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opgave9bW.Verlinden

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 05 Jun 2009 08:07:30 -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/05/t1244210939yptuvcv8bl59g55.htm/, Retrieved Fri, 05 Jun 2009 16:08:59 +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/05/t1244210939yptuvcv8bl59g55.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

665272 661735 621014 574889 677734 717075 653612 690697 665864 830701 789303 617808 805775 909449 599973 955874 799494 876097 823300 900079 860754 923882 1121084 741757 966066 901978 648659 852732 706036 835792 722489 714262 739459 816834 743082 683375 1006000 866000 644000 703000 699000 713000 688000 672000 600000 847000 697000 687000 973000 796000 658000 709000 798000 820000 776000 699000 828433 942131 792916 864942 982689 948143 874863 735794 854605 1284216 961585 818379 1079498 1095091 1008925 967118 1127715

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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	665272	NA	NA	139904.652777778	NA
2	661735	NA	NA	73882.1944444445	NA
3	621014	NA	NA	-129843.772222222	NA
4	574889	NA	NA	-29312.9722222222	NA
5	677734	NA	NA	-53199.4055555555	NA
6	717075	NA	NA	76453.4944444445	NA
7	653612	645643.169444444	686329.625	-40686.4555555555	7968.83055555564
8	690697	650995.669444444	702505.333333333	-51509.6638888889	39701.3305555556
9	665864	670670.036111111	711950.041666667	-41280.0055555556	-4806.03611111105
10	830701	778595.611111111	726947.708333333	51647.9027777778	52105.3888888889
11	789303	795732.927777778	747895.416666667	47837.5111111111	-6429.92777777766
12	617808	715701.186111111	759594.666666667	-43893.4805555556	-97893.186111111
13	805775	913195.569444444	773290.916666667	139904.652777778	-107420.569444444
14	909449	862967.694444444	789085.5	73882.1944444445	46481.3055555556
15	599973	676086.394444444	805930.166666667	-129843.772222222	-76113.3944444444
16	955874	788620.152777778	817933.125	-29312.9722222222	167253.847222222
17	799494	782440.469444444	835639.875	-53199.4055555555	17053.5305555556
18	876097	931082.119444444	854628.625	76453.4944444445	-54985.1194444443
19	823300	825785.502777778	866471.958333333	-40686.4555555555	-2485.50277777773
20	900079	821329.794444444	872839.458333333	-51509.6638888889	78749.2055555556
21	860754	833276.744444444	874556.75	-41280.0055555556	27477.2555555556
22	923882	923935.652777778	872287.75	51647.9027777778	-53.6527777778683
23	1121084	911933.594444444	864096.083333333	47837.5111111111	209150.405555555
24	741757	814629.144444444	858522.625	-43893.4805555556	-72872.1444444444
25	966066	992547.444444444	852642.791666667	139904.652777778	-26481.4444444444
26	901978	914582.152777778	840699.958333333	73882.1944444445	-12604.1527777778
27	648659	698059.852777778	827903.625	-129843.772222222	-49400.8527777777
28	852732	789076.361111111	818389.333333333	-29312.9722222222	63655.6388888889
29	706036	744979.511111111	798178.916666667	-53199.4055555555	-38943.5111111113
30	835792	856449.744444444	779996.25	76453.4944444445	-20657.7444444443
31	722489	738541.127777778	779227.583333333	-40686.4555555555	-16052.1277777777
32	714262	727882.752777778	779392.416666667	-51509.6638888889	-13620.7527777777
33	739459	736419.202777778	777699.208333333	-41280.0055555556	3039.7972222222
34	816834	822914.152777778	771266.25	51647.9027777778	-6080.15277777775
35	743082	812571.761111111	764734.25	47837.5111111111	-69489.761111111
36	683375	715431.269444444	759324.75	-43893.4805555556	-32056.2694444444
37	1006000	892676.027777778	752771.375	139904.652777778	113323.972222222
38	866000	823455.611111111	749573.416666667	73882.1944444445	42544.3888888889
39	644000	612157.936111111	742001.708333333	-129843.772222222	31842.0638888889
40	703000	708134.861111111	737447.833333333	-29312.9722222222	-5134.86111111101
41	699000	683585.261111111	736784.666666667	-53199.4055555555	15414.7388888889
42	713000	811469.119444444	735015.625	76453.4944444445	-98469.1194444444
43	688000	693105.211111111	733791.666666667	-40686.4555555555	-5105.21111111098
44	672000	677990.336111111	729500	-51509.6638888889	-5990.3361111111
45	6e+05	685886.661111111	727166.666666667	-41280.0055555556	-85886.661111111
46	847000	779647.902777778	728000	51647.9027777778	67352.0972222224
47	697000	780212.511111111	732375	47837.5111111111	-83212.511111111
48	687000	697064.852777778	740958.333333333	-43893.4805555556	-10064.8527777778
49	973000	888987.986111111	749083.333333333	139904.652777778	84012.013888889
50	796000	827757.194444444	753875	73882.1944444445	-31757.1944444445
51	658000	634674.269444444	764518.041666667	-129843.772222222	23325.7305555556
52	709000	748686.902777778	777999.875	-29312.9722222222	-39686.9027777778
53	798000	732760.761111111	785960.166666667	-53199.4055555555	65239.2388888889
54	820000	873824.411111111	797370.916666667	76453.4944444445	-53824.4111111112
55	776000	764502.419444444	805188.875	-40686.4555555555	11497.5805555555
56	699000	760422.211111111	811931.875	-51509.6638888889	-61422.2111111111
57	828433	786027.119444444	827307.125	-41280.0055555556	42405.8805555556
58	942131	889107.402777778	837459.5	51647.9027777778	53023.5972222222
59	792916	888771.969444444	840934.458333333	47837.5111111111	-95855.9694444444
60	864942	818741.852777778	862635.333333333	-43893.4805555556	46200.1472222223
61	982689	1029615.02777778	889710.375	139904.652777778	-46926.0277777779
62	948143	976299.402777778	902417.208333333	73882.1944444445	-28156.4027777779
63	874863	788008.602777778	917852.375	-129843.772222222	86854.3972222223
64	735794	905373.777777778	934686.75	-29312.9722222222	-169579.777777778
65	854605	896861.052777778	950060.458333333	-53199.4055555555	-42256.0527777777
66	1284216	1039771.66111111	963318.166666667	76453.4944444445	244444.338888889
67	961585	932931.794444444	973618.25	-40686.4555555555	28653.2055555555
68	818379	NA	NA	-51509.6638888889	NA
69	1079498	NA	NA	-41280.0055555556	NA
70	1095091	NA	NA	51647.9027777778	NA
71	1008925	NA	NA	47837.5111111111	NA
72	967118	NA	NA	-43893.4805555556	NA
73	1127715	NA	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/14yam1244210846.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/14yam1244210846.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/2mzoj1244210846.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/2mzoj1244210846.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/3cpmo1244210846.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/3cpmo1244210846.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/4ww2m1244210846.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/05/t1244210939yptuvcv8bl59g55/4ww2m1244210846.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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