Home » date » 2010 » May » 27 »

Decompositie wisselkoers dollar/euro

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 27 May 2010 15:51:13 +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/May/27/t1274975503fbw5sthvuxgoriz.htm/, Retrieved Thu, 27 May 2010 17:51:45 +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/2010/May/27/t1274975503fbw5sthvuxgoriz.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

1.1591 1.1203 1.0886 1.0701 1.0630 1.0377 1.0370 1.0605 1.0497 1.0706 1.0328 1.0110 1.0131 0.9834 0.9643 0.9449 0.9059 0.9505 0.9386 0.9045 0.8695 0.8525 0.8552 0.8983 0.9376 0.9205 0.9083 0.8925 0.8753 0.8530 0.8615 0.9014 0.9114 0.9050 0.8883 0.8912 0.8832 0.8707 0.8766 0.8860 0.9170 0.9561 0.9935 0.9781 0.9806 0.9812 1.0013 1.0194 1.0622 1.0785 1.0797 1.0862 1.1556 1.1674 1.1365 1.1155 1.1267 1.1714 1.1710 1.2298 1.2638 1.2640 1.2261 1.1989 1.2000 1.2146 1.2266 1.2191 1.2224 1.2507 1.2997 1.3406 1.3123 1.3013 1.3185 1.2943 1.2697 1.2155 1.2041 1.2295 1.2234 1.2022 1.1789 1.1861 1.2126 1.1940 1.2028 1.2273 1.2767 1.2661 1.2681 1.2810 1.2722 1.2617 1.2888 1.3205 1.2993 1.3080 1.3246 1.3513 1.3518 1.3421 1.3726 1.3626 1.3910 1.4233 1.4683 1.4559 1.4728 1.4759 1.5520 1.5754 1.5554 1.5562 1.5759 1.4955 1.4342 1.3266 1.2744 1.3511 1.3244 1.2797 1.3050 1.3199 1.3646 1.4014 1.4092 1.4266 etc...

