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Data:
93.87 94.07 94.22 94.38 94.74 94.77 94.98 95.23 95.32 95.4 95.61 95.91 96.26 96.55 96.47 96.21 96.24 96.14 95.92 95.81 95.69 95.9 96.12 95.92 95.98 95.92 96.12 96 96.19 96.29 96.34 96.36 96.42 96.88 96.9 96.93 96.87 96.93 97.05 97.11 96.96 97.09 97.32 97.37 97.45 97.74 97.73 97.76 97.86 98.01 98.08 98.07 98.21 98.37 98.47 98.57 98.54 98.38 98.56 98.66 98.74 98.86 98.75 98.89 99.02 99.1 99.03 98.95 98.95 99.29 99.23 99.18 99.14 99.06 99.2 99 98.91 98.93 99.03 98.87 98.8 98.84 99 99.24 99.4 99.53 99.57 99.58 99.79 99.78 99.91 99.8 99.82 99.92 99.87 99.74 99.38 99.26 99.21 99.46 99.63 99.57 99.57 99.6 99.52 99.36 99.29 99.43 99.78 99.87 100.05 100.31 100.52 100.56 100.57 100.57 100.57 100.76 100.73 100.7 100.7 100.7 100.92 101.38 101.82 102.19 102.49 102.85 102.78 102.72 102.78 102.73 102.84 102.78 102.74 102.61 102.38 102.38 102.3 102.19 102.11 102.1 102.16 102.26 102.32 102.31 102.16 102.13 102.06 102.18 102.2 102.18 102.07 102.11 102.23 102.38 102.47 102.47 102.56 102.64 102.64 102.76 102.98 103.19 103.31 103.47 103.79 104.01 104.36 104.49 104.54 104.59 104.63 104.77 105.14 105.19 105.33 105.37 105.49 105.62 105.87 105.9 106.03 106.11 106.23 106.63 106.63 106.63 106.75 106.78 106.61 106.74 106.7 106.82 107.13 107.26 107.21 107.05 107.35 107.43 107.31 107.38 107.5 107.09 106.64 106.88 106.96 107.04 106.75 106.62 106.33 105.12 105.78 105.9 106.32 106.32 106.53 106.36 106.38 105.7 105.03 104.4 104.4 104.39 104.77 105.24 105.24 105.38 105.26 105.33 105.47 105.67 105.41 105.37 105.21 105.37 105.51 105.6 105.54 105.61 105.68 105.77 105.99 106.15 106.15 106.04 106.05 106.28 106.31 106.1 105.81 105.6 105.64 105.78 105.9 106.11 106.25 106.49 106.59 106.57 106.44 106.13 105.87 106.13 106.56 106.75 106.86 106.81 106.82 106.84 107.03 107.23 107.32 107.31 107.35 107.42 107.39 107.51 107.44 107.65 107.71 107.8 107.97 108.04 108.16 108.29 108.43 108.54 108.48 108.36 108.34 108.4 108.54 108.39 108.65 108.74 108.68 108.92 109.16 109.29 109.36 109.29 109.43 109.53 109.45 109.09 109.09 109.32 109.23 108.88 108.87 108.87 108.87 108.83 108.75 108.61 108.41 108.42 108.52 108.83 108.81 109.09 109.34 109.59 109.69 109.64 109.67 109.79 109.6 109.69 109.66 109.67 109.84 109.88 109.67 109.66 109.63 109.63 109.76 109.36 109.6 109.86 109.88 109.96 109.88 109.48 109.06 109.3 108.72 108.84 109.17 109 108.84 108.5 108.64 108.78 108.34 108.09 107.8 108.11 108.64 108.99 109.18 109.27 109.2 109.24 109.33 109.37 109.36 109.37 109.47 109.53 109.99 110.45 110.77 110.83 110.83 110.37 110.67 110.95 110.71 110.71 110.57 111.16 111.03 111.15 111.56 111.52 111.05 111.79 112.04 111.42 111.15 111.56 111.67 110.77 110.17 110.28 110.59 110.57 111.1 110.9 110.73 110.67 111.06 110.93 111.21 111.27 111.53 111.43 111.19 111.16 111.35 111.56 111.33 111.5 111.71 111.64 111.41 111.22 110.91 110.78 111.27 111.65 111.48 111.34 111.19 111.06 110.89 111.05 111.05 110.77 110.53 110 109.39 109.47 109.47 109.48 109.92 109.84 110.12 