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Opgave 9 Oefening 2 decompositie

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 06 Jun 2010 19:58:04 +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/Jun/06/t1275854417ft0y8xl7ff6dq9h.htm/, Retrieved Sun, 06 Jun 2010 22:00:23 +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/Jun/06/t1275854417ft0y8xl7ff6dq9h.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:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

0,9383 0,9217 0,9095 0,8920 0,8742 0,8607 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 1,5751 1,5557 1,5553 1,5770 1,4975 1,4370 1,3322 1,2732 1,3449 1,3239 1,2785 1,3050 1,3190 1,3650 1,4016 1,4088 1,4268 1,4562 1,4816 1,4914 1,4614

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	0.9383	NA	NA	0.00486019965277778	NA
2	0.9217	NA	NA	-0.00783563368055566	NA
3	0.9095	NA	NA	0.00144665798611115	NA
4	0.892	NA	NA	0.00173415798611112	NA
5	0.8742	NA	NA	0.0153945746527778	NA
6	0.8607	NA	NA	0.0120023871527777	NA
7	0.8607	0.903337803819445	0.893983333333333	0.00935447048611112	-0.0426378038194445
8	0.9005	0.887825303819445	0.8895375	-0.00171219618055551	0.0126746961805554
9	0.9111	0.877973741319445	0.885979166666667	-0.00800542534722225	0.0331262586805555
10	0.9059	0.867264887152778	0.884316666666667	-0.0170517795138888	0.0386351128472221
11	0.8883	0.869584678819444	0.885841666666667	-0.0162569878472223	0.0187153211805555
12	0.8924	0.897640407986111	0.891570833333333	0.00606957465277776	-0.00524040798611125
13	0.8833	0.905856032986111	0.900995833333333	0.00486019965277778	-0.0225560329861111
14	0.87	0.901860199652778	0.909695833333333	-0.00783563368055566	-0.0318601996527778
15	0.8758	0.917267491319444	0.915820833333333	0.00144665798611115	-0.0414674913194444
16	0.8858	0.923592491319444	0.921858333333333	0.00173415798611112	-0.0377924913194443
17	0.917	0.945098741319444	0.929704166666667	0.0153945746527778	-0.0280987413194445
18	0.9554	0.951664887152778	0.9396625	0.0120023871527777	0.00373511284722239
19	0.9922	0.961716970486111	0.9523625	0.00935447048611112	0.0304830295138889
20	0.9778	0.966741970486111	0.968454166666667	-0.00171219618055551	0.0110580295138890
21	0.9808	0.977623741319444	0.985629166666667	-0.00800542534722225	0.0031762586805556
22	0.9811	0.985406553819445	1.00245833333333	-0.0170517795138888	-0.00430655381944467
23	1.0014	1.00454301215278	1.0208	-0.0162569878472223	-0.00314301215277757
24	1.0183	1.04570707465278	1.0396375	0.00606957465277776	-0.0274070746527777
25	1.0622	1.05932686631944	1.05446666666667	0.00486019965277778	0.00287313368055564
26	1.0773	1.05834353298611	1.06617916666667	-0.00783563368055566	0.0189564670138886
27	1.0807	1.07918832465278	1.07774166666667	0.00144665798611115	0.00151167534722219
28	1.0848	1.09320499131944	1.09147083333333	0.00173415798611112	-0.00840499131944461
29	1.1582	1.12173624131944	1.10634166666667	0.0153945746527778	0.0364637586805552
30	1.1663	1.13413988715278	1.1221375	0.0120023871527777	0.0321601128472222
31	1.1372	1.14855030381944	1.13919583333333	0.00935447048611112	-0.0113503038194442
32	1.1139	1.15358363715278	1.15529583333333	-0.00171219618055551	-0.039683637152778
33	1.1222	1.16115707465278	1.1691625	-0.00800542534722225	-0.0389570746527779
