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

Title produced by software: Classical Decomposition

Date of computation: Wed, 27 Jan 2010 02:56:28 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy.htm/, Retrieved Wed, 27 Jan 2010 10:58:13 +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/Jan/27/t1264586288x5f4d1umme730uy.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 «

1,61 1,58 1,69 1,78 1,76 1,83 1,8 1,57 1,45 1,4 1,55 1,58 1,58 1,59 1,8 1,99 2,06 2,06 2,08 2 1,85 1,77 1,7 1,66 1,67 1,73 1,91 2,02 2,07 2,15 2,1 1,68 1,68 1,65 1,72 1,73 1,76 1,84 1,99 2,05 2,12 2,13 2,08 1,88 1,81 1,81 1,88 1,87 1,87 1,9 2,01 2,05 2,16 2,18 2,15 2,12 2,04 2,04 2,06 1,93 1,86 1,94 2,35 2,46 2,59 2,66 2,41 2,18 2,13 2,11 2,12 2,16 2,07 2,2 2,29 2,32 2,37 2,38 2,38 2,28 2,22 2,25 2,3 2,3 2,23 2,27 2,3 2,32 2,41 2,43 2,45 2,47 2,46 2,5 2,46 2,43 2,37 2,45 2,53 2,56 2,62 2,67 2,62 2,6 2,53 2,49 2,48 2,44

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	1.61	NA	NA	-0.154939236111111	NA
2	1.58	NA	NA	-0.100824652777778	NA
3	1.69	NA	NA	0.0456857638888889	NA
4	1.78	NA	NA	0.108133680555556	NA
5	1.76	NA	NA	0.176362847222222	NA
6	1.83	NA	NA	0.199539930555556	NA
7	1.8	1.78401909722222	1.63208333333333	0.151935763888889	0.0159809027777778
8	1.57	1.61594618055556	1.63125	-0.0153038194444445	-0.0459461805555557
9	1.45	1.54453993055556	1.63625	-0.0917100694444444	-0.0945399305555557
10	1.4	1.53568576388889	1.64958333333333	-0.113897569444444	-0.135685763888889
11	1.55	1.58089409722222	1.67083333333333	-0.0899392361111112	-0.0308940972222218
12	1.58	1.57787326388889	1.69291666666667	-0.115043402777778	0.00212673611111147
13	1.58	1.55922743055556	1.71416666666667	-0.154939236111111	0.0207725694444447
14	1.59	1.64292534722222	1.74375	-0.100824652777778	-0.052925347222222
15	1.8	1.82401909722222	1.77833333333333	0.0456857638888889	-0.0240190972222218
16	1.99	1.91855034722222	1.81041666666667	0.108133680555556	0.071449652777778
17	2.06	2.00844618055556	1.83208333333333	0.176362847222222	0.0515538194444447
18	2.06	2.04120659722222	1.84166666666667	0.199539930555556	0.0187934027777779
19	2.08	2.00068576388889	1.84875	0.151935763888889	0.0793142361111112
20	2	1.84302951388889	1.85833333333333	-0.0153038194444445	0.156970486111112
21	1.85	1.77703993055556	1.86875	-0.0917100694444444	0.0729600694444448
22	1.77	1.76068576388889	1.87458333333333	-0.113897569444444	0.00931423611111093
23	1.7	1.78631076388889	1.87625	-0.0899392361111112	-0.086310763888889
24	1.66	1.76537326388889	1.88041666666667	-0.115043402777778	-0.105373263888889
25	1.67	1.73006076388889	1.885	-0.154939236111111	-0.0600607638888888
26	1.73	1.77167534722222	1.8725	-0.100824652777778	-0.041675347222222
27	1.91	1.89776909722222	1.85208333333333	0.0456857638888889	0.0122309027777783
28	2.02	1.94813368055556	1.84	0.108133680555556	0.0718663194444444
29	2.07	2.01219618055556	1.83583333333333	0.176362847222222	0.0578038194444448
30	2.15	2.03912326388889	1.83958333333333	0.199539930555556	0.110876736111111
31	2.1	1.99818576388889	1.84625	0.151935763888889	0.101814236111111
32	1.68	1.83927951388889	1.85458333333333	-0.0153038194444445	-0.159279513888889
