Home » date » 2009 » Jun » 01 »

decompositie - aantal nietwerkenden werkzoekenden - Lize Geunes

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 01 Jun 2009 10:05:26 -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/Jun/01/t1243872366c5s1n2wmeenk4wt.htm/, Retrieved Mon, 01 Jun 2009 18:06:10 +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/Jun/01/t1243872366c5s1n2wmeenk4wt.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 «

220206 220115 218444 214912 210705 209673 237041 242081 241878 242621 238545 240337 244752 244576 241572 240541 236089 236997 264579 270349 269645 267037 258113 262813 267413 267366 264777 258863 254844 254868 277267 285351 286602 283042 276687 277915 277128 277103 275037 270150 267140 264993 287259 291186 292300 288186 281477 282656 280190 280408 276836 275216 274352 271311 289802 290726 292300 278506 269826 265861 269034 264176 255198 253353 246057 235372 258556 260993 254663 250643 243422 247105 248541 245039 237080 237085 225554 226839 247934 248333 246969 245098 246263 255765 264319

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	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	220206	NA	NA	1736.77777777775	NA
2	220115	NA	NA	219.381944444439	NA
3	218444	NA	NA	-4554.05555555555	NA
4	214912	NA	NA	-7155.27777777779	NA
5	210705	NA	NA	-12421.4097222222	NA
6	209673	NA	NA	-14858.1458333333	NA
7	237041	236470.916666667	229069.25	7401.66666666667	570.083333333343
8	242081	242546.486111111	231111.208333333	11435.2777777778	-465.486111111095
9	241878	244541.180555556	233094.083333333	11447.0972222222	-2663.18055555553
10	242621	241580.9375	235125.625	6455.31250000001	1040.06250000003
11	238545	237274.048611111	237251.166666667	22.881944444444	1270.95138888893
12	240337	239717.826388889	239447.333333333	270.493055555573	619.173611111153
13	244752	243470.027777778	241733.25	1736.77777777775	1281.97222222225
14	244576	244277.881944444	244058.5	219.381944444439	298.118055555562
15	241572	241839.236111111	246393.291666667	-4554.05555555555	-267.236111111095
16	240541	241412.305555556	248567.583333333	-7155.27777777779	-871.305555555562
17	236089	237978.840277778	250400.25	-12421.4097222222	-1889.84027777781
18	236997	237293.9375	252152.083333333	-14858.1458333333	-296.9375
19	264579	261434.458333333	254032.791666667	7401.66666666667	3144.54166666666
20	270349	267361.861111111	255926.583333333	11435.2777777778	2987.13888888888
21	269645	269290.138888889	257843.041666667	11447.0972222222	354.861111111095
22	267037	266028.645833333	259573.333333333	6455.31250000001	1008.35416666666
23	258113	261141.090277778	261118.208333333	22.881944444444	-3028.09027777775
24	262813	262914.784722222	262644.291666667	270.493055555573	-101.784722222190
25	267413	265654.361111111	263917.583333333	1736.77777777775	1758.63888888888
26	267366	265290.715277778	265071.333333333	219.381944444439	2075.28472222225
27	264777	261848.902777778	266402.958333333	-4554.05555555555	2928.09722222225
28	258863	260621.097222222	267776.375	-7155.27777777779	-1758.09722222219
29	254844	256795.756944444	269217.166666667	-12421.4097222222	-1951.75694444438
30	254868	255762.1875	270620.333333333	-14858.1458333333	-894.1875
31	277267	279056.041666667	271654.375	7401.66666666667	-1789.04166666669
32	285351	283900.152777778	272464.875	11435.2777777778	1450.84722222225
33	286602	284745.180555556	273298.083333333	11447.0972222222	1856.81944444444
34	283042	280651.1875	274195.875	6455.31250000001	2390.81250000006
35	276687	275201.381944444	275178.5	22.881944444444	1485.61805555556
36	277915	276383.201388889	276112.708333333	270.493055555573	1531.79861111112
37	277128	278687.694444444	276950.916666667	1736.77777777775	-1559.69444444444
38	277103	277829.756944444	277610.375	219.381944444439	-726.756944444438
39	275037	273536.861111111	278090.916666667	-4554.05555555555	1500.13888888893