34	1.1692	1.16291072048611	1.1799625	-0.0170517795138888	0.00628927951388913
35	1.1702	1.17021384548611	1.18647083333333	-0.0162569878472223	-1.38454861111637e-05
36	1.2286	1.19629040798611	1.19022083333333	0.00606957465277776	0.0323095920138887
37	1.2613	1.20078519965278	1.195925	0.00486019965277778	0.0605148003472225
38	1.2646	1.19613519965278	1.20397083333333	-0.00783563368055566	0.0684648003472224
39	1.2262	1.21388832465278	1.21244166666667	0.00144665798611115	0.0123116753472223
40	1.1985	1.22165082465278	1.21991666666667	0.00173415798611112	-0.0231508246527781
41	1.2007	1.24400707465278	1.2286125	0.0153945746527778	-0.0433070746527777
42	1.2138	1.25066072048611	1.23865833333333	0.0120023871527777	-0.0368607204861111
43	1.2266	1.25479613715278	1.24544166666667	0.00935447048611112	-0.0281961371527777
44	1.2176	1.24737113715278	1.24908333333333	-0.00171219618055551	-0.0297711371527776
45	1.2218	1.24652374131944	1.25452916666667	-0.00800542534722225	-0.0247237413194445
46	1.249	1.24536072048611	1.2624125	-0.0170517795138888	0.00363927951388887
47	1.2991	1.25298884548611	1.26924583333333	-0.0162569878472223	0.0461111545138890
48	1.3408	1.27829040798611	1.27222083333333	0.00606957465277776	0.0625095920138892
49	1.3119	1.27623936631944	1.27137916666667	0.00486019965277778	0.0356606336805558
50	1.3014	1.26307269965278	1.27090833333333	-0.00783563368055566	0.0383273003472222
51	1.3201	1.27299665798611	1.27155	0.00144665798611115	0.0471033420138889
52	1.2938	1.27146332465278	1.26972916666667	0.00173415798611112	0.0223366753472221
53	1.2694	1.27812374131944	1.26272916666667	0.0153945746527778	-0.00872374131944431
54	1.2165	1.26324405381944	1.25124166666667	0.0120023871527777	-0.0467440538194444
55	1.2037	1.24989613715278	1.24054166666667	0.00935447048611112	-0.0461961371527777
56	1.2292	1.23011280381944	1.231825	-0.00171219618055551	-0.000912803819444363
57	1.2256	1.21441540798611	1.22242083333333	-0.00800542534722225	0.0111845920138887
58	1.2015	1.19766905381944	1.21472083333333	-0.0170517795138888	0.00383094618055568
59	1.1786	1.19600134548611	1.21225833333333	-0.0162569878472223	-0.0174013454861108
60	1.1856	1.22066540798611	1.21459583333333	0.00606957465277776	-0.0350654079861108
61	1.2103	1.22417269965278	1.2193125	0.00486019965277778	-0.0138726996527780
62	1.1938	1.21633519965278	1.22417083333333	-0.00783563368055566	-0.0225351996527778
63	1.202	1.22974249131944	1.22829583333333	0.00144665798611115	-0.0277424913194444
64	1.2271	1.23447582465278	1.23274166666667	0.00173415798611112	-0.00737582465277753
65	1.277	1.25518207465278	1.2397875	0.0153945746527778	0.0218179253472219
66	1.265	1.26200655381944	1.25000416666667	0.0120023871527777	0.00299344618055541
67	1.2684	1.26874613715278	1.25939166666667	0.00935447048611112	-0.000346137152777759
68	1.2811	1.26614613715278	1.26785833333333	-0.00171219618055551	0.0149538628472221
69	1.2727	1.26967790798611	1.27768333333333	-0.00800542534722225	0.00302209201388903
70	1.2611	1.27091072048611	1.2879625	-0.0170517795138888	-0.00981072048611087
71	1.2881	1.27998051215278	1.2962375	-0.0162569878472223	0.00811948784722238
72	1.3213	1.30859874131944	1.30252916666667	0.00606957465277776	0.0127012586805557
73	1.2999	1.31489353298611	1.31003333333333	0.00486019965277778	-0.0149935329861111