33	1.68	1.77078993055556	1.8625	-0.0917100694444444	-0.090789930555556
34	1.65	1.75318576388889	1.86708333333333	-0.113897569444444	-0.103185763888889
35	1.72	1.78047743055556	1.87041666666667	-0.0899392361111112	-0.0604774305555553
36	1.73	1.75662326388889	1.87166666666667	-0.115043402777778	-0.0266232638888888
37	1.76	1.71506076388889	1.87	-0.154939236111111	0.0449392361111114
38	1.84	1.77667534722222	1.8775	-0.100824652777778	0.063324652777778
39	1.99	1.93693576388889	1.89125	0.0456857638888889	0.0530642361111111
40	2.05	2.01146701388889	1.90333333333333	0.108133680555556	0.038532986111111
41	2.12	2.09302951388889	1.91666666666667	0.176362847222222	0.0269704861111111
42	2.13	2.12870659722222	1.92916666666667	0.199539930555556	0.00129340277777779
43	2.08	2.09151909722222	1.93958333333333	0.151935763888889	-0.0115190972222221
44	1.88	1.93136284722222	1.94666666666667	-0.0153038194444445	-0.0513628472222223
45	1.81	1.85828993055556	1.95	-0.0917100694444444	-0.0482899305555557
46	1.81	1.83693576388889	1.95083333333333	-0.113897569444444	-0.0269357638888890
47	1.88	1.86256076388889	1.9525	-0.0899392361111112	0.0174392361111111
48	1.87	1.84120659722222	1.95625	-0.115043402777778	0.0287934027777776
49	1.87	1.80631076388889	1.96125	-0.154939236111111	0.0636892361111108
50	1.9	1.87334201388889	1.97416666666667	-0.100824652777778	0.0266579861111111
51	2.01	2.03943576388889	1.99375	0.0456857638888889	-0.0294357638888887
52	2.05	2.12105034722222	2.01291666666667	0.108133680555556	-0.0710503472222224
53	2.16	2.20636284722222	2.03	0.176362847222222	-0.0463628472222213
54	2.18	2.23953993055556	2.04	0.199539930555556	-0.0595399305555555
55	2.15	2.19401909722222	2.04208333333333	0.151935763888889	-0.0440190972222223
56	2.12	2.02802951388889	2.04333333333333	-0.0153038194444445	0.0919704861111112
57	2.04	1.96745659722222	2.05916666666667	-0.0917100694444444	0.0725434027777778
58	2.04	1.97651909722222	2.09041666666667	-0.113897569444444	0.063480902777778
59	2.06	2.03547743055555	2.12541666666667	-0.0899392361111112	0.0245225694444451
60	1.93	2.04828993055556	2.16333333333333	-0.115043402777778	-0.118289930555556
61	1.86	2.03922743055556	2.19416666666667	-0.154939236111111	-0.179227430555555
62	1.94	2.10667534722222	2.2075	-0.100824652777778	-0.166675347222222
63	2.35	2.25943576388889	2.21375	0.0456857638888889	0.0905642361111112
64	2.46	2.32855034722222	2.22041666666667	0.108133680555556	0.131449652777778
65	2.59	2.40219618055556	2.22583333333333	0.176362847222222	0.187803819444444
66	2.66	2.43745659722222	2.23791666666667	0.199539930555556	0.222543402777778
67	2.41	2.40818576388889	2.25625	0.151935763888889	0.00181423611111109
68	2.18	2.26052951388889	2.27583333333333	-0.0153038194444445	-0.080529513888889
69	2.13	2.19245659722222	2.28416666666667	-0.0917100694444444	-0.0624565972222224
70	2.11	2.16193576388889	2.27583333333333	-0.113897569444444	-0.0519357638888889
71	2.12	2.17089409722222	2.26083333333333	-0.0899392361111112	-0.0508940972222223
72	2.16	2.12495659722222	2.24	-0.115043402777778	0.0350434027777782
73	2.07	2.07214409722222	2.22708333333333	-0.154939236111111	-0.00214409722222264
