Home » date » 2009 » Jun » 07 »

Opdracht 9 oefening 2

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 07 Jun 2009 09:23:52 -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/07/t1244388385xb16lqv90ipnaq3.htm/, Retrieved Sun, 07 Jun 2009 17:26:30 +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/07/t1244388385xb16lqv90ipnaq3.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:

thomas cammaert

Dataseries X:

» Textbox « » Textfile « » CSV «

8,9722 8,8284 8,7446 8,7519 8,6337 8,7272 8,6330 8,5865 8,5968 8,5114 8,3884 8,2671 8,2410 8,3177 8,4070 8,3917 8,4145 8,5245 8,6289 8,6622 8,9055 8,9770 9,1264 9,1120 9,0576 9,2106 9,2637 9,3107 9,6744 9,5780 9,4166 9,4359 9,2275 9,1828 9,0594 9,1358 9,2208 9,1137 9,2689 9,2489 9,1679 9,1051 9,0818 9,0961 9,1733 9,1455 9,2265 9,1541 9,1559 9,1182 9,1856 9,2378 9,0682 9,0105 8,9939 9,0228 9,1368 9,1763 9,2346 9,1653 9,1277 9,1430 9,1962 9,1861 9,0920 9,0620 8,9981 8,9819 9,0476 9,0852 9,0884 9,1670 9,1931 9,2628 9,4276 9,3398 9,3342 9,4223 9,5614 9,4316 9,3111 9,3414 9,4017 9,3346 9,3310 9,2349 9,2170 9,2098 9,2665 9,2533 9,1008 9,0377 9,0795 9,1896 9,2992 9,2372 9,2061 9,3290 9,1842 9,3231 9,2835 9,1735 9,2889 9,4319 9,4314 9,3642 9,4020 9,3699 9,3106 9,3739 9,4566 9,3984 9,5637 9,8506

