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Data:
1189593.60 1185163.20 1180670.40 1171372.80 1263350.40 1258483.20 1189593.60 1143792.00 1148222.40 1148222.40 1153152.00 1162012.80 1175803.20 1175803.20 1166942.40 1143792.00 1263350.40 1281571.20 1254052.80 1189593.60 1217174.40 1175803.20 1194460.80 1203384.00 1212681.60 1189593.60 1194460.80 1162012.80 1263350.40 1295361.60 1267843.20 1217174.40 1272273.60 1212681.60 1267843.20 1263350.40 1277140.80 1226472.00 1281571.20 1277140.80 1359820.80 1341163.20 1267843.20 1230902.40 1281571.20 1212681.60 1263350.40 1272273.60 1290931.20 1249622.40 1272273.60 1286064.00 1336732.80 1295361.60 1240262.40 1180670.40 1235832.00 1084200.00 1157582.40 1198891.20 1240262.40 1180670.40 1180670.40 1180670.40 1212681.60 1166942.40 1106913.60 1056681.60 1093123.20 950851.20 1038024.00 1088692.80 1097990.40 1047321.60 1051752.00 1038024.00 1084200.00 1051752.00 987792.00 941553.60 1019740.80 849950.40 960211.20 1010443.20 1010443.20 950851.20 895752.00 891321.60 941553.60 895752.00 808641.60 748612.80 813072.00 661502.40 799281.60 872601.60 895752.00 845083.20 781060.80 826862.40 845083.20 831292.80 693451.20 629491.20 675230.40 537451.20 679723.20 730392.00 771700.80 702811.20 638352.00 675230.40 693451.20 657009.60 519230.40 459201.60 514300.80 362731.20 528091.20 629491.20
Type of Seasonality
0.0112482002001212multiplicativeadditivemultiplicativeadditivemultiplicativemultiplicative
additive
multiplicative
Seasonal Period
0.99155121212121212
12
1
2
3
4
5
6
7
8
9
10
11
12
Chart options
R Code
par2 <- '12' par1 <- 'multiplicative' 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$trend)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6)) a<-table.element(a,signif(m$trend[i],6)) a<-table.element(a,signif(m$seasonal[i],6)) a<-table.element(a,signif(m$random[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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0 seconds
R Server
Big Analytics Cloud Computing Center
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