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.1591	NA	NA	1.01126246991022	NA
2	1.1203	NA	NA	0.999236931664656	NA
3	1.0886	NA	NA	1.00123179446176	NA
4	1.0701	NA	NA	0.998851866664662	NA
5	1.063	NA	NA	1.00363953527856	NA
6	1.0377	NA	NA	1.00603022503051	NA
7	1.037	1.06608269146686	1.06061666666667	1.00515362898961	0.97272004160686
8	1.0605	1.04864657522087	1.04882916666667	0.999825909259966	1.01130354597938
9	1.0497	1.03059518515307	1.03794583333333	0.992918081132754	1.01853765195312
10	1.0706	1.0163090695351	1.02755	0.989060454026665	1.05341970478502
11	1.0328	1.00282908279445	1.0157875	0.987242984181682	1.02988636620114
12	1.011	1.01118555721858	1.00560833333333	1.00554611939895	0.999816495382815
13	1.0131	1.00911353716166	0.997875	1.01126246991022	1.00395046017275
14	0.9834	0.986521641709224	0.987275	0.999236931664656	0.996835708840796
15	0.9643	0.97446553115648	0.973266666666667	1.00123179446176	0.989568095708407
16	0.9449	0.955572447658638	0.956670833333333	0.998851866664662	0.988831356863848
17	0.9059	0.943605163743319	0.940183333333333	1.00363953527856	0.960041376211062
18	0.9505	0.933684076473002	0.9280875	1.00603022503051	1.01801029272184
19	0.9386	0.924988438937567	0.920245833333333	1.00515362898961	1.01471538506802
20	0.9045	0.914319964311796	0.914479166666667	0.999825909259966	0.989259816371627
21	0.8695	0.903083817742268	0.909525	0.992918081132754	0.962812070062081
22	0.8525	0.895107953064582	0.905008333333333	0.989060454026665	0.952399090055333
23	0.8552	0.890048912388996	0.90155	0.987242984181682	0.960846070475546
24	0.8983	0.901183001531833	0.8962125	1.00554611939895	0.996800870048667
25	0.9376	0.898949131845817	0.8889375	1.01126246991022	1.04299561208188
26	0.9205	0.884920063195004	0.885595833333333	0.999236931664656	1.04020695007924
27	0.9083	0.888305363443903	0.8872125	1.00123179446176	1.02250874235249
28	0.8925	0.890122679095436	0.891145833333333	0.998851866664662	1.00267077893912
29	0.8753	0.897968837707923	0.8947125	1.00363953527856	0.97475542941358
30	0.853	0.901197683789725	0.895795833333333	1.00603022503051	0.946518189453125
31	0.8615	0.897836726534485	0.893233333333333	1.00515362898961	0.959528580798049
32	0.9014	0.888736918858607	0.888891666666667	0.999825909259966	1.01424840228046
33	0.9114	0.879224823684382	0.885495833333333	0.992918081132754	1.03659493618571
34	0.905	0.874234656399394	0.883904166666667	0.989060454026665	1.03519117364589
35	0.8883	0.874076143607423	0.885370833333333	0.987242984181682	1.01627301751295
36	0.8912	0.896348000607723	0.891404166666667	1.00554611939895	0.99425669427027
37	0.8832	0.91134973788309	0.9012	1.01126246991022	0.969112036013224
38	0.8707	0.909201520634456	0.909895833333333	0.999236931664656	0.957653479717468
39	0.8766	0.91710329293211	0.915975	1.00123179446176	0.955835625883956
40	0.886	0.920974716127041	0.922033333333333	0.998851866664662	0.962024238543573
41	0.917	0.933301131181125	0.929916666666667	1.00363953527856	0.9825338996852
42	0.9561	0.945634877187843	0.939966666666667	1.00603022503051	1.01106676907188
43	0.9935	0.957676872580333	0.952766666666667	1.00515362898961	1.03740627809372
44	0.9781	0.968714659716827	0.968883333333333	0.999825909259966	1.0096884466329
45	0.9806	0.979021365155567	0.986004166666667	0.992918081132754	1.00161246209799
46	0.9812	0.99183806546839	1.00280833333333	0.989060454026665	0.989274392828061
47	1.0013	1.00806558412305	1.02109166666667	0.987242984181682	0.993288547660385
48	1.0194	1.04560456293051	1.0398375	1.00554611939895	0.974938362111711
49	1.0622	1.06647740076732	1.0546	1.01126246991022	0.995989225121657
50	1.0785	1.06546968628516	1.06628333333333	0.999236931664656	1.01222964283505
51	1.0797	1.07942382581008	1.07809583333333	1.00123179446176	1.0002558533389
52	1.0862	1.09085444735003	1.09210833333333	0.998851866664662	0.995733209539237
53	1.1556	1.1111335113383	1.10710416666667	1.00363953527856	1.04001903300365
54	1.1674	1.1297132576128	1.12294166666667	1.00603022503051	1.03335956459149
55	1.1365	1.14598402869129	1.14010833333333	1.00515362898961	0.991724117916263
56	1.1155	1.15603620975797	1.1562375	0.999825909259966	0.964935172950632
57	1.1267	1.16178034946406	1.17006666666667	0.992918081132754	0.969804662748645
58	1.1714	1.16794440039306	1.1808625	0.989060454026665	1.00295870214864
59	1.171	1.1722605464422	1.18740833333333	0.987242984181682	0.99892468748008
60	1.2298	1.19783167608102	1.191225	1.00554611939895	1.0266884943497
61	1.2638	1.21042639976541	1.19694583333333	1.01126246991022	1.04409487453754
62	1.264	1.20409715660477	1.20501666666667	0.999236931664656	1.04974917768607
63	1.2261	1.21481539521617	1.21332083333333	1.00123179446176	1.00928915193886
64	1.1989	1.21921107409922	1.2206125	0.998851866664662	0.983340805763082
65	1.2	1.23375317156095	1.22927916666667	1.00363953527856	0.972641876560893
66	1.2146	1.24673133995427	1.23925833333333	1.00603022503051	0.974227534895012
67	1.2266	1.25231671821803	1.24589583333333	1.00515362898961	0.979464685056169
68	1.2191	1.24925331203131	1.24947083333333	0.999825909259966	0.975862932088387
69	1.2224	1.24598807706146	1.254875	0.992918081132754	0.981068777867366
70	1.2507	1.24888663529947	1.2627	0.989060454026665	1.00145198503153
71	1.2997	1.25338312515489	1.26957916666667	0.987242984181682	1.03695348526364
72	1.3406	1.27957838581265	1.27252083333333	1.00554611939895	1.04768884412548