110.32 110.38 110.36 110.34 110.61 110.32 110.41 110.75 111.02 110.94 111.06 110.89 110.83 110.84 110.8 110.77 110.9 110.95 110.86 110.89 110.89 110.89 111.24 111.36 111.08 111.23 111.46 111.46 111.45 111.11 111.51 112 112.55 112.44 112.23 112.35 112.13 112.08 112.12 112.17 112.06 112.43 112.22 112.06 112.49 112.78 112.93 112.98 112.92 112.92 112.03 111.83 111.73 111.55 111.48 111.91 111.91 111.99 111.85 111.8 111.63 111.21 111.22 111.38 111.38 111.8 111.68 111.13 111.12 111.21 111.09 111.18 111.2 111.35 111.69 111.59 111.96 112.22 111.98 111.96 111.77 111.86 111.6 111.36 111.48 111.36 111.97 112.07 111.84 112.01 111.99 112.08 112.58 112.15 111.69 111.47 111.04 109.94 109.46 109.16 108.76 108.76 109.39 109.48 109.96 109.79 109.44 109 108.85 108.66 108.57 108.81 108.81 109.04 109.32 109.52 109.39 109.12 109.37 109.3 109.4 109.14 108.19 107.36 107.18 107.14 107.78 107.75 107.47 107.34 106.94 106.56 106.29 106.56 106.31 106.42 106.73 106.19 105.64 105.34 105.34 105.76 105.44 105.85 105.69 106.18 106.18 106.58 106.76 106.52 106.69 106.39 106.45 106.78 107.16 107.19 107.79 107.79 107.92 107.69 107.33 107.75 107.75 107.7 107.9 107.45 107.42 107.65 107.34 106.94 106.29 105.91 105.94 105.68 105.2 104.97 104.62 104.79 104.99 105.18 105.41 105.76 106.11 106.45 106.71 106.92 106.86 106.91 107.13 107.18 107.22 107.37 107.36 107.46 107.67 107.73 107.73 107.92 107.8 108.26 108.64 108.46 108.76 108.62 108.79 108.84 108.95 108.81 109.05 109.24 109.27 109.41 109.41 109.3 109.32 109.41 109.44 109.49 109.72 109.79 110.03 110.49 110.28 110.28 110.38 110.55 110.76 110.76 110.69 110.68 110.57 110.66 110.64 110.74 110.78 110.79 110.84 110.93 111.11 111.18 111.16 111.22 111.4 111.6 111.61 111.76 111.9 111.73 111.23 111.32 111.47 111.68 111.75 111.99 111.63 111.7 111.64 111.7 111.55 111.72 111.52 111.55 111.65 111.66 111.57 111.36 111.49 111.58 111.41 111.34 111.34 111.34 111.28 110.81 110.7 110.92 111.06 111.02 111.17 111.1 110.95 110.72 110.6 110.65 110.86 110.87 110.97 110.97 111.08 111.34 111.37 111.29 111.43 111.25 111.26 111.2 111.29 111.14 110.91 110.91 110.75 110.33 110.38 110.64 110.71 110.79 110.79 110.9 111.12 111.19 111.29 110.92 110.51 110.66 110.78 110.75 111.01 111.05 110.98 110.69 110.7 110.95 111.13 111.15 111.26 111.49 111.39 111.35 111.34 111.43 111.39 111.51 111.87 112.19 112.45 112.81 112.77 112.73 112.85 112.9 113.08 113.17 113.22 113.34 113.5 113.68 113.94 113.7 113.6 113.54 113.55 113.49 113.88 113.97 113.97 114.18 114.08 114.13 114.25 114.45 114.59 114.7 114.51 114.51 114.55 114.59 114.89 114.72 114.84 114.92 114.8 114.97 115.1 114.97 114.97 114.83 115.06 115.03 114.88 114.9 115.5 115.96 115.97 116.09 116.19 116.28 116.53 116.41 116.31 116.62 116.59 116.75 116.63 116.55 116.02 116.34 116.23 116.56 116.71 116.74 116.94 117.15 116.91 116.79 116.72 117.16 117.07 117.43 117.88 118.09 118.19 117.76 117.76 117.13 117.12 117.15 117.13 117.2 117.44 117.44 117.84 117.68 117.73 118.07 117.58 117.46 117.38 117.5 117.46 117.13 117.05 