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CD Dollar

*The author of this computation has been verified*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 26 Dec 2010 12:31:19 +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/26/t1293366670cfer3pjhp8pn4yp.htm/, Retrieved Sun, 26 Dec 2010 13:31:15 +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/26/t1293366670cfer3pjhp8pn4yp.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 «

0,8973 0,9383 0,9217 0,9095 0,892 0,8742 0,8532 0,8607 0,9005 0,9111 0,9059 0,8883 0,8924 0,8833 0,87 0,8758 0,8858 0,917 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 1,249 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 1,202 1,2271 1,277 1,265 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 1,457 1,4718 1,4748 1,5527 1,575 1,5557 1,5553 1,577 1,4975 1,4369 1,3322 1,2732 1,3449 1,3239 1,2785 1,305 1,319 1,365 1,4016 1,4088 1,4268 1,4562 1,4816 1,4914 1,4614 1,4272 1,3686 1,3569 1,3406 1,2565 1,2208 1,277 1,2894 1,3067 1,3898 1,3661

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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	0.8973	NA	NA	0.0107257330246914	NA
2	0.9383	NA	NA	0.00726323302469138	NA
3	0.9217	NA	NA	-0.00928676697530873	NA
4	0.9095	NA	NA	-0.00100760030864195	NA
5	0.892	NA	NA	-0.00145713734567903	NA
6	0.8742	NA	NA	0.00235721450617286	NA
7	0.8532	0.900138695987654	0.895854166666667	0.00428452932098763	-0.0469386959876544
8	0.8607	0.901345640432099	0.893358333333333	0.00798730709876542	-0.0406456404320987
9	0.9005	0.888167399691358	0.8889125	-0.000745100308641905	0.0123326003086419
10	0.9111	0.881613233024691	0.885354166666667	-0.00374093364197534	0.0294867669753087
11	0.9059	0.874402584876543	0.883691666666667	-0.00928908179012342	0.0314974151234567
12	0.8883	0.878125270061728	0.885216666666667	-0.00709139660493828	0.0101747299382716
13	0.8924	0.901984066358025	0.891258333333333	0.0107257330246914	-0.00958406635802478
14	0.8833	0.908259066358025	0.900995833333333	0.00726323302469138	-0.0249590663580247
15	0.87	0.900409066358025	0.909695833333333	-0.00928676697530873	-0.0304090663580247
16	0.8758	0.914813233024691	0.915820833333333	-0.00100760030864195	-0.0390132330246913
17	0.8858	0.920401195987654	0.921858333333333	-0.00145713734567903	-0.0346011959876542
18	0.917	0.93206138117284	0.929704166666667	0.00235721450617286	-0.0150613811728395
19	0.9554	0.943947029320988	0.9396625	0.00428452932098763	0.0114529706790125
20	0.9922	0.960349807098765	0.9523625	0.00798730709876542	0.0318501929012347
21	0.9778	0.967709066358025	0.968454166666667	-0.000745100308641905	0.0100909336419754
22	0.9808	0.981888233024691	0.985629166666667	-0.00374093364197534	-0.00108823302469130
23	0.9811	0.99316925154321	1.00245833333333	-0.00928908179012342	-0.0120692515432100
24	1.0014	1.01370860339506	1.0208	-0.00709139660493828	-0.0123086033950617
25	1.0183	1.05036323302469	1.0396375	0.0107257330246914	-0.0320632330246913
26	1.0622	1.06172989969136	1.05446666666667	0.00726323302469138	0.00047010030864203
27	1.0773	1.05689239969136	1.06617916666667	-0.00928676697530873	0.0204076003086417
28	1.0807	1.07673406635802	1.07774166666667	-0.00100760030864195	0.00396593364197528
29	1.0848	1.09001369598765	1.09147083333333	-0.00145713734567903	-0.00521369598765431
30	1.1582	1.10869888117284	1.10634166666667	0.00235721450617286	0.0495011188271604
31	1.1663	1.12642202932099	1.1221375	0.00428452932098763	0.0398779706790122
32	1.1372	1.14718314043210	1.13919583333333	0.00798730709876542	-0.0099831404320987
33	1.1139	1.15455073302469	1.15529583333333	-0.000745100308641905	-0.0406507330246917
34	1.1222	1.16542156635802	1.1691625	-0.00374093364197534	-0.0432215663580247
35	1.1692	1.17067341820988	1.1799625	-0.00928908179012342	-0.00147341820987634