40	270150	271387.388888889	278542.666666667	-7155.27777777779	-1237.38888888888
41	267140	266535.173611111	278956.583333333	-12421.4097222222	604.826388888934
42	264993	264495.5625	279353.708333333	-14858.1458333333	497.4375
43	287259	287080.5	279678.833333333	7401.66666666667	178.5
44	291186	291379.402777778	279944.125	11435.2777777778	-193.402777777694
45	292300	291603.888888889	280156.791666667	11447.0972222222	696.111111111124
46	288186	286898.145833333	280442.833333333	6455.31250000001	1287.85416666669
47	281477	280977.298611111	280954.416666667	22.881944444444	499.701388888934
48	282656	281788.659722222	281518.166666667	270.493055555573	867.34027777781
49	280190	283624.152777778	281887.375	1736.77777777775	-3434.15277777775
50	280408	282193.548611111	281974.166666667	219.381944444439	-1785.54861111107
51	276836	277400.944444444	281955	-4554.05555555555	-564.94444444438
52	275216	274396.388888889	281551.666666667	-7155.27777777779	819.611111111182
53	274352	268241.465277778	280662.875	-12421.4097222222	6110.5347222223
54	271311	264619.479166667	279477.625	-14858.1458333333	6691.52083333337
55	289802	285714.666666667	278313	7401.66666666667	4087.33333333337
56	290726	288607.111111111	277171.833333333	11435.2777777778	2118.88888888893
57	292300	287041.013888889	275593.916666667	11447.0972222222	5258.98611111112
58	278506	280236.6875	273781.375	6455.31250000001	-1730.68749999994
59	269826	271714.340277778	271691.458333333	22.881944444444	-1888.34027777775
60	265861	269285.534722222	269015.041666667	270.493055555573	-3424.53472222219
61	269034	267952.444444444	266215.666666667	1736.77777777775	1081.55555555556
62	264176	263894.256944444	263674.875	219.381944444439	281.743055555562
63	255198	256313.736111111	260867.791666667	-4554.05555555555	-1115.73611111109
64	253353	250983.347222222	258138.625	-7155.27777777779	2369.65277777781
65	246057	243456.090277778	255877.5	-12421.4097222222	2600.90972222225
66	235372	239137.6875	253995.833333333	-14858.1458333333	-3765.68749999997
67	258556	259762.125	252360.458333333	7401.66666666667	-1206.125
68	260993	262144.486111111	250709.208333333	11435.2777777778	-1151.48611111112
69	254663	260604.013888889	249156.916666667	11447.0972222222	-5941.01388888888
70	250643	254179.479166667	247724.166666667	6455.31250000001	-3536.47916666666
71	243422	246214.923611111	246192.041666667	22.881944444444	-2792.92361111109
72	247105	245252.701388889	244982.208333333	270.493055555573	1852.29861111115
73	248541	245920.861111111	244184.083333333	1736.77777777775	2620.13888888896
74	245039	243433.381944444	243214	219.381944444439	1605.61805555559
75	237080	237811.861111111	242365.916666667	-4554.05555555555	-731.861111111095
76	237085	234659.013888889	241814.291666667	-7155.27777777779	2425.98611111112
77	225554	229280.215277778	241701.625	-12421.4097222222	-3726.21527777778
78	226839	227322.6875	242180.833333333	-14858.1458333333	-483.687499999971
79	247934	250600.75	243199.083333333	7401.66666666667	-2666.74999999997
80	248333	NA	NA	11435.2777777778	NA
81	246969	NA	NA	11447.0972222222	NA
82	245098	NA	NA	6455.31250000001	NA
83	246263	NA	NA	22.881944444444	NA
84	255765	NA	NA	270.493055555573	NA
85	264319	NA	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/19jxj1243872324.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/19jxj1243872324.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/2zmc61243872324.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/2zmc61243872324.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/3oqs41243872324.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/3oqs41243872324.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/455071243872324.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243872366c5s1n2wmeenk4wt/455071243872324.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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