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Data:
97.7 88.9 96.5 89.5 85.4 84.3 83.7 86.2 90.7 95.7 95.6 97 97.2 86.6 88.4 81.4 86.9 84.9 83.7 86.8 88.3 92.5 94.7 94.5 98.7 88.6 95.2 91.3 91.7 89.3 88.7 91.2 88.6 94.6 96 94.3 102 93.4 96.7 93.7 91.6 89.6 92.9 94.1 92 97.5 92.7 100.7 105.9 95.3 99.8 91.3 90.8 87.1 91.4 86.1 87.1 92.6 96.6 105.3 102.4 98.2 98.6 92.6 87.9 84.1 86.7 84.4 86 90.4 92.9 105.8 106 99.1 99.9 88.1 87.8 87.1 85.9 86.5 84.1 92.1 93.3 98.9 103 98.4 100.7 92.3 89 88.9 85.5 90.1 87 97.1 101.5 103 106.1 96.1 94.2 89.1 85.2 86.5 88 88.4 87.9 95.7 94.8 105.2 108.7 96.1 98.3 88.6 90.8 88.1 91.9 98.5 98.6 100.3 98.7 110.7 115.4 105.4 108 94.5 96.5 91 94.1 96.4 93.1 97.5 102.5 105.7 109.1 97.2 100.3 91.3 94.3 89.5 89.3 93.4 91.9 92.9 93.7 100.1 105.5 110.5 89.5 90.4 89.9 84.6 86.2 83.4 82.9 81.8 87.6 94.6 99.6 96.7 99.8 83.8 82.4 86.8 91 85.3 83.6 94 100.3 107.1 100.7 95.5 92.9 79.2 82 79.3 81.5 76 73.1 80.4 82.1 90.5 98.1 89.5 86.5 77 74.7 73.4 72.5 69.3 75.2 83.5 90.5 92.2 110.5 101.8 107.4 95.5 84.5 81.1 86.2 91.5 84.7 92.2 99.2 104.5 113 100.4 101 84.8 86.5 91.7 94.8 95
Seasonal period
12
1
2
3
4
5
6
7
8
9
10
11
12
Seasonal window
(?)
Seasonal degree
(?)
0
1
Trend window
(?)
Trend degree
(?)
1
0
Low-pass window
(?)
Low-pass degree
(?)
1
0
Robust loess fitting
FALSE
TRUE
Chart options
Title:
R Code
par1 <- as.numeric(par1) #seasonal period if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window par3 <- as.numeric(par3) #s.degree if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window par5 <- as.numeric(par5)#t.degree if (par6 != '') par6 <- as.numeric(par6)#l.window par7 <- as.numeric(par7)#l.degree if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust nx <- length(x) x <- ts(x,frequency=par1) if (par6 != '') { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8) } else { m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8) } m$time.series m$win m$deg m$jump m$inner m$outer bitmap(file='test1.png') plot(m,main=main) dev.off() mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend') acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Component',header=TRUE) a<-table.element(a,'Window',header=TRUE) a<-table.element(a,'Degree',header=TRUE) a<-table.element(a,'Jump',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,m$win['s']) a<-table.element(a,m$deg['s']) a<-table.element(a,m$jump['s']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,m$win['t']) a<-table.element(a,m$deg['t']) a<-table.element(a,m$jump['t']) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Low-pass',header=TRUE) a<-table.element(a,m$win['l']) a<-table.element(a,m$deg['l']) a<-table.element(a,m$jump['l']) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observed',header=TRUE) a<-table.element(a,'Fitted',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,'Remainder',header=TRUE) a<-table.row.end(a) for (i in 1:nx) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]+m$time.series[i,'remainder']) a<-table.element(a,m$time.series[i,'seasonal']) a<-table.element(a,m$time.series[i,'trend']) a<-table.element(a,m$time.series[i,'remainder']) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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