Home » date » 2009 » Jun » 02 »

Opgave 9 Oefening 2 - Wisselkoers Euro in Dollar - Anthony Van Trier

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 02 Jun 2009 11:47:33 -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/02/t1243964918ko1ljtl2i9wpvqc.htm/, Retrieved Tue, 02 Jun 2009 19:48:43 +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/02/t1243964918ko1ljtl2i9wpvqc.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 «

1,1608 1,1208 1,0883 1,0704 1,0628 1,0378 1,0353 1,0604 1,0501 1,0706 1,0338 1,0110 1,0137 0,9834 0,9643 0,9470 0,9060 0,9492 0,9397 0,9041 0,8721 0,8552 0,8564 0,8973 0,9383 0,9217 0,9095 0,8920 0,8742 0,8532 0,8607 0,9005 0,9111 0,9059 0,8883 0,8924 0,8833 0,8700 0,8758 0,8858 0,9170 0,9554 0,9922 0,9778 0,9808 0,9811 1,0014 1,0183 1,0622 1,0773 1,0807 1,0848 1,1582 1,1663 1,1372 1,1139 1,1222 1,1692 1,1702 1,2286 1,2613 1,2646 1,2262 1,1985 1,2007 1,2138 1,2266 1,2176 1,2218 1,2490 1,2991 1,3408 1,3119 1,3014 1,3201 1,2938 1,2694 1,2165 1,2037 1,2292 1,2256 1,2015 1,1786 1,1856 1,2103 1,1938 1,2020 1,2271 1,2770 1,2650 1,2684 1,2811 1,2727 1,2611 1,2881 1,3213 1,2999 1,3074 1,3242 1,3516 1,3511 1,3419 1,3716 1,3622 1,3896 1,4227 1,4684 1,4570 1,4718 1,4748 1,5527 1,5750 1,5557 1,5553 1,5770 1,4975 1,4369 1,3322 1,2732 1,3449 1,3239

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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.1608	NA	NA	0.0128629629629630	NA
2	1.1208	NA	NA	0.00185370370370362	NA
3	1.0883	NA	NA	0.00482824074074078	NA
4	1.0704	NA	NA	0.00183749999999997	NA
5	1.0628	NA	NA	0.00548472222222228	NA
6	1.0378	NA	NA	0.00364166666666666	NA
7	1.0353	1.06809444444444	1.0607125	0.00738194444444443	-0.0327944444444443
8	1.0604	1.03498981481481	1.04885833333333	-0.0138685185185185	0.0254101851851853
9	1.0501	1.02426064814815	1.03796666666667	-0.0137060185185185	0.0258393518518518
10	1.0706	1.01391990740741	1.02765833333333	-0.0137384259259259	0.0566800925925925
11	1.0338	1.01139722222222	1.01598333333333	-0.00458611111111112	0.022402777777778
12	1.011	1.01376666666667	1.00575833333333	0.00800833333333332	-0.00276666666666681
13	1.0137	1.01094629629630	0.998083333333333	0.0128629629629630	0.00275370370370376
14	0.9834	0.989441203703704	0.9875875	0.00185370370370362	-0.00604120370370353
15	0.9643	0.978486574074074	0.973658333333333	0.00482824074074078	-0.0141865740740739
16	0.947	0.959104166666666	0.957266666666666	0.00183749999999997	-0.0121041666666665
17	0.906	0.946384722222222	0.9409	0.00548472222222228	-0.0403847222222221
18	0.9492	0.9324125	0.928770833333333	0.00364166666666666	0.0167875000000003
19	0.9397	0.928273611111111	0.920891666666667	0.00738194444444443	0.0114263888888890
20	0.9041	0.901310648148148	0.915179166666666	-0.0138685185185185	0.00278935185185203
21	0.8721	0.896618981481481	0.910325	-0.0137060185185185	-0.0245189814814814
22	0.8552	0.892011574074074	0.90575	-0.0137384259259259	-0.0368115740740741
23	0.8564	0.897547222222222	0.902133333333333	-0.00458611111111112	-0.0411472222222221
24	0.8973	0.904816666666667	0.896808333333333	0.00800833333333332	-0.00751666666666662
25	0.9383	0.90237962962963	0.889516666666667	0.0128629629629630	0.0359203703703704
26	0.9217	0.887928703703704	0.886075	0.00185370370370362	0.0337712962962964
27	0.9095	0.892378240740741	0.88755	0.00482824074074078	0.0171217592592592
28	0.892	0.893125	0.8912875	0.00183749999999997	-0.00112500000000004
29	0.8742	0.900213888888889	0.894729166666667	0.00548472222222228	-0.026013888888889
30	0.8532	0.899495833333333	0.895854166666667	0.00364166666666666	-0.0462958333333334
31	0.8607	0.900740277777778	0.893358333333333	0.00738194444444443	-0.0400402777777777
32	0.9005	0.875043981481482	0.8889125	-0.0138685185185185	0.0254560185185184
33	0.9111	0.871648148148148	0.885354166666667	-0.0137060185185185	0.0394518518518518
