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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: Mon, 28 Apr 2008 05:37:16 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2.htm/, Retrieved Mon, 28 Apr 2008 13:39:32 +0200
 
User-defined keywords:
my compet
 
Dataseries X:
» Textbox « » Textfile « » CSV «
13328 12873 14000 13477 14237 13674 13529 14058 12975 14326 14008 16193 14483 14011 15057 14884 15414 14440 14900 15074 14442 15307 14938 17193 15528 14765 15838 15723 16150 15486 15986 15983 15692 16490 15686 18897 16316 15636 17163 16534 16518 16375 16290 16352 15943 16362 16393 19051 16747 16320 17910 16961 17480 17049 16879 17473 16998 17307 17418 20169 17871 17226 19062 17804 19100 18522 18060 18869 18127 18871 18890 21263 19547 18450 20254 19240 20216 19420 19415 20018 18652 19978 19509 21971
 
Text written by user:
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
113328NANA-95.6243055555557NA
212873NANA-770.874305555556NA
314000NANA560.500694444444NA
413477NANA-145.107638888889NA
514237NANA327.534027777778NA
613674NANA-313.399305555556NA
71352913588.709027777813937.9583333333-349.249305555555-59.709027777777
81405813932.259027777814033.5-101.240972222222125.740972222224
91297513433.617361111114124.9583333333-691.340972222222-458.61736111111
101432614083.675694444414227.625-143.949305555555242.324305555559
111400813912.625694444414335.2916666667-422.66597222222295.3743055555587
121619316561.667361111114416.252145.41736111111-368.667361111111
131448314409.667361111114505.2916666667-95.624305555555773.3326388888872
141401113833.875694444414604.75-770.874305555556177.124305555555
151505715268.709027777814708.2083333333560.500694444444-211.709027777777
161488414665.100694444414810.2083333333-145.107638888889218.899305555557
171541415217.367361111114889.8333333333327.534027777778196.632638888892
181444014656.850694444414970.25-313.399305555556-216.850694444443
191490014706.209027777815055.4583333333-349.249305555555193.790972222221
201507415029.175694444415130.4166666667-101.24097222222244.8243055555558
211444214503.034027777815194.375-691.340972222222-61.0340277777777
221530715117.925694444415261.875-143.949305555555189.074305555558
231493814904.834027777815327.5-422.66597222222233.165972222223
241719317547.167361111115401.752145.41736111111-354.167361111109
251552815394.959027777815490.5833333333-95.6243055555557133.040972222221
261476514802.834027777815573.7083333333-770.874305555556-37.8340277777788
271583816224.167361111115663.6666666667560.500694444444-386.167361111111
281572315619.934027777815765.0416666667-145.107638888889103.065972222224
291615016173.034027777815845.5327.534027777778-23.0340277777759
301548615634.267361111115947.6666666667-313.399305555556-148.267361111109
311598615702.250694444416051.5-349.249305555555283.749305555557
321598316019.384027777816120.625-101.240972222222-36.3840277777781
331569215520.784027777816212.125-691.340972222222171.215972222226
341649016157.175694444416301.125-143.949305555555332.824305555556
351568615927.584027777816350.25-422.665972222222-241.584027777773
361889718548.042361111116402.6252145.41736111111348.957638888893
371631616356.709027777816452.3333333333-95.6243055555557-40.7090277777716
381563615709.500694444416480.375-770.874305555556-73.5006944444394
391716317066.709027777816506.2083333333560.50069444444496.2909722222248
401653416366.225694444416511.3333333333-145.107638888889167.774305555558
411651816862.992361111116535.4583333333327.534027777778-344.99236111111
421637516257.934027777816571.3333333333-313.399305555556117.065972222219
431629016246.459027777816595.7083333333-349.24930555555543.5409722222248
441635216540.925694444416642.1666666667-101.240972222222-188.925694444442
451594316010.450694444416701.7916666667-691.340972222222-67.4506944444402
461636216606.759027777816750.7083333333-143.949305555555-244.759027777778
471639316385.917361111116808.5833333333-422.6659722222227.08263888888541
481905119022.167361111116876.752145.4173611111128.8326388888891
491674716833.750694444416929.375-95.6243055555557-86.7506944444431
501632016229.750694444417000.625-770.87430555555690.2493055555569
511791017651.792361111117091.2916666667560.500694444444258.207638888889
521696117029.517361111117174.625-145.107638888889-68.5173611111095
531748017584.242361111117256.7083333333327.534027777778-104.242361111112
541704917032.600694444417346-313.39930555555616.3993055555547
551687917090.167361111117439.4166666667-349.249305555555-211.167361111111
561747317422.759027777817524-101.24097222222250.2409722222219
571699816918.409027777817609.75-691.34097222222279.5909722222241
581730717548.925694444417692.875-143.949305555555-241.925694444446
591741817372.834027777817795.5-422.66597222222245.1659722222212
602016920069.792361111117924.3752145.4173611111199.207638888889
611787117939.334027777818034.9583333333-95.6243055555557-68.3340277777752
621722617371.459027777818142.3333333333-770.874305555556-145.459027777775
631906218808.042361111118247.5416666667560.500694444444253.957638888893
641780418214.642361111118359.75-145.107638888889-410.642361111109
651910018813.784027777818486.25327.534027777778286.215972222220
661852218279.767361111118593.1666666667-313.399305555556242.232638888891
671806018359.334027777818708.5833333333-349.249305555555-299.334027777772
681886918728.175694444418829.4166666667-101.240972222222140.824305555558
691812718238.742361111118930.0833333333-691.340972222222-111.742361111112
701887118895.634027777819039.5833333333-143.949305555555-24.6340277777781
711889018723.250694444419145.9166666667-422.665972222222166.749305555557
722126321375.250694444419229.83333333332145.41736111111-112.250694444443
731954719228.084027777819323.7083333333-95.6243055555557318.915972222225
741845018657.167361111119428.0416666667-770.874305555556-207.167361111104
752025420058.292361111119497.7916666667560.500694444444195.707638888889
761924019420.684027777819565.7916666667-145.107638888889-180.684027777777
772021619965.242361111119637.7083333333327.534027777778250.757638888888
781942019379.600694444419693-313.39930555555640.3993055555547
7919415NANA-349.249305555555NA
8020018NANA-101.240972222222NA
8118652NANA-691.340972222222NA
8219978NANA-143.949305555555NA
8319509NANA-422.665972222222NA
8421971NANA2145.41736111111NA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/1qiiu1209382634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/1qiiu1209382634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/2ke6u1209382634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/2ke6u1209382634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/3uspq1209382634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/3uspq1209382634.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/4nslq1209382634.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209382753h66n7s5uhhf68n2/4nslq1209382634.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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,m$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')
 





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