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	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.9722	NA	NA	0.996413972028731	NA
2	8.8284	NA	NA	0.998332675899909	NA
3	8.7446	NA	NA	1.00320216960678	NA
4	8.7519	NA	NA	1.00352650149531	NA
5	8.6337	NA	NA	1.00309617782405	NA
6	8.7272	NA	NA	0.999620611253606	NA
7	8.633	8.5855656916167	8.6063	0.997590798788876	1.00552489027364
8	8.5865	8.52697232011876	8.55455416666667	0.996775770424672	1.00698110391901
9	8.5968	8.50786043051106	8.51920833333333	0.99866796275214	1.01045381153292
10	8.5114	8.4862263859274	8.49013333333333	0.99953982496475	1.00296640849864
11	8.3884	8.49510145836803	8.46599166666667	1.00343843850166	0.98743964873275
12	8.2671	8.44668139036732	8.4484125	0.99979509645952	0.978739414680407
13	8.241	8.4095304894032	8.43979583333333	0.996413972028731	0.979959583996328
14	8.3177	8.42870231749034	8.44277916666667	0.998332675899909	0.986830438030775
15	8.407	8.48588233226078	8.45879583333333	1.00320216960678	0.99070428634617
16	8.3917	8.52100206324256	8.49105833333333	1.00352650149531	0.984825486218301
17	8.4145	8.56765343316562	8.54120833333333	1.00309617782405	0.982124226387034
18	8.5245	8.60389703940911	8.6071625	0.999620611253606	0.99077196774375
19	8.6289	8.65548849335515	8.67639166666667	0.997590798788876	0.996928134861994
20	8.6622	8.71941649552875	8.74762083333333	0.996775770424672	0.993438036185324
21	8.9055	8.80877157103782	8.82052083333333	0.99866796275214	1.01098092148061
22	8.977	8.89041530264752	8.89450833333333	0.99953982496475	1.00973910603779
23	9.1264	9.01619122047543	8.98529583333333	1.00343843850166	1.01222342969771
24	9.112	9.07982663007772	9.0816875	0.99979509645952	1.00354339033476
25	9.0576	9.12556187315282	9.15840416666667	0.996413972028731	0.992552582065905
26	9.2106	9.20808399868746	9.2234625	0.998332675899909	1.00027323831026
27	9.2637	9.29879795033836	9.26911666666667	1.00320216960678	0.996225538986243
28	9.3107	9.32387344076388	9.29110833333333	1.00352650149531	0.998587127887613
29	9.6744	9.32567649647763	9.29689166666667	1.00309617782405	1.03739390956292
30	9.578	9.29156521349163	9.29509166666667	0.999620611253606	1.03082739882108
31	9.4166	9.28047081553972	9.30288333333333	0.997590798788876	1.01466834896268
32	9.4359	9.27564229481998	9.30564583333333	0.996775770424672	1.01727726232711
33	9.2275	9.28943462262693	9.301825	0.99866796275214	0.99333278879254
34	9.1828	9.29518728426554	9.29946666666667	0.99953982496475	0.98790908877589
35	9.0594	9.30768172487318	9.2757875	1.00343843850166	0.973325073609932
36	9.1358	9.23308688673916	9.23497916666667	0.99979509645952	0.989463232835067
37	9.2208	9.16832879117726	9.201325	0.996413972028731	1.00572309414484
38	9.1137	9.15792194144298	9.17321666666667	0.998332675899909	0.99517118165827
39	9.2689	9.18612162665535	9.1568	1.00320216960678	1.00901124290630
40	9.2489	9.18526552410527	9.1529875	1.00352650149531	1.00692788637713
41	9.1679	9.1867518554164	9.15839583333333	1.00309617782405	0.997947930268163
42	9.1051	9.16264331024108	9.16612083333333	0.999620611253606	0.993719791517284
43	9.0818	9.14210081511938	9.16417916666667	0.997590798788876	0.993404052707486
44	9.0961	9.13212319680833	9.1616625	0.996775770424672	0.996055331708521
45	9.1733	9.14617986448665	9.15837916666667	0.99866796275214	1.00296518720550
46	9.1455	9.1502331858993	9.15444583333333	0.99953982496475	0.99948272510622
47	9.2265	9.1812902915569	9.14982916666667	1.00343843850166	1.00492411273442
48	9.1541	9.13986015980722	9.14173333333333	0.99979509645952	1.00155799322351
49	9.1559	9.10137392398182	9.13412916666667	0.996413972028731	1.00599097196463
50	9.1182	9.11219414516728	9.1274125	0.998332675899909	1.00065910084191
51	9.1856	9.15205037297008	9.1228375	1.00320216960678	1.00366580445503
52	9.2378	9.15477086254108	9.1226	1.00352650149531	1.00906949378697
53	9.0682	9.15247104353926	9.12422083333333	1.00309617782405	0.99079253644853
54	9.0105	9.12156306820443	9.125025	0.999620611253606	0.98782411880793
55	8.9939	9.10233435190266	9.12431666666667	0.997590798788876	0.988087193052847
56	9.0228	9.09475656511454	9.124175	0.996775770424672	0.99208812631769
57	9.1368	9.11349429428908	9.12565	0.99866796275214	1.00255727440632
58	9.1763	9.11973889173933	9.1239375	0.99953982496475	1.00620205347238
59	9.2346	9.15414310080194	9.122775	1.00343843850166	1.00878912404057
60	9.1653	9.12404256821865	9.1259125	0.99979509645952	1.00452183683634
61	9.1277	9.09549923327173	9.12823333333333	0.996413972028731	1.00354029678882
