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Data:
8.64 8.89 8.87 8.81 8.87 9.06 9.12 8.66 8.17 8.04 7.71 7.55 7.52 7.38 7.52 7.31 6.92 7.09 7.05 7.37 7.05 6.79 6.35 6.44 6.89 7.16 7.46 7.91 7.86 8.02 8.38 8.50 8.40 8.24 8.33 8.28 8.15 8.06 7.79 7.28 7.52 7.23 7.13 7.21 6.99 6.77 6.69 6.39 6.85 6.74 6.56 6.62 6.71 6.67 6.54 6.14 6.13 5.86 5.88 5.75 5.53 5.86 5.90 5.95 5.69 5.53 5.71 5.60 5.73 5.60 5.41 5.13 5.00 5.04 5.10 4.96 4.90 4.80 4.48 4.29 4.27 4.18 4.02 3.82 4.13 4.16 3.98 4.26 4.70 4.96 5.13 5.35 5.41 5.42 5.51 5.75 5.67 5.46 5.56 5.56 5.54 5.53 5.65 5.58 5.57 5.36 5.23 5.11 5.07 5.04 5.34 5.43 5.31 5.12 4.97 5.00 4.64 4.80 5.10 5.11 5.12 5.36 5.26 5.27 5.10 4.94 4.68 4.41 4.60 4.53 4.18 4.00 3.87 4.09 4.13 3.74 3.81 4.11 4.14 3.99 4.28 4.37 4.24 4.19 4.01 3.95 4.30 4.37 4.40 4.29 4.12 4.07 3.93 3.79 3.67 3.53 3.69 3.69 3.48 3.31 3.16 3.25 3.14 3.19 3.43 3.45 3.31 3.51 3.53 3.83 4.02 3.99 4.11 3.96 3.83 3.71 3.81 3.73 3.99 4.17 4.00 4.10 4.24 4.45 4.62 4.49 4.45 4.49 4.36 4.32 4.45 4.13 4.14 4.30 4.42 4.67 4.96 4.73 4.52 4.36 4.15 3.92 3.88 4.20 3.95 3.78 3.69 3.77 3.66 3.53 3.50 3.14 3.42 3.30 2.81 3.15 3.37 4.05 4.00 4.20 4.21 4.24 4.24 4.17 4.12 4.35 3.98 3.62 4.39 5.01 4.07 3.70 3.59 3.44 3.33 2.98 3.14 2.55 2.49 2.53 2.43
Seasonal period
12
12
1
2
3
4
5
6
7
8
9
10
11
12
Seasonal window
(?)
Seasonal degree
(?)
0
0
1
Trend window
(?)
Trend degree
(?)
1
1
0
Low-pass window
(?)
Low-pass degree
(?)
1
1
0
Robust loess fitting
FALSE
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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