34	0.9059	0.869953240740741	0.883691666666667	-0.0137384259259259	0.0359467592592592
35	0.8883	0.880630555555556	0.885216666666667	-0.00458611111111112	0.0076694444444444
36	0.8924	0.899266666666667	0.891258333333333	0.00800833333333332	-0.00686666666666669
37	0.8833	0.913858796296296	0.900995833333333	0.0128629629629630	-0.0305587962962963
38	0.87	0.911549537037037	0.909695833333333	0.00185370370370362	-0.041549537037037
39	0.8758	0.920649074074074	0.915820833333333	0.00482824074074078	-0.044849074074074
40	0.8858	0.923695833333333	0.921858333333333	0.00183749999999997	-0.0378958333333331
41	0.917	0.935188888888889	0.929704166666667	0.00548472222222228	-0.0181888888888889
42	0.9554	0.943304166666666	0.9396625	0.00364166666666666	0.0120958333333335
43	0.9922	0.959744444444444	0.9523625	0.00738194444444443	0.0324555555555557
44	0.9778	0.954585648148148	0.968454166666667	-0.0138685185185185	0.0232143518518519
45	0.9808	0.971923148148148	0.985629166666667	-0.0137060185185185	0.00887685185185183
46	0.9811	0.988719907407408	1.00245833333333	-0.0137384259259259	-0.00761990740740759
47	1.0014	1.01621388888889	1.0208	-0.00458611111111112	-0.0148138888888887
48	1.0183	1.04764583333333	1.0396375	0.00800833333333332	-0.0293458333333334
49	1.0622	1.06732962962963	1.05446666666667	0.0128629629629630	-0.00512962962962971
50	1.0773	1.06803287037037	1.06617916666667	0.00185370370370362	0.00926712962962939
51	1.0807	1.08256990740741	1.07774166666667	0.00482824074074078	-0.00186990740740733
52	1.0848	1.09330833333333	1.09147083333333	0.00183749999999997	-0.00850833333333334
53	1.1582	1.11182638888889	1.10634166666667	0.00548472222222228	0.0463736111111108
54	1.1663	1.12577916666667	1.1221375	0.00364166666666666	0.0405208333333331
55	1.1372	1.14657777777778	1.13919583333333	0.00738194444444443	-0.0093777777777777
56	1.1139	1.14142731481481	1.15529583333333	-0.0138685185185185	-0.0275273148148150
57	1.1222	1.15545648148148	1.1691625	-0.0137060185185185	-0.0332564814814815
58	1.1692	1.16622407407407	1.1799625	-0.0137384259259259	0.00297592592592610
59	1.1702	1.18188472222222	1.18647083333333	-0.00458611111111112	-0.0116847222222223
60	1.2286	1.19822916666667	1.19022083333333	0.00800833333333332	0.030370833333333
61	1.2613	1.20878796296296	1.195925	0.0128629629629630	0.0525120370370371
62	1.2646	1.20582453703704	1.20397083333333	0.00185370370370362	0.0587754629629631
63	1.2262	1.21726990740741	1.21244166666667	0.00482824074074078	0.00893009259259281
64	1.1985	1.22175416666667	1.21991666666667	0.00183749999999997	-0.0232541666666668
65	1.2007	1.23409722222222	1.2286125	0.00548472222222228	-0.0333972222222221
66	1.2138	1.2423	1.23865833333333	0.00364166666666666	-0.0285000000000002
67	1.2266	1.25282361111111	1.24544166666667	0.00738194444444443	-0.0262236111111112
68	1.2176	1.23521481481481	1.24908333333333	-0.0138685185185185	-0.0176148148148145
69	1.2218	1.24082314814815	1.25452916666667	-0.0137060185185185	-0.0190231481481482
70	1.249	1.24867407407407	1.2624125	-0.0137384259259259	0.000325925925925841
71	1.2991	1.26465972222222	1.26924583333333	-0.00458611111111112	0.0344402777777779
72	1.3408	1.28022916666667	1.27222083333333	0.00800833333333332	0.0605708333333335
73	1.3119	1.28424212962963	1.27137916666667	0.0128629629629630	0.0276578703703705
74	1.3014	1.27276203703704	1.27090833333333	0.00185370370370362	0.0286379629629629
75	1.3201	1.27637824074074	1.27155	0.00482824074074078	0.0437217592592594
76	1.2938	1.27156666666667	1.26972916666667	0.00183749999999997	0.0222333333333333
77	1.2694	1.26821388888889	1.26272916666667	0.00548472222222228	0.00118611111111133
78	1.2165	1.25488333333333	1.25124166666667	0.00364166666666666	-0.0383833333333334
79	1.2037	1.24792361111111	1.24054166666667	0.00738194444444443	-0.0442236111111112
80	1.2292	1.21795648148148	1.231825	-0.0138685185185185	0.0112435185185187