62	9.143	9.11148699285518	9.12670416666666	0.998332675899909	1.00345860200092
63	9.1962	9.15049122959815	9.12128333333333	1.00320216960678	1.00499522585782
64	9.1861	9.14591055980496	9.11377083333333	1.00352650149531	1.00439425248391
65	9.092	9.13207057502277	9.10388333333333	1.00309617782405	0.995612104101302
66	9.062	9.09441087335126	9.0978625	0.999620611253606	0.996436176702085
67	8.9981	9.07873301625464	9.10065833333333	0.997590798788876	0.991118472576484
68	8.9819	9.07900750794182	9.108375	0.996775770424672	0.989304171424368
69	9.0476	9.1108561464208	9.12300833333333	0.99866796275214	0.993057057931306
70	9.0852	9.13484860209338	9.13905416666667	0.99953982496475	0.994564923376836
71	9.0884	9.18703079562383	9.15555	1.00343843850166	0.989264127026676
72	9.167	9.178773018124	9.18065416666667	0.99979509645952	0.998717364717402
73	9.1931	9.18607741505402	9.2191375	0.996413972028731	1.00076448135898
74	9.2628	9.24590416822614	9.26134583333333	0.998332675899909	1.00182738556083
75	9.4276	9.32081405795218	9.2910625	1.00320216960678	1.01145671841364
76	9.3398	9.34555797591702	9.31271666666667	1.00352650149531	0.999383880991177
77	9.3342	9.36535312987797	9.33644583333333	1.00309617782405	0.996673576591726
78	9.4223	9.35293358885084	9.35648333333333	0.999620611253606	1.00741654054209
79	9.5614	9.34664018189773	9.3692125	0.997590798788876	1.02297722111077
80	9.4316	9.34357256357442	9.37379583333333	0.996775770424672	1.00942117544725
81	9.3111	9.35138532524966	9.36385833333333	0.99866796275214	0.99569204734395
82	9.3414	9.34536418347876	9.34966666666667	0.99953982496475	0.999575812841433
83	9.4017	9.37354909637382	9.34142916666667	1.00343843850166	1.00300322784217
84	9.3346	9.32965459561845	9.33156666666667	0.99979509645952	1.00053007368396
85	9.331	9.27196414771802	9.30533333333334	0.996413972028731	1.00636713552182
86	9.2349	9.25427352382577	9.26972916666667	0.998332675899909	0.997906532179334
87	9.217	9.27326645512186	9.24366666666667	1.00320216960678	0.993932401770815
88	9.2098	9.26023313512738	9.22769166666666	1.00352650149531	0.994553794230507
89	9.2665	9.24563360105467	9.21709583333333	1.00309617782405	1.00225689226349
90	9.2533	9.20527296422516	9.20876666666666	0.999620611253606	1.00521733966624
91	9.1008	9.1773407100866	9.19950416666667	0.997590798788876	0.991659816007215
92	9.0377	9.1685636576821	9.19822083333333	0.996775770424672	0.985726918351878
93	9.0795	9.18851922499083	9.200775	0.99866796275214	0.988135278131179
94	9.1896	9.19989365620296	9.20412916666666	0.99953982496475	0.99888111139241
95	9.2992	9.2412248332899	9.20955833333333	1.00343843850166	1.00627353708583
96	9.2372	9.20505513172218	9.20694166666667	0.99979509645952	1.00349208862064
97	9.2061	9.17842163436894	9.21145416666667	0.996413972028731	1.00301559099523
98	9.329	9.22031773368672	9.23571666666667	0.998332675899909	1.01178725825426
99	9.1842	9.29647804532114	9.26680416666667	1.00320216960678	0.987922518100535
100	9.3231	9.32149842804367	9.28874166666666	1.00352650149531	1.00017181486096
101	9.2835	9.32909538261704	9.3003	1.00309617782405	0.995112561213384
102	9.1735	9.30658034808983	9.3101125	0.999620611253606	0.9857004030361
103	9.2889	9.297542088084	9.31999583333333	0.997590798788876	0.999070497557083
104	9.4319	9.29615095629646	9.32622083333333	0.996775770424672	1.01460271507441
105	9.4314	9.32700118249246	9.33944166666667	0.99866796275214	1.01119318154516
106	9.3642	9.34962472198268	9.35392916666667	0.99953982496475	1.0015589158336
107	9.402	9.4009555087254	9.36874166666667	1.00343843850166	1.00011110479926
108	9.3699	9.40670130523936	9.40862916666667	0.99979509645952	0.996087756584886
109	9.3106	NA	NA	NA	NA
110	9.3739	NA	NA	NA	NA
111	9.4566	NA	NA	NA	NA
112	9.3984	NA	NA	NA	NA
113	9.5637	NA	NA	NA	NA
114	9.8506	NA	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/12dtd1244388229.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/12dtd1244388229.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/2aq291244388229.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/2aq291244388229.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/39bhi1244388229.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/39bhi1244388229.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/4s58o1244388229.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244388385xb16lqv90ipnaq3/4s58o1244388229.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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