116.78 117.38 117.12 117.26 117.47 117.56 117.57 117.54 117.82 118.06 118.05 118.09 118.23 118.44 118.64 118.76 118.62 118.75 118.76 118.64 118.81 118.94 119.2 119.27 119.32 119.32 119.32 119.32 119.24 119.46 119.46 119.46 119.48 120.29 120.3 120.68 120.77 120.7 121.08 121.19 121.08 121.04 120.74 120.94 120.87 120.92 121.13 121 121.18 121.23 121.28 121.03 121.17 120.8 120.7 121.05 120.73 120.8 120.96 121.13 121.17 121.17 121.21 121.38 121.58 121.53 121.61 121.91 121.65 121.46 121.95 121.89 121.57 121.92 122.09 122.01 122.02 122.67 122.75 122.85 123.18 123.14 123.2 123.09 123.44 123.16 122.94 122.8 122.97 122.78 122.82 122.69 122.92 122.73 122.73 122.73 122.92 123.1 122.85 123.09 123.13 123.19 123.29 123.4 123.41 123.42 123.4 123.31 123.18 123.13 123.32 123.45 123.86 123.82 123.92 123.95 124.02 124.02 124.18 124.37 124.26 124.2 124.21 124.21 124.43 124.32 124.3 124.33 124.5 124.55 124.55 124.9 124.82 125.08 124.1 124.17 124.22 124.56 123.89 124.21 123.63 123.36 123.59 123 122.66 122.92 122.97 122.22 122.29 122.29 122.53 122.45 122.42 122.46 121.68 121.47 120.82 120.97 121.37 121.63 121.56 121.76 121.67 121.55 121.67 121.57 121.58 121.88 121.8 121.78 121.9 122.03 121.99 122.09 122.15 122.2 122.3 122.35 122.36 122.29 122.24 122.18 122.07 121.94 122.28 122.42 122.5 122.27 122.16 122.3 122.55 122.58 122.75 122.75 122.42 122.3 122.04 121.77 121.46 121.6 121.85 121.82 121.4 121.37 121.55 121.48 121.66 121.75 121.74 121.82 121.76 121.98 122.3 122.36 122.55 122.59 122.89 122.81 123 123.16 123.09 123.06 123.1 123.08 123.2 123.01 122.76 122.97 122.9 122.8 122.96 122.91 122.73 122.72 123.08 123.32 123.35 123.56 123.76 123.92 124.35 124.47 124.64 124.48 124.59 124.58 124.69 124.81 124.89 124.89 124.98 124.98 124.66 124.94 124.88 124.63 124.68 124.4 124.5 124.84 124.94 125.05 124.86 124.7 124.65 124.79 124.99 124.97 125.07 125.22 125.29 125.2 124.62 124.33 123.87 123.93 124.08 124 123.81 123.51 123.45 123.91 123.77 124.04 124.66 124.82 124.82 124.82 124.82 125.33 125.78 125.78 125.78 125.69 125.29 125.48 125.42 125.82 125.8 125.72 125.83 126.04 126.21 126.63 126.53 126.67 126.59 126.64 126.62 126.34 125.8 125.43 125.65 125.61 125.62 125.67 125.37 125.11 125.25 125.79 126.08 126.19 126.65 126.79 126.88 127.08 127.24 127.28 127.3 127.28 127.42 127.78 127.78 127.76 127.87 127.76 127.32 127.93 127.84 127.88 127.5 127.33 127.33 127.15 126.95 126.55 126.59 126.75 126.64 126.55 126.57 126.58 126.68 126.65 126.79 126.91 127.01 127.23 127.34 127.33 127.4 127.09 127.12 127.25 127.08 126.69 126.97 126.94 127.25 127.25 127.25 127.24 127.54 127.42 127.55 127.39 127.46 127.79 127.79 127.78 127.94 127.86 127.65 127.83 128.23 128.34 128.61 128.77 129.01 128.66 128.86 128.9 128.77 129.03 129.15 129.46 129.45 129.76 129.76 130.02 129.77 129.86 129.61 129.62 129.94 129.94 130.56 130.75 130.41 130.34 130.77 130.51 130.72 130.77 130.93 130.93 130.9 130.67 130.51 130.65 130.51 130.41 130.9 130.82 131 131.03 130.82 130.4 130.52 130.29 130.43 130.55 130.55 130.74 130.48 