73	1.3123	1.28594242470596	1.27162083333333	1.01126246991022	1.020496699376
74	1.3013	1.27014671778781	1.27111666666667	0.999236931664656	1.02452730993665
75	1.3185	1.27315800623929	1.27159166666667	1.00123179446176	1.03561379933874
76	1.2943	1.26815481556579	1.2696125	0.998851866664662	1.02061671344326
77	1.2697	1.26715345892875	1.26255833333333	1.00363953527856	1.00200965483171
78	1.2155	1.25863183915786	1.2510875	1.00603022503051	0.965731171089145
79	1.2041	1.24688888862149	1.24049583333333	1.00515362898961	0.965683479087864
80	1.2295	1.23165637602833	1.23187083333333	0.999825909259966	0.998249206458634
81	1.2234	1.21392096019955	1.22257916666667	0.992918081132754	1.00780861366698
82	1.2022	1.2016754829606	1.21496666666667	0.989060454026665	1.00043648809253
83	1.1789	1.19699921022082	1.21246666666667	0.987242984181682	0.98487951364857
84	1.1861	1.22160446225381	1.21486666666667	1.00554611939895	0.970936204515574
85	1.2126	1.23337784423875	1.21964166666667	1.01126246991022	0.98315370724729
86	1.194	1.223519824464	1.22445416666667	0.999236931664656	0.975873031336508
87	1.2028	1.23014675706887	1.22863333333333	1.00123179446176	0.977769516594893
88	1.2273	1.23173001749475	1.23314583333333	0.998851866664662	0.996403418418136
89	1.2767	1.24471793348387	1.24020416666667	1.00363953527856	1.02569422811047
90	1.2661	1.25792342620773	1.25038333333333	1.00603022503051	1.00650005685713
91	1.2681	1.26608732293519	1.25959583333333	1.00515362898961	1.00158968266118
92	1.281	1.26773759352875	1.26795833333333	0.999825909259966	1.0104614760491
93	1.2722	1.26873417543675	1.27778333333333	0.992918081132754	1.00273171845636
94	1.2617	1.2739345912977	1.288025	0.989060454026665	0.990396217057555
95	1.2888	1.27978364795689	1.29632083333333	0.987242984181682	1.00704521585153
96	1.3205	1.30984113423106	1.30261666666667	1.00554611939895	1.0081375256055
97	1.2993	1.324892884172	1.3101375	1.01126246991022	0.980683054096108
98	1.308	1.31688602526642	1.31789166666667	0.999236931664656	0.993252244236837
99	1.3246	1.32787532380662	1.32624166666667	1.00123179446176	0.997533410141826
100	1.3513	1.33638888370732	1.337925	0.998851866664662	1.01115776737929
101	1.3518	1.35705865213272	1.3521375	1.00363953527856	0.996124963261937
102	1.3421	1.37349114830811	1.36525833333333	1.00603022503051	0.97714499409277
103	1.3726	1.38523153309143	1.37812916666667	1.00515362898961	0.990881283893938
104	1.3626	1.3921117706994	1.39235416666667	0.999825909259966	0.978800717499446
105	1.391	1.39884781565185	1.408825	0.992918081132754	0.99438980025987
106	1.4233	1.41201979393549	1.4276375	0.989060454026665	1.00798870250471
107	1.4683	1.42701859851028	1.44545833333333	0.987242984181682	1.02892842569313
108	1.4559	1.47097571008925	1.4628625	1.00554611939895	0.989751217517838
109	1.4728	1.49692548467823	1.48025416666667	1.01126246991022	0.98388330954001
110	1.4759	1.49312227560156	1.4942625	0.999236931664656	0.988465595964256
111	1.552	1.50344966256378	1.5016	1.00123179446176	1.03229262584916
112	1.5754	1.49764935569755	1.49937083333333	0.998851866664662	1.05191511885386
113	1.5554	1.49267544433724	1.4872625	1.00363953527856	1.04202156329477
114	1.5562	1.48371014304541	1.47481666666667	1.00603022503051	1.04885715535098
115	1.5759	1.47181295380852	1.46426666666667	1.00515362898961	1.07072029494111
116	1.4955	1.4496559177186	1.44990833333333	0.999825909259966	1.03162411281261
117	1.4342	1.42130431292014	1.43144166666667	0.992918081132754	1.00907313582506
118	1.3266	1.39507389148984	1.41050416666667	0.989060454026665	0.950917372973907
119	1.2744	1.37415173670735	1.39190833333333	0.987242984181682	0.927408499336201
120	1.3511	1.38514815902305	1.37750833333333	1.00554611939895	0.975419121195624
121	1.3244	1.37947577598541	1.3641125	1.01126246991022	0.960074850936717
122	1.2797	1.35326241306623	1.35429583333333	0.999236931664656	0.945640688490305
123	1.305	1.35406170703094	1.35239583333333	1.00123179446176	0.963767007975938
124	1.3199	1.35828454900116	1.35984583333333	0.998851866664662	0.971740421379754
125	1.3646	1.38034727118258	1.37534166666667	1.00363953527856	0.98859180474991
126	1.4014	1.39718316010758	1.38880833333333	1.00603022503051	1.0030181009998
127	1.4092	NA	NA	1.00515362898961	NA
128	1.4266	NA	NA	0.999825909259966	NA
129	1.4575	NA	NA	0.992918081132754	NA
130	1.4821	NA	NA	0.989060454026665	NA
131	1.4908	NA	NA	0.987242984181682	NA
132	1.4579	NA	NA	1.00554611939895	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/1jrfl1274975469.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/1jrfl1274975469.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/2jrfl1274975469.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/2jrfl1274975469.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/3u1x61274975469.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/3u1x61274975469.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/4u1x61274975469.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/27/t1274975503fbw5sthvuxgoriz/4u1x61274975469.ps (open in new window)

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

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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We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

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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