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opdracht 9

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 06 Dec 2010 17:52:56 +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/06/t129165820404nl4lsngisr0ai.htm/, Retrieved Mon, 06 Dec 2010 18:56:44 +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/06/t129165820404nl4lsngisr0ai.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 «

108 106,6 122,2 115,8 115,6 124,5 121,7 118,7 113,7 113,4 115,1 143,9 101 103,4 121,5 111,9 117,4 124,3 122 119,7 115 112,2 115,3 142,6 104,1 105,3 124,4 113,9 124,8 131,8 125,6 125 119,7 116,1 120 148,1 109,2 109,4 135,1 114,9 129 138,5 125,6 130,4 120,3 126,2 127,6 150,9 114,6 118,6 131,4 124,5 136,8 136,8 136,6 131 125,8 129,4 124,8 157,1 116,6 114,2 128,4 127,3 133,5 137,2 137,7 131,2 127,7 133,9 124,3 160,6

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	108	NA	NA	-14.8594444444444	NA
2	106.6	NA	NA	-14.0169444444444	NA
3	122.2	NA	NA	3.74222222222223	NA
4	115.8	NA	NA	-6.20527777777777	NA
5	115.6	NA	NA	3.34722222222222	NA
6	124.5	NA	NA	8.55138888888887	NA
7	121.7	121.452222222222	117.975	3.47722222222220	0.247777777777799
8	118.7	119.552222222222	117.55	2.00222222222222	-0.852222222222224
9	113.7	113.214722222222	117.3875	-4.17277777777778	0.485277777777767
10	113.4	113.435555555556	117.195833333333	-3.76027777777778	-0.0355555555555469
11	115.1	114.203055555556	117.108333333333	-2.90527777777777	0.896944444444443
12	143.9	141.974722222222	117.175	24.7997222222222	1.92527777777779
13	101	102.319722222222	117.179166666667	-14.8594444444444	-1.31972222222221
14	103.4	103.216388888889	117.233333333333	-14.0169444444444	0.183611111111119
15	121.5	121.071388888889	117.329166666667	3.74222222222223	0.42861111111111
16	111.9	111.128055555556	117.333333333333	-6.20527777777777	0.771944444444458
17	117.4	120.638888888889	117.291666666667	3.34722222222222	-3.23888888888888
18	124.3	125.797222222222	117.245833333333	8.55138888888887	-1.49722222222223
19	122	120.798055555556	117.320833333333	3.47722222222220	1.20194444444445
20	119.7	119.531388888889	117.529166666667	2.00222222222222	0.168611111111119
21	115	113.556388888889	117.729166666667	-4.17277777777778	1.44361111111111
22	112.2	114.173055555556	117.933333333333	-3.76027777777778	-1.97305555555553
23	115.3	115.419722222222	118.325	-2.90527777777777	-0.119722222222222
24	142.6	143.745555555556	118.945833333333	24.7997222222222	-1.14555555555555
25	104.1	104.548888888889	119.408333333333	-14.8594444444444	-0.448888888888888
26	105.3	105.762222222222	119.779166666667	-14.0169444444444	-0.462222222222223
27	124.4	123.938055555556	120.195833333333	3.74222222222223	0.461944444444441
28	113.9	114.348888888889	120.554166666667	-6.20527777777777	-0.448888888888902
29	124.8	124.259722222222	120.9125	3.34722222222222	0.540277777777774
30	131.8	129.888888888889	121.3375	8.55138888888887	1.91111111111111
31	125.6	125.256388888889	121.779166666667	3.47722222222220	0.343611111111088
32	125	124.164722222222	122.1625	2.00222222222222	0.835277777777776
33	119.7	118.606388888889	122.779166666667	-4.17277777777778	1.09361111111112
34	116.1	119.506388888889	123.266666666667	-3.76027777777778	-3.4063888888889
35	120	120.578055555556	123.483333333333	-2.90527777777777	-0.578055555555565
36	148.1	148.737222222222	123.9375	24.7997222222222	-0.637222222222235
37	109.2	109.357222222222	124.216666666667	-14.8594444444444	-0.157222222222217
38	109.4	110.424722222222	124.441666666667	-14.0169444444444	-1.02472222222221
39	135.1	128.433888888889	124.691666666667	3.74222222222223	6.66611111111109
40	114.9	118.932222222222	125.1375	-6.20527777777777	-4.03222222222222
41	129	129.222222222222	125.875	3.34722222222222	-0.222222222222214
42	138.5	134.859722222222	126.308333333333	8.55138888888887	3.64027777777777
43	125.6	130.127222222222	126.65	3.47722222222220	-4.52722222222224
44	130.4	129.260555555556	127.258333333333	2.00222222222222	1.13944444444445
45	120.3	123.314722222222	127.4875	-4.17277777777778	-3.01472222222223
46	126.2	123.973055555556	127.733333333333	-3.76027777777778	2.22694444444444
47	127.6	125.553055555556	128.458333333333	-2.90527777777777	2.04694444444445
48	150.9	153.512222222222	128.7125	24.7997222222222	-2.61222222222223
49	114.6	114.240555555556	129.1	-14.8594444444444	0.359444444444449
50	118.6	115.566388888889	129.583333333333	-14.0169444444444	3.0336111111111
51	131.4	133.579722222222	129.8375	3.74222222222223	-2.17972222222221
52	124.5	123.994722222222	130.2	-6.20527777777777	0.505277777777792
53	136.8	133.563888888889	130.216666666667	3.34722222222222	3.23611111111111
54	136.8	138.909722222222	130.358333333333	8.55138888888887	-2.10972222222222
55	136.6	134.177222222222	130.7	3.47722222222220	2.42277777777778
56	131	132.602222222222	130.6	2.00222222222222	-1.60222222222225
57	125.8	126.118888888889	130.291666666667	-4.17277777777778	-0.318888888888864
58	129.4	126.523055555556	130.283333333333	-3.76027777777778	2.87694444444443
59	124.8	127.357222222222	130.2625	-2.90527777777777	-2.55722222222222
60	157.1	154.941388888889	130.141666666667	24.7997222222222	2.1586111111111
61	116.6	115.344722222222	130.204166666667	-14.8594444444444	1.25527777777779
62	114.2	116.241388888889	130.258333333333	-14.0169444444444	-2.04138888888889
63	128.4	134.088055555556	130.345833333333	3.74222222222223	-5.68805555555556
64	127.3	124.407222222222	130.6125	-6.20527777777777	2.89277777777775
65	133.5	134.126388888889	130.779166666667	3.34722222222222	-0.626388888888897
66	137.2	139.455555555556	130.904166666667	8.55138888888887	-2.25555555555556
67	137.7	NA	NA	3.47722222222220	NA
68	131.2	NA	NA	2.00222222222222	NA
69	127.7	NA	NA	-4.17277777777778	NA
70	133.9	NA	NA	-3.76027777777778	NA
71	124.3	NA	NA	-2.90527777777777	NA
72	160.6	NA	NA	24.7997222222222	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/1ajrg1291657972.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/1ajrg1291657972.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/2ajrg1291657972.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/2ajrg1291657972.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/3ls8j1291657972.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/3ls8j1291657972.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/4dk731291657972.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t129165820404nl4lsngisr0ai/4dk731291657972.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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