Home » date » 2010 » Dec » 06 »

opdracht 9 oef 2 eigen reeks

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 06 Dec 2010 14:08:25 +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/06/t1291644473iobz8k2kegg06yq.htm/, Retrieved Mon, 06 Dec 2010 15:07:54 +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/06/t1291644473iobz8k2kegg06yq.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:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

7,08 7,08 7,09 7,07 7,06 6,99 6,99 6,99 6,98 6,96 6,95 6,91 6,91 6,87 6,91 6,89 6,88 6,9 6,91 6,85 6,86 6,82 6,8 6,83 6,84 6,89 7,14 7,21 7,25 7,31 7,3 7,48 7,49 7,4 7,44 7,42 7,14 7,24 7,33 7,61 7,66 7,69 7,7 7,68 7,71 7,71 7,72 7,68 7,72 7,74 7,76 7,9 7,97 7,96 7,95 7,97 7,93 7,99 7,96 7,92 7,97 7,98 8 8,04 8,17 8,29 8,26 8,3 8,32 8,28 8,27 8,32 8,31 8,34 8,32 8,36 8,33 8,35 8,34 8,37 8,31 8,33 8,34 8,25

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	7.08	NA	NA	-0.0989814814814815	NA
2	7.08	NA	NA	-0.0896064814814817	NA
3	7.09	NA	NA	-0.0417592592592595	NA
4	7.07	NA	NA	0.031157407407407	NA
5	7.06	NA	NA	0.0536574074074075	NA
6	6.99	NA	NA	0.0746990740740737	NA
7	6.99	7.0500462962963	7.00541666666667	0.0446296296296297	-0.0600462962962949
8	6.99	7.04358796296296	6.98958333333333	0.0540046296296298	-0.0535879629629621
9	6.98	7.01337962962963	6.97333333333333	0.0400462962962964	-0.0333796296296285
10	6.96	6.95921296296296	6.95833333333333	0.000879629629629668	0.000787037037038196
11	6.95	6.92310185185185	6.94333333333333	-0.0202314814814813	0.0268981481481489
12	6.91	6.88358796296296	6.93208333333333	-0.0484953703703697	0.0264120370370371
13	6.91	6.82601851851852	6.925	-0.0989814814814815	0.0839814814814828
14	6.87	6.82622685185185	6.91583333333333	-0.0896064814814817	0.0437731481481487
15	6.91	6.86324074074074	6.905	-0.0417592592592595	0.0467592592592583
16	6.89	6.92532407407407	6.89416666666667	0.031157407407407	-0.0353240740740741
17	6.88	6.93574074074074	6.88208333333333	0.0536574074074075	-0.0557407407407418
18	6.9	6.94719907407407	6.8725	0.0746990740740737	-0.047199074074074
19	6.91	6.91087962962963	6.86625	0.0446296296296297	-0.000879629629629619
20	6.85	6.9181712962963	6.86416666666667	0.0540046296296298	-0.0681712962962973
21	6.86	6.91462962962963	6.87458333333333	0.0400462962962964	-0.0546296296296296
22	6.82	6.89837962962963	6.8975	0.000879629629629668	-0.0783796296296284
23	6.8	6.90601851851852	6.92625	-0.0202314814814813	-0.106018518518519
24	6.83	6.91025462962963	6.95875	-0.0484953703703697	-0.0802546296296285
25	6.84	6.89310185185185	6.99208333333333	-0.0989814814814815	-0.0531018518518511
26	6.89	6.94497685185185	7.03458333333333	-0.0896064814814817	-0.0549768518518512
27	7.14	7.04532407407407	7.08708333333333	-0.0417592592592595	0.0946759259259258
28	7.21	7.16865740740741	7.1375	0.031157407407407	0.041342592592593
29	7.25	7.24199074074074	7.18833333333333	0.0536574074074075	0.00800925925925888
30	7.31	7.31428240740741	7.23958333333333	0.0746990740740737	-0.00428240740740726
31	7.3	7.3212962962963	7.27666666666667	0.0446296296296297	-0.0212962962962964
32	7.48	7.35775462962963	7.30375	0.0540046296296298	0.12224537037037
33	7.49	7.3662962962963	7.32625	0.0400462962962964	0.123703703703703
34	7.4	7.35171296296296	7.35083333333333	0.000879629629629668	0.0482870370370367
35	7.44	7.36435185185185	7.38458333333333	-0.0202314814814813	0.075648148148149
36	7.42	7.36900462962963	7.4175	-0.0484953703703697	0.0509953703703712
37	7.14	7.35101851851852	7.45	-0.0989814814814815	-0.211018518518518
38	7.24	7.38539351851852	7.475	-0.0896064814814817	-0.145393518518517
39	7.33	7.45074074074074	7.4925	-0.0417592592592595	-0.12074074074074
40	7.61	7.54574074074074	7.51458333333333	0.031157407407407	0.0642592592592601
41	7.66	7.59282407407407	7.53916666666667	0.0536574074074075	0.0671759259259268