36	1.1702	1.17937943672840	1.18647083333333	-0.00709139660493828	-0.00917943672839527
37	1.2286	1.20094656635802	1.19022083333333	0.0107257330246914	0.0276534336419751
38	1.2613	1.20318823302469	1.195925	0.00726323302469138	0.0581117669753088
39	1.2646	1.19468406635802	1.20397083333333	-0.00928676697530873	0.0699159336419755
40	1.2262	1.21143406635802	1.21244166666667	-0.00100760030864195	0.0147659336419754
41	1.1985	1.21845952932099	1.21991666666667	-0.00145713734567903	-0.0199595293209878
42	1.2007	1.23096971450617	1.2286125	0.00235721450617286	-0.0302697145061726
43	1.2138	1.24294286265432	1.23865833333333	0.00428452932098763	-0.0291428626543211
44	1.2266	1.25342897376543	1.24544166666667	0.00798730709876542	-0.0268289737654321
45	1.2176	1.24833823302469	1.24908333333333	-0.000745100308641905	-0.0307382330246913
46	1.2218	1.25078823302469	1.25452916666667	-0.00374093364197534	-0.0289882330246913
47	1.249	1.25312341820988	1.2624125	-0.00928908179012342	-0.0041234182098766
48	1.2991	1.26215443672840	1.26924583333333	-0.00709139660493828	0.0369455632716049
49	1.3408	1.28294656635802	1.27222083333333	0.0107257330246914	0.0578534336419756
50	1.3119	1.27864239969136	1.27137916666667	0.00726323302469138	0.0332576003086422
51	1.3014	1.26162156635802	1.27090833333333	-0.00928676697530873	0.0397784336419753
52	1.3201	1.27054239969136	1.27155	-0.00100760030864195	0.049557600308642
53	1.2938	1.26827202932099	1.26972916666667	-0.00145713734567903	0.0255279706790124
54	1.2694	1.26508638117284	1.26272916666667	0.00235721450617286	0.00431361882716086
55	1.2165	1.25552619598765	1.25124166666667	0.00428452932098763	-0.0390261959876543
56	1.2037	1.24852897376543	1.24054166666667	0.00798730709876542	-0.0448289737654322
57	1.2292	1.23107989969136	1.231825	-0.000745100308641905	-0.00187989969135804
58	1.2256	1.21867989969136	1.22242083333333	-0.00374093364197534	0.00692010030864187
59	1.2015	1.20543175154321	1.21472083333333	-0.00928908179012342	-0.00393175154320979
60	1.1786	1.20516693672840	1.21225833333333	-0.00709139660493828	-0.0265669367283949
61	1.1856	1.22532156635802	1.21459583333333	0.0107257330246914	-0.0397215663580244
62	1.2103	1.22657573302469	1.2193125	0.00726323302469138	-0.0162757330246917
63	1.1938	1.21488406635802	1.22417083333333	-0.00928676697530873	-0.0210840663580247
64	1.202	1.22728823302469	1.22829583333333	-0.00100760030864195	-0.0252882330246913
65	1.2271	1.23128452932099	1.23274166666667	-0.00145713734567903	-0.00418452932098723
66	1.277	1.24214471450617	1.2397875	0.00235721450617286	0.0348552854938271
67	1.265	1.25428869598765	1.25000416666667	0.00428452932098763	0.0107113040123454
68	1.2684	1.26737897376543	1.25939166666667	0.00798730709876542	0.00102102623456779
69	1.2811	1.26711323302469	1.26785833333333	-0.000745100308641905	0.0139867669753084
70	1.2727	1.27394239969136	1.27768333333333	-0.00374093364197534	-0.00124239969135775
71	1.2611	1.27867341820988	1.2879625	-0.00928908179012342	-0.0175734182098763
72	1.2881	1.28914610339506	1.2962375	-0.00709139660493828	-0.00104610339506173
73	1.3213	1.31325489969136	1.30252916666667	0.0107257330246914	0.00804510030864214
74	1.2999	1.31729656635802	1.31003333333333	0.00726323302469138	-0.0173965663580247
75	1.3074	1.30842573302469	1.3177125	-0.00928676697530873	-0.00102573302469144
76	1.3242	1.32495489969136	1.3259625	-0.00100760030864195	-0.000754899691358002
77	1.3516	1.33610952932099	1.33756666666667	-0.00145713734567903	0.0154904706790124
78	1.3511	1.35416971450617	1.3518125	0.00235721450617286	-0.00306971450617244
79	1.3419	1.36926369598765	1.36497916666667	0.00428452932098763	-0.0273636959876542
80	1.3716	1.3857831404321	1.37779583333333	0.00798730709876542	-0.0141831404320989
