	-0.329236111111110
53	6.8	7.13173611111111	7.02916666666667	0.102569444444444	-0.33173611111111
54	6.9	7.03423611111111	7.02916666666667	0.00506944444444411	-0.134236111111109
55	7.2	7.08006944444444	7.05416666666667	0.0259027777777773	0.119930555555556
56	7.3	7.09006944444444	7.10416666666667	-0.0140972222222225	0.209930555555556
57	7.2	7.13506944444444	7.17083333333333	-0.0357638888888889	0.0649305555555566
58	7.1	7.16756944444444	7.24583333333333	-0.0782638888888891	-0.0675694444444437
59	7.1	7.26090277777778	7.32083333333333	-0.0599305555555554	-0.160902777777777
60	7.3	7.37340277777778	7.39583333333333	-0.0224305555555557	-0.0734027777777762
61	7.5	7.42923611111111	7.46666666666667	-0.0374305555555549	0.070763888888889
62	7.6	7.52673611111111	7.53333333333333	-0.00659722222222189	0.0732638888888886
63	7.7	7.62923611111111	7.60416666666667	0.0250694444444449	0.070763888888889
64	7.7	7.77506944444445	7.67916666666667	0.0959027777777776	-0.0750694444444449
65	7.7	7.86090277777778	7.75833333333333	0.102569444444444	-0.160902777777777
66	7.8	7.84256944444444	7.8375	0.00506944444444411	-0.0425694444444433
67	8	7.93423611111111	7.90833333333333	0.0259027777777773	0.0657638888888892
68	8.1	7.96090277777778	7.975	-0.0140972222222225	0.139097222222223
69	8.1	8.01006944444444	8.04583333333333	-0.0357638888888889	0.089930555555556
70	8	8.04256944444444	8.12083333333333	-0.0782638888888891	-0.0425694444444442
71	8.1	8.14006944444444	8.2	-0.0599305555555554	-0.0400694444444447
72	8.2	8.26090277777778	8.28333333333333	-0.0224305555555557	-0.0609027777777786
73	8.3	NA	8.3625	NA	NA
74	8.4	NA	NA	NA	NA
75	8.6	NA	NA	NA	NA
76	8.6	NA	NA	NA	NA
77	8.7	NA	NA	NA	NA
78	8.8	NA	NA	NA	NA
79	8.9	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/1nyj41294908061.png (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/1nyj41294908061.ps (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/2skk31294908061.png (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/2skk31294908061.ps (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/362rh1294908061.png (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/362rh1294908061.ps (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/4giqw1294908061.png (open in new window)

http://www.freestatistics.org/blog/date/2011/Jan/13/t1294908038ilb3x2s3gqemxf1/4giqw1294908061.ps (open in new window)

Parameters (Session):

par1 = 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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