42	7.69	7.63636574074074	7.56166666666667	0.0746990740740737	0.0536342592592609
43	7.7	7.6412962962963	7.59666666666667	0.0446296296296297	0.0587037037037037
44	7.68	7.6956712962963	7.64166666666667	0.0540046296296298	-0.015671296296297
45	7.71	7.72046296296296	7.68041666666667	0.0400462962962964	-0.0104629629629622
46	7.71	7.7112962962963	7.71041666666667	0.000879629629629668	-0.00129629629629679
47	7.72	7.71518518518519	7.73541666666667	-0.0202314814814813	0.00481481481481438
48	7.68	7.71108796296296	7.75958333333333	-0.0484953703703697	-0.031087962962963
49	7.72	7.68226851851852	7.78125	-0.0989814814814815	0.0377314814814813
50	7.74	7.71414351851852	7.80375	-0.0896064814814817	0.0258564814814823
51	7.76	7.78324074074074	7.825	-0.0417592592592595	-0.0232407407407402
52	7.9	7.87699074074074	7.84583333333333	0.031157407407407	0.0230092592592603
53	7.97	7.9211574074074	7.8675	0.0536574074074075	0.0488425925925933
54	7.96	7.96219907407407	7.8875	0.0746990740740737	-0.00219907407407405
55	7.95	7.9525462962963	7.90791666666667	0.0446296296296297	-0.00254629629629566
56	7.97	7.98233796296296	7.92833333333333	0.0540046296296298	-0.0123379629629623
57	7.93	7.98837962962963	7.94833333333333	0.0400462962962964	-0.0583796296296288
58	7.99	7.9650462962963	7.96416666666667	0.000879629629629668	0.0249537037037051
59	7.96	7.95810185185185	7.97833333333333	-0.0202314814814813	0.00189814814814859
60	7.92	7.9519212962963	8.00041666666667	-0.0484953703703697	-0.0319212962962965
61	7.97	7.92810185185185	8.02708333333333	-0.0989814814814815	0.0418981481481477
62	7.98	7.96414351851852	8.05375	-0.0896064814814817	0.0158564814814817
63	8	8.04199074074074	8.08375	-0.0417592592592595	-0.04199074074074
64	8.04	8.14324074074074	8.11208333333333	0.031157407407407	-0.103240740740741
65	8.17	8.19074074074074	8.13708333333333	0.0536574074074075	-0.0207407407407398
66	8.29	8.24136574074074	8.16666666666667	0.0746990740740737	0.0486342592592592
67	8.26	8.24212962962963	8.1975	0.0446296296296297	0.0178703703703711
68	8.3	8.2806712962963	8.22666666666667	0.0540046296296298	0.0193287037037049
69	8.32	8.2950462962963	8.255	0.0400462962962964	0.0249537037037051
70	8.28	8.2825462962963	8.28166666666667	0.000879629629629668	-0.00254629629629655
71	8.27	8.28143518518518	8.30166666666667	-0.0202314814814813	-0.011435185185185
72	8.32	8.26233796296296	8.31083333333333	-0.0484953703703697	0.0576620370370389
73	8.31	8.21768518518519	8.31666666666667	-0.0989814814814815	0.0923148148148147
74	8.34	8.23331018518518	8.32291666666667	-0.0896064814814817	0.106689814814816
75	8.32	8.2836574074074	8.32541666666667	-0.0417592592592595	0.0363425925925949
76	8.36	8.35824074074074	8.32708333333333	0.031157407407407	0.00175925925925924
77	8.33	8.38574074074074	8.33208333333333	0.0536574074074075	-0.0557407407407382
78	8.35	8.4067824074074	8.33208333333333	0.0746990740740737	-0.0567824074074075
79	8.34	NA	NA	0.0446296296296297	NA
80	8.37	NA	NA	0.0540046296296298	NA
81	8.31	NA	NA	0.0400462962962964	NA
82	8.33	NA	NA	0.000879629629629668	NA
83	8.34	NA	NA	-0.0202314814814813	NA
84	8.25	NA	NA	-0.0484953703703697	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/1m2ly1291644501.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/1m2ly1291644501.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/2m2ly1291644501.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/2m2ly1291644501.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/3ft211291644501.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/3ft211291644501.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/4ft211291644501.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/06/t1291644473iobz8k2kegg06yq/4ft211291644501.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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