81	1.3622	1.39118823302469	1.39193333333333	-0.000745100308641905	-0.0289882330246913
82	1.3896	1.40468823302469	1.40842916666667	-0.00374093364197534	-0.0150882330246915
83	1.4227	1.41796925154321	1.42725833333333	-0.00928908179012342	0.00473074845679022
84	1.4684	1.43800027006173	1.44509166666667	-0.00709139660493828	0.0303997299382712
85	1.457	1.47323406635802	1.46250833333333	0.0107257330246914	-0.0162340663580247
86	1.4718	1.48722156635802	1.47995833333333	0.00726323302469138	-0.0154215663580246
87	1.4748	1.48486739969136	1.49415416666667	-0.00928676697530873	-0.0100673996913578
88	1.5527	1.50075489969136	1.5017625	-0.00100760030864195	0.0519451003086417
89	1.575	1.49850536265432	1.4999625	-0.00145713734567903	0.076494637345679
90	1.5557	1.49041554783951	1.48805833333333	0.00235721450617286	0.065284452160494
91	1.5553	1.47953869598765	1.47525416666667	0.00428452932098763	0.075761304012346
92	1.577	1.4724081404321	1.46442083333333	0.00798730709876542	0.104591859567901
93	1.4975	1.44933406635802	1.45007916666667	-0.000745100308641905	0.0481659336419755
94	1.4369	1.42783823302469	1.43157916666667	-0.00374093364197534	0.00906176697530903
95	1.3322	1.40130258487654	1.41059166666667	-0.00928908179012342	-0.0691025848765432
96	1.2732	1.38488777006173	1.39197916666667	-0.00709139660493828	-0.111687770061728
97	1.3449	1.38835489969136	1.37762916666667	0.0107257330246914	-0.0434548996913577
98	1.3239	1.37147989969136	1.36421666666667	0.00726323302469138	-0.0475798996913579
99	1.2785	1.34497573302469	1.3542625	-0.00928676697530873	-0.0664757330246915
100	1.305	1.35111323302469	1.35212083333333	-0.00100760030864195	-0.0461132330246916
101	1.319	1.35769286265432	1.35915	-0.00145713734567903	-0.0386928626543208
102	1.365	1.37682388117284	1.37446666666667	0.00235721450617286	-0.0118238811728395
103	1.4016	1.39269702932099	1.3884125	0.00428452932098763	0.00890297067901225
104	1.4088	1.4055581404321	1.39757083333333	0.00798730709876542	0.00324185956790113
105	1.4268	1.40488406635802	1.40562916666667	-0.000745100308641905	0.0219159336419752
106	1.4562	1.40780489969136	1.41154583333333	-0.00374093364197534	0.0483951003086418
107	1.4816	1.40531925154321	1.41460833333333	-0.00928908179012342	0.0762807484567902
108	1.4914	1.40389610339506	1.4109875	-0.00709139660493828	0.0875038966049382
109	1.4614	1.40965906635802	1.39893333333333	0.0107257330246914	0.0517409336419754
110	1.4272	1.39317156635802	1.38590833333333	0.00726323302469138	0.0340284336419754
111	1.3686	1.36540489969136	1.37469166666667	-0.00928676697530873	0.00319510030864212
112	1.3569	1.36172989969136	1.3627375	-0.00100760030864195	-0.00482989969135805
113	1.3406	1.35122619598765	1.35268333333333	-0.00145713734567903	-0.0106261959876544
114	1.2565	1.34599471450617	1.3436375	0.00235721450617286	-0.089494714506173
115	1.2208	NA	NA	0.00428452932098763	NA
116	1.277	NA	NA	0.00798730709876542	NA
117	1.2894	NA	NA	-0.000745100308641905	NA
118	1.3067	NA	NA	-0.00374093364197534	NA
119	1.3898	NA	NA	-0.00928908179012342	NA
120	1.3661	NA	NA	-0.00709139660493828	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/1jdoz1293366675.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/1jdoz1293366675.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/2umnj1293366675.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/2umnj1293366675.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/3umnj1293366675.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/3umnj1293366675.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/45dnm1293366675.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293366670cfer3pjhp8pn4yp/45dnm1293366675.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])

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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