130.85 130.6 130.91 131.01 130.82 130.89 130.84 130.96 130.94 130.15 129.92 130.2 130.22 130.1 130.08 129.75 130.21 130.11 130.34 130.34 130.53 130.79 131.04 131 131.24 131.4 131.85 131.95 131.93 131.91 132.02 132.12 132.07 132.03 132.57 132.47 132.37 132 131.98 131.81 131.57 131.53 131.62 131.61 132.03 132.39 132.12 131.65 132.21 131.88 132.09 131.85 132.25 132.16 131.51 132.32 132.16 131.73 131.68 131.49 131.73 131.41 131.48 131.1 130.89 131.41 131.47 132.05 132.13 132.24 132.33 132.16 132.42 132.39 132.88 133.33 133.15 132.77 133.33 133.47 133.46 133.61 133.61 133.31 133.47 133.48 133.59 133.52 133.41 133.55 134.34 134.23 134.15 134.25 134.44 134.5 134.23 134.4 134.53 133.95 134.99 134.69 133.98 133.74 134.12 133.15 132.68 132.54 133.21 134.39 134.41 134.43 134.43 134.43 134.43 134.91 135.32 135.32 135.32 135.12 135.2 134.74 134.46 135.11 136.01 135.41 135.49 135.8 135.49 134.96 134.97 134.82 134.9 134.83 135.8 136.88 136.98 136.35 136.21 136.55 136.71 137.11 137.19 136.95 137.11 136.96 136.75 136.94 136.88 137.05 137.22 137.22 137.14 137.41 137.22 137.62 137.84 138.25 138.38 138.95 138.9 138.91 138.32 138.71 139.03 138.73 138.66 138.39 139 139.34 139.36 139.53 139.18 139.74 139.9 140.25 139.82 139.89 139.26 139.04 139.17 139.82 139.62 139.62 139.62 139.62 139.53 140.34 140.82 141.54 141.81 141.83 141.63 142.11 141.46 140.6 141.22 141.46 141.66 141.5 141.62 141.53 140.98 139.94 139.94 139.68 139.85 139.09 138.71 138.82 139.5 139.38 138.88 138.88 139.1 139.1 139.21 139.83 139.82 139.96 139.96 140.06 139.85 140.36 140.11 139.61 139.86 139.22 139.17 138.82 138.84 138.48 138.31 138.81 138.87 138.56 137.97 138.01 137.92 138.01 138.1 138.1 138.96 138.72 138.65 138.72 137.74 137.61 137.93 137.97 137.95 137.73 137.89 137.48 137.77 137.75 138.34 138.53 138.7 139.06 139.26 139.12 138.91 138.77 138.44 138 137.21 137.73 137.83 137.94 137.94 138.24 138.1 138.41 137.73 137.49 137.68 137.24 136.54 136.29 136.36 136.76 136.74 136.61 135.61 134.83 133.58 133.98 134.52 135.61 135.71 135.53 134.65 134.95 135.24 135.01 135.01 135.32 135.29 135.19 135.07 135.06 135.11 135.16 135.2 134.92 134.82 134.34 134.18 133.77 133.52 132.79 132.55 132.76 132.79 132.91 132.98 132.97 133.2 133.14 133.21 133.4 133.47 133.51 133.6 133.85 133.94 133.86 133.49 133.61 134.08 134.23 134.48 134.68 134.88 134.51 134.91 135.12 135.12 134.9 134.76 134.2 134.3 134.22 133.49 133.39 133.62 133.8 134.46 134.45 134.6 134.34 134.47 134.97 135.13 135.32 135.07 135.64 135.24 134.11 134.69 134.55 134.19 133.61 133.79 132.64 132.17 133.03 133.76 133.3 132.62 133.02 133.37 133.37 133.37 134.11 133.95 135.04 135.04
Seasonal period
12
12
1
2
3
4
5
6
7
8
9
10
11
12
Seasonal window
(?)
Seasonal degree
(?)
1
0
1
Trend window
(?)
Trend degree
(?)
1
1
0
Low-pass window
(?)
Low-pass degree
(?)
1
1
0
Robust loess fitting
TRUE
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
0 seconds
R Server
Big Analytics Cloud Computing Center
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