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Data:
42.33600 42.14710 40.25640 39.18980 39.13170 38.15070 38.27070 39.13350 40.12190 41.28450 42.57490 43.90190 43.18350 43.61880 44.76240 45.19720 44.38810 43.55520 43.56780 44.21350 45.14510 45.80790 42.32820 37.89990 34.79640 35.21440 36.37270 36.25020 36.82610 36.77230 36.90420 37.04940 36.82590 36.13570 36.03000 35.79270 35.91740 35.40080 35.17230 34.92110 35.02920 34.77390 34.89990 34.90540 34.56800 34.40600 34.45780 34.73160 34.26020 33.88490 34.05490 34.27550 34.13930 34.15870 34.53860 33.79870 33.49730 33.68020 34.32840 34.15380 33.91840 34.32620 34.77500 35.01190 34.55130 34.69510 35.47300 35.97940 36.47890 36.39100 36.67040 37.41620 37.11850 36.30010 35.70020 35.58590 35.67770 35.24080 34.80160 34.43890 34.98810 36.06800 36.35660 36.12540 34.87100 35.21990 34.33900 33.82340 34.51990 35.53000 35.79660 33.84840 33.98710 34.11610 33.82350 32.45400 31.87740 31.11500 31.04360 30.88680 31.30010 30.05070 28.67990 27.64380 27.23940 26.85490 27.01580 26.91880 26.49660 26.78500 26.83980 26.44780 25.17280 24.87840 25.40150 25.77160 26.11810 26.3969 26.65710 25.18390 23.83940 23.86190 24.25810 25.10980 26.16170 26.80870 25.65770 27.09820 27.46650 28.28900 28.69330 27.24010 27.27980 27.64040 26.83100 26.24670 25.22120 25.36530 26.25920 27.22790 26.33150 25.89810 26.68980
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 <- 5 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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R Server
Big Analytics Cloud Computing Center
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