> data(AirPassengers, package="datasets") > AirPassengers <- as.data.frame(AirPassengers) > summary(AirPassengers) x Min. :104.0 1st Qu.:180.0 Median :265.5 Mean :280.3 3rd Qu.:360.5 Max. :622.0 > attach(AirPassengers) > air.ts <- ts(x, start=c(1949, 1), end=c(1960, 12), frequency=12) > str(air.ts) Time-Series [1:144] from 1949 to 1961: 112 118 132 129 121 135 148 148 136 119 ... > acf(air.ts, main="") > plot(air.ts) > air.comps <- stl(air.ts, s.window="period") > summary(air.comps) Call: stl(x = air.ts, s.window = "period") Time.series components: seasonal trend remainder Min. :-57.48185 Min. :126.1117 Min. :-49.42378 1st Qu.:-27.05842 1st Qu.:184.9487 1st Qu.:-10.30070 Median : -7.01817 Median :260.2407 Median : 0.64024 Mean : 0.00000 Mean :280.4517 Mean : -0.15312 3rd Qu.: 21.16290 3rd Qu.:373.3595 3rd Qu.: 10.84274 Max. : 70.24388 Max. :497.4299 Max. : 72.50607 IQR: STL.seasonal STL.trend STL.remainder data 48.22 188.41 21.14 180.50 % 26.7 104.4 11.7 100.0 Weights: all == 1 Other components: List of 5 $ win : Named num [1:3] 1441 19 13 $ deg : Named int [1:3] 0 1 1 $ jump : Named num [1:3] 145 2 2 $ inner: int 2 $ outer: int 0 > plot(air.comps) ###FORECAST library(forecast, pos=17) > air.exp <- ets(air.ts) > # predict next three future values > forecast(air.exp, 3) Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 Jan 1961 441.8018 419.6256 463.9780 407.8863 475.7174 Feb 1961 434.1186 407.1668 461.0704 392.8994 475.3379 Mar 1961 496.6300 460.6291 532.6310 441.5714 551.6887 > plot(forecast(air.exp, 3)) > #########MULTIPLICATIVE MODEL > decompose_air = decompose(air.ts, "multiplicative") > > plot(as.ts(decompose_air$seasonal)) > plot(as.ts(decompose_air$trend)) > plot(as.ts(decompose_air$random)) > plot(decompose_air) > print (decompose_air) #############################################SCRIPT data(AirPassengers, package="datasets") AirPassengers <- as.data.frame(AirPassengers) summary(AirPassengers) attach(AirPassengers) air.ts <- ts(x, start=c(1949, 1), end=c(1960, 12), frequency=12) str(air.ts) acf(air.ts, main="") plot(air.ts) air.comps <- stl(air.ts, s.window="period") summary(air.comps) plot(air.comps) ###FORECAST library(forecast, pos=17) air.exp <- ets(air.ts) # predict next three future values forecast(air.exp, 3) plot(forecast(air.exp, 3)) #########MULTIPLICATIVE MODEL decompose_air = decompose(air.ts, "multiplicative") plot(as.ts(decompose_air$seasonal)) plot(as.ts(decompose_air$trend)) plot(as.ts(decompose_air$random)) plot(decompose_air) print (decompose_air)