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Opgave 9 - oefening 2

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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: Wed, 08 Dec 2010 18:19:16 +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/08/t12918326827j9l5irj32qi7ff.htm/, Retrieved Wed, 08 Dec 2010 19:24:42 +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/08/t12918326827j9l5irj32qi7ff.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

Dataseries X:

» Textbox « » Textfile « » CSV «

105,23 105,22 105,13 105 105,01 105,01 105,01 105,01 105,57 106,05 106,09 106,2 106,19 106,2 106,09 106,23 106,23 106,22 106,22 106,61 106,95 107,74 107,8 107,8 107,2 107,56 107,72 108,14 108,16 108,16 108,16 108,1 108,95 110,49 110,72 110,82 110,82 110,75 110,71 110,86 110,84 110,84 110,84 110,92 111,46 112,46 113,04 113,15 113,15 113,21 113,37 113,47 113,71 113,71 113,71 113,8 115,46 117 117,94 118,08 118,08 118,47 118,49 118,45 118,54 118,55 118,55 118,55 119,04 121,37 122 122,14

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	105.23	NA	NA	0.285319444444454	NA
2	105.22	NA	NA	0.209652777777771	NA
3	105.13	NA	NA	0.0225694444444462	NA
4	105	NA	NA	-0.0633472222222333	NA
5	105.01	NA	NA	-0.257597222222224	NA
6	105.01	NA	NA	-0.523013888888897	NA
7	105.01	104.741569444444	105.4175	-0.675930555555558	0.268430555555554
8	105.01	104.704902777778	105.498333333333	-0.79343055555555	0.305097222222216
9	105.57	105.353986111111	105.579166666667	-0.225180555555553	0.216013888888895
10	106.05	106.291819444444	105.670416666667	0.621402777777778	-0.241819444444431
11	106.09	106.539069444444	105.7725	0.766569444444452	-0.449069444444447
12	106.2	106.506736111111	105.87375	0.632986111111115	-0.306736111111093
13	106.19	106.259902777778	105.974583333333	0.285319444444454	-0.0699027777777701
14	106.2	106.301319444444	106.091666666667	0.209652777777771	-0.101319444444428
15	106.09	106.238402777778	106.215833333333	0.0225694444444462	-0.148402777777747
16	106.23	106.280402777778	106.34375	-0.0633472222222333	-0.050402777777748
17	106.23	106.227819444444	106.485416666667	-0.257597222222224	0.00218055555558294
18	106.22	106.100319444444	106.623333333333	-0.523013888888897	0.119680555555576
19	106.22	106.056152777778	106.732083333333	-0.675930555555558	0.163847222222245
20	106.61	106.037402777778	106.830833333333	-0.79343055555555	0.572597222222242
21	106.95	106.730236111111	106.955416666667	-0.225180555555553	0.21976388888892
22	107.74	107.724319444444	107.102916666667	0.621402777777778	0.0156805555555763
23	107.8	108.029486111111	107.262916666667	0.766569444444452	-0.229486111111100
24	107.8	108.057152777778	107.424166666667	0.632986111111115	-0.257152777777748
25	107.2	107.871152777778	107.585833333333	0.285319444444454	-0.671152777777749
26	107.56	107.938402777778	107.72875	0.209652777777771	-0.378402777777765
27	107.72	107.896736111111	107.874166666667	0.0225694444444462	-0.176736111111097
28	108.14	108.008736111111	108.072083333333	-0.0633472222222333	0.131263888888896
29	108.16	108.050736111111	108.308333333333	-0.257597222222224	0.10926388888889
30	108.16	108.032819444444	108.555833333333	-0.523013888888897	0.127180555555569
31	108.16	108.156569444444	108.8325	-0.675930555555558	0.00343055555553917
32	108.1	108.322819444444	109.11625	-0.79343055555555	-0.222819444444454
33	108.95	109.148569444444	109.37375	-0.225180555555553	-0.198569444444459
34	110.49	110.233069444444	109.611666666667	0.621402777777778	0.256930555555556
35	110.72	110.603236111111	109.836666666667	0.766569444444452	0.116763888888897
36	110.82	110.692986111111	110.06	0.632986111111115	0.127013888888897
37	110.82	110.568652777778	110.283333333333	0.285319444444454	0.251347222222236
38	110.75	110.722152777778	110.5125	0.209652777777771	0.0278472222222348
39	110.71	110.757152777778	110.734583333333	0.0225694444444462	-0.0471527777777681
40	110.86	110.857902777778	110.92125	-0.0633472222222333	0.00209722222223263
41	110.84	110.842402777778	111.1	-0.257597222222224	-0.00240277777774622
42	110.84	110.770736111111	111.29375	-0.523013888888897	0.0692638888889121
43	110.84	110.811986111111	111.487916666667	-0.675930555555558	0.028013888888907
44	110.92	110.894069444444	111.6875	-0.79343055555555	0.0259305555555613
45	111.46	111.675652777778	111.900833333333	-0.225180555555553	-0.215652777777777
46	112.46	112.741819444444	112.120416666667	0.621402777777778	-0.281819444444437
47	113.04	113.115319444444	112.34875	0.766569444444452	-0.075319444444446
48	113.15	113.220902777778	112.587916666667	0.632986111111115	-0.0709027777777607
49	113.15	113.112402777778	112.827083333333	0.285319444444454	0.0375972222222316
50	113.21	113.276319444444	113.066666666667	0.209652777777771	-0.0663194444444599
51	113.37	113.375902777778	113.353333333333	0.0225694444444462	-0.00590277777776294
52	113.47	113.645819444444	113.709166666667	-0.0633472222222333	-0.175819444444457
53	113.71	113.844902777778	114.1025	-0.257597222222224	-0.134902777777782
54	113.71	113.989069444444	114.512083333333	-0.523013888888897	-0.279069444444460
55	113.71	114.246986111111	114.922916666667	-0.675930555555558	-0.536986111111119
56	113.8	114.554069444444	115.3475	-0.79343055555555	-0.75406944444444
57	115.46	115.554819444444	115.78	-0.225180555555553	-0.0948194444444255
58	117	116.822236111111	116.200833333333	0.621402777777778	0.177763888888904
59	117.94	117.376152777778	116.609583333333	0.766569444444452	0.563847222222222
60	118.08	117.645486111111	117.0125	0.632986111111115	0.434513888888887
61	118.08	117.701152777778	117.415833333333	0.285319444444454	0.378847222222205
62	118.47	118.025069444444	117.815416666667	0.209652777777771	0.444930555555544
63	118.49	118.185069444444	118.1625	0.0225694444444462	0.304930555555543
64	118.45	118.430402777778	118.49375	-0.0633472222222333	0.0195972222222309
65	118.54	118.587402777778	118.845	-0.257597222222224	-0.0474027777777621
66	118.55	118.660319444444	119.183333333333	-0.523013888888897	-0.110319444444443
67	118.55	NA	NA	-0.675930555555558	NA
68	118.55	NA	NA	-0.79343055555555	NA
69	119.04	NA	NA	-0.225180555555553	NA
70	121.37	NA	NA	0.621402777777778	NA
71	122	NA	NA	0.766569444444452	NA
72	122.14	NA	NA	0.632986111111115	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/1ctaj1291832352.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/1ctaj1291832352.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/2ctaj1291832352.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/2ctaj1291832352.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/3nl941291832352.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/3nl941291832352.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/4nl941291832352.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/08/t12918326827j9l5irj32qi7ff/4nl941291832352.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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