81	1.2256	1.20871481481482	1.22242083333333	-0.0137060185185185	0.016885185185185
82	1.2015	1.20098240740741	1.21472083333333	-0.0137384259259259	0.000517592592592653
83	1.1786	1.20767222222222	1.21225833333333	-0.00458611111111112	-0.0290722222222219
84	1.1856	1.22260416666667	1.21459583333333	0.00800833333333332	-0.0370041666666665
85	1.2103	1.23217546296296	1.2193125	0.0128629629629630	-0.0218754629629634
86	1.1938	1.22602453703704	1.22417083333333	0.00185370370370362	-0.0322245370370371
87	1.202	1.23312407407407	1.22829583333333	0.00482824074074078	-0.0311240740740739
88	1.2271	1.23457916666667	1.23274166666667	0.00183749999999997	-0.00747916666666626
89	1.277	1.24527222222222	1.2397875	0.00548472222222228	0.0317277777777776
90	1.265	1.25364583333333	1.25000416666667	0.00364166666666666	0.0113541666666663
91	1.2684	1.26677361111111	1.25939166666667	0.00738194444444443	0.00162638888888877
92	1.2811	1.25398981481481	1.26785833333333	-0.0138685185185185	0.0271101851851852
93	1.2727	1.26397731481481	1.27768333333333	-0.0137060185185185	0.00872268518518537
94	1.2611	1.27422407407407	1.2879625	-0.0137384259259259	-0.0131240740740739
95	1.2881	1.29165138888889	1.2962375	-0.00458611111111112	-0.00355138888888873
96	1.3213	1.3105375	1.30252916666667	0.00800833333333332	0.0107625
97	1.2999	1.32289629629630	1.31003333333333	0.0128629629629630	-0.0229962962962964
98	1.3074	1.31956620370370	1.3177125	0.00185370370370362	-0.0121662037037038
99	1.3242	1.33079074074074	1.3259625	0.00482824074074078	-0.00659074074074062
100	1.3516	1.33940416666667	1.33756666666667	0.00183749999999997	0.0121958333333334
101	1.3511	1.35729722222222	1.3518125	0.00548472222222228	-0.00619722222222197
102	1.3419	1.36862083333333	1.36497916666667	0.00364166666666666	-0.0267208333333333
103	1.3716	1.38517777777778	1.37779583333333	0.00738194444444443	-0.0135777777777779
104	1.3622	1.37806481481481	1.39193333333333	-0.0138685185185185	-0.0158648148148146
105	1.3896	1.39472314814815	1.40842916666667	-0.0137060185185185	-0.0051231481481484
106	1.4227	1.41351990740741	1.42725833333333	-0.0137384259259259	0.00918009259259267
107	1.4684	1.44050555555556	1.44509166666667	-0.00458611111111112	0.0278944444444442
108	1.457	1.47051666666667	1.46250833333333	0.00800833333333332	-0.0135166666666668
109	1.4718	1.49282129629630	1.47995833333333	0.0128629629629630	-0.0210212962962963
110	1.4748	1.49600787037037	1.49415416666667	0.00185370370370362	-0.0212078703703702
111	1.5527	1.50659074074074	1.5017625	0.00482824074074078	0.0461092592592591
112	1.575	1.5018	1.4999625	0.00183749999999997	0.0732
113	1.5557	1.49354305555556	1.48805833333333	0.00548472222222228	0.0621569444444445
114	1.5553	1.47889583333333	1.47525416666667	0.00364166666666666	0.0764041666666668
115	1.577	1.47180277777778	1.46442083333333	0.00738194444444443	0.105197222222222
116	1.4975	NA	NA	-0.0138685185185185	NA
117	1.4369	NA	NA	-0.0137060185185185	NA
118	1.3322	NA	NA	-0.0137384259259259	NA
119	1.2732	NA	NA	-0.00458611111111112	NA
120	1.3449	NA	NA	0.00800833333333332	NA
121	1.3239	NA	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/1d8z71243964850.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/1d8z71243964850.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/2yhc41243964850.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/2yhc41243964850.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/3d2ub1243964850.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/3d2ub1243964850.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/4awxd1243964850.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/02/t1243964918ko1ljtl2i9wpvqc/4awxd1243964850.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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FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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