74	1.3074	1.30987686631944	1.3177125	-0.00783563368055566	-0.00247686631944455
75	1.3242	1.32740915798611	1.3259625	0.00144665798611115	-0.0032091579861111
76	1.3516	1.33930082465278	1.33756666666667	0.00173415798611112	0.0122991753472221
77	1.3511	1.36720707465278	1.3518125	0.0153945746527778	-0.0161070746527776
78	1.3419	1.37698155381944	1.36497916666667	0.0120023871527777	-0.0350815538194442
79	1.3716	1.38715030381944	1.37779583333333	0.00935447048611112	-0.0155503038194444
80	1.3622	1.39022113715278	1.39193333333333	-0.00171219618055551	-0.0280211371527777
81	1.3896	1.40042374131944	1.40842916666667	-0.00800542534722225	-0.0108237413194447
82	1.4227	1.41021072048611	1.4272625	-0.0170517795138888	0.0124892795138891
83	1.4684	1.42884301215278	1.4451	-0.0162569878472223	0.0395569878472219
84	1.457	1.46858624131944	1.46251666666667	0.00606957465277776	-0.0115862413194443
85	1.4718	1.48482686631944	1.47996666666667	0.00486019965277778	-0.0130268663194444
86	1.4748	1.48632686631944	1.4941625	-0.00783563368055566	-0.0115268663194441
87	1.5527	1.50322165798611	1.501775	0.00144665798611115	0.0494783420138887
88	1.5751	1.50171332465278	1.49997916666667	0.00173415798611112	0.0733866753472221
89	1.5557	1.50346957465278	1.488075	0.0153945746527778	0.0522304253472223
90	1.5553	1.48727322048611	1.47527083333333	0.0120023871527777	0.0680267795138891
91	1.577	1.47379197048611	1.4644375	0.00935447048611112	0.103208029513889
92	1.4975	1.44838363715278	1.45009583333333	-0.00171219618055551	0.0491163628472224
93	1.437	1.42359040798611	1.43159583333333	-0.00800542534722225	0.0134095920138890
94	1.3322	1.39355238715278	1.41060416666667	-0.0170517795138888	-0.0613523871527777
95	1.2732	1.37573051215278	1.3919875	-0.0162569878472223	-0.102530512152778
96	1.3449	1.38370707465278	1.3776375	0.00606957465277776	-0.0388070746527778
97	1.3239	1.36908519965278	1.364225	0.00486019965277778	-0.0451851996527777
98	1.2785	1.34643519965278	1.35427083333333	-0.00783563368055566	-0.067935199652778
99	1.305	1.35357165798611	1.352125	0.00144665798611115	-0.0485716579861113
100	1.319	1.36088415798611	1.35915	0.00173415798611112	-0.0418841579861111
101	1.365	1.38986124131944	1.37446666666667	0.0153945746527778	-0.0248612413194447
102	1.4016	1.40041488715278	1.3884125	0.0120023871527777	0.00118511284722222
103	1.4088	NA	NA	0.00935447048611112	NA
104	1.4268	NA	NA	-0.00171219618055551	NA
105	1.4562	NA	NA	-0.00800542534722225	NA
106	1.4816	NA	NA	-0.0170517795138888	NA
107	1.4914	NA	NA	-0.0162569878472223	NA
108	1.4614	NA	NA	0.00606957465277776	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/1j9hv1275854281.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/1j9hv1275854281.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/2j9hv1275854281.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/2j9hv1275854281.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/3ciyy1275854281.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/3ciyy1275854281.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/4ciyy1275854281.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jun/06/t1275854417ft0y8xl7ff6dq9h/4ciyy1275854281.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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