74	2.2	2.12917534722222	2.23	-0.100824652777778	0.070824652777778
75	2.29	2.28360243055556	2.23791666666667	0.0456857638888889	0.00639756944444425
76	2.32	2.35563368055556	2.2475	0.108133680555556	-0.0356336805555553
77	2.37	2.43719618055556	2.26083333333333	0.176362847222222	-0.0671961805555559
78	2.38	2.47370659722222	2.27416666666667	0.199539930555556	-0.0937065972222224
79	2.38	2.43860243055556	2.28666666666667	0.151935763888889	-0.0586024305555557
80	2.28	2.28094618055556	2.29625	-0.0153038194444445	-0.000946180555555287
81	2.22	2.20787326388889	2.29958333333333	-0.0917100694444444	0.0121267361111115
82	2.25	2.18610243055556	2.3	-0.113897569444444	0.0638975694444448
83	2.3	2.21172743055555	2.30166666666667	-0.0899392361111112	0.0882725694444448
84	2.3	2.19037326388889	2.30541666666667	-0.115043402777778	0.109626736111111
85	2.23	2.15547743055556	2.31041666666667	-0.154939236111111	0.0745225694444445
86	2.27	2.22042534722222	2.32125	-0.100824652777778	0.0495746527777778
87	2.3	2.38485243055556	2.33916666666667	0.0456857638888889	-0.0848524305555554
88	2.32	2.46771701388889	2.35958333333333	0.108133680555556	-0.147717013888889
89	2.41	2.55302951388889	2.37666666666667	0.176362847222222	-0.143029513888889
90	2.43	2.58828993055556	2.38875	0.199539930555556	-0.158289930555556
91	2.45	2.55193576388889	2.4	0.151935763888889	-0.101935763888889
92	2.47	2.39802951388889	2.41333333333333	-0.0153038194444445	0.0719704861111117
93	2.46	2.33870659722222	2.43041666666667	-0.0917100694444444	0.121293402777778
94	2.5	2.33610243055556	2.45	-0.113897569444444	0.163897569444445
95	2.46	2.37881076388889	2.46875	-0.0899392361111112	0.0811892361111108
96	2.43	2.37245659722222	2.4875	-0.115043402777778	0.0575434027777781
97	2.37	2.34964409722222	2.50458333333333	-0.154939236111111	0.0203559027777773
98	2.45	2.41625868055556	2.51708333333333	-0.100824652777778	0.0337413194444447
99	2.53	2.57110243055556	2.52541666666667	0.0456857638888889	-0.0411024305555556
100	2.56	2.63605034722222	2.52791666666667	0.108133680555556	-0.0760503472222216
101	2.62	2.70469618055556	2.52833333333333	0.176362847222222	-0.084696180555556
102	2.67	2.72912326388889	2.52958333333333	0.199539930555556	-0.0591232638888886
103	2.62	NA	NA	0.151935763888889	NA
104	2.6	NA	NA	-0.0153038194444445	NA
105	2.53	NA	NA	-0.0917100694444444	NA
106	2.49	NA	NA	-0.113897569444444	NA
107	2.48	NA	NA	-0.0899392361111112	NA
108	2.44	NA	NA	-0.115043402777778	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/158a71264586186.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/158a71264586186.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/2ap8m1264586186.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/2ap8m1264586186.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/3hi7p1264586186.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/3hi7p1264586186.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/4udww1264586186.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264586288x5f4d1umme730uy/4udww1264586186.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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