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*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: Wed, 15 Dec 2010 19:20:11 +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/15/t1292440691kmymzlh6kwz805o.htm/, Retrieved Wed, 15 Dec 2010 20:18:15 +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/15/t1292440691kmymzlh6kwz805o.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 «

130 127 122 117 112 113 149 157 157 147 137 132 125 123 117 114 111 112 144 150 149 134 123 116 117 111 105 102 95 93 124 130 124 115 106 105 105 101 95 93 84 87 116 120 117 109 105 107 109 109 108 107 99 103 131 137 135 124 118 121 121

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	130	NA	NA	-2.95659722222222	NA
2	127	NA	NA	-5.56076388888889	NA
3	122	NA	NA	-9.87326388888889	NA
4	117	NA	NA	-11.6545138888889	NA
5	112	NA	NA	-17.9670138888889	NA
6	113	NA	NA	-16.1545138888889	NA
7	149	147.126736111111	133.125	14.0017361111111	1.87326388888889
8	157	151.595486111111	132.75	18.8454861111111	5.40451388888889
9	157	151.053819444444	132.375	18.6788194444444	5.94618055555554
10	147	142.980902777778	132.041666666667	10.9392361111111	4.01909722222223
11	137	134.595486111111	131.875	2.72048611111112	2.40451388888889
12	132	130.772569444444	131.791666666667	-1.01909722222222	1.22743055555557
13	125	128.585069444444	131.541666666667	-2.95659722222222	-3.58506944444444
14	123	125.480902777778	131.041666666667	-5.56076388888889	-2.48090277777777
15	117	120.543402777778	130.416666666667	-9.87326388888889	-3.54340277777777
16	114	117.887152777778	129.541666666667	-11.6545138888889	-3.8871527777778
17	111	110.449652777778	128.416666666667	-17.9670138888889	0.550347222222229
18	112	111.012152777778	127.166666666667	-16.1545138888889	0.987847222222214
19	144	140.168402777778	126.166666666667	14.0017361111111	3.83159722222223
20	150	144.178819444444	125.333333333333	18.8454861111111	5.82118055555556
21	149	143.012152777778	124.333333333333	18.6788194444444	5.98784722222221
22	134	134.272569444444	123.333333333333	10.9392361111111	-0.272569444444443
23	123	124.887152777778	122.166666666667	2.72048611111112	-1.88715277777777
24	116	119.689236111111	120.708333333333	-1.01909722222222	-3.68923611111113
25	117	116.126736111111	119.083333333333	-2.95659722222222	0.873263888888872
26	111	111.855902777778	117.416666666667	-5.56076388888889	-0.855902777777786
27	105	105.668402777778	115.541666666667	-9.87326388888889	-0.668402777777786
28	102	102.053819444444	113.708333333333	-11.6545138888889	-0.0538194444444287
29	95	94.2413194444444	112.208333333333	-17.9670138888889	0.758680555555557
30	93	94.8871527777778	111.041666666667	-16.1545138888889	-1.88715277777777
31	124	124.085069444444	110.083333333333	14.0017361111111	-0.0850694444444429
32	130	128.012152777778	109.166666666667	18.8454861111111	1.98784722222223
33	124	127.012152777778	108.333333333333	18.6788194444444	-3.01215277777776
34	115	118.480902777778	107.541666666667	10.9392361111111	-3.48090277777776
35	106	109.428819444444	106.708333333333	2.72048611111112	-3.42881944444441
36	105	104.980902777778	106	-1.01909722222222	0.0190972222222427
37	105	102.460069444444	105.416666666667	-2.95659722222222	2.53993055555556
38	101	99.1059027777778	104.666666666667	-5.56076388888889	1.89409722222223
39	95	94.0850694444444	103.958333333333	-9.87326388888889	0.914930555555557
40	93	91.7621527777778	103.416666666667	-11.6545138888889	1.23784722222223
41	84	85.1579861111111	103.125	-17.9670138888889	-1.15798611111113
42	87	87.0121527777778	103.166666666667	-16.1545138888889	-0.0121527777777857
43	116	117.418402777778	103.416666666667	14.0017361111111	-1.41840277777779
44	120	122.762152777778	103.916666666667	18.8454861111111	-2.76215277777779
45	117	123.470486111111	104.791666666667	18.6788194444444	-6.4704861111111
46	109	116.855902777778	105.916666666667	10.9392361111111	-7.85590277777779
47	105	109.845486111111	107.125	2.72048611111112	-4.84548611111111
48	107	107.397569444444	108.416666666667	-1.01909722222222	-0.397569444444443
49	109	106.751736111111	109.708333333333	-2.95659722222222	2.2482638888889
50	109	105.480902777778	111.041666666667	-5.56076388888889	3.51909722222223
51	108	102.626736111111	112.5	-9.87326388888889	5.3732638888889
52	107	102.220486111111	113.875	-11.6545138888889	4.77951388888889
53	99	97.0746527777778	115.041666666667	-17.9670138888889	1.92534722222223
54	103	100.012152777778	116.166666666667	-16.1545138888889	2.98784722222224
55	131	131.251736111111	117.25	14.0017361111111	-0.2517361111111
56	137	NA	NA	18.8454861111111	NA
57	135	NA	NA	18.6788194444444	NA
58	124	NA	NA	10.9392361111111	NA
59	118	NA	NA	2.72048611111112	NA
60	121	NA	NA	-1.01909722222222	NA
61	121	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/1sox21292440808.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/1sox21292440808.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/2sox21292440808.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/2sox21292440808.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/3lxwm1292440808.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/3lxwm1292440808.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/4dowp1292440808.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/15/t1292440691kmymzlh6kwz805o/4dowp1292440808.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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