Displaying 1 result from an estimated 1 matches for "llrsaison".
2010 Feb 07
2
predicting with stl() decomposition
...th=300)
noise <- rnorm(300,0,2)
time <- 1:300
series[1] <- noise[1]
for(i in 3:300){
series[i] <- 0.5*series[i-1]+ noise[i] + 0.01*time[i]
}
seriesTs <- ts(series, start=c(1980,1), frequency=12)
decomp <- stl(seriesTs ,"periodic")
plot(decomp)
llrSaison <- loess(seriesTs~time , span=decomp$win[1] ,
degree=decomp$deg[1])
llrTrend <- loess(seriesTs~time, span=decomp$win[2] ,
degree=decomp$deg[2])
plot(llrSaison$fitted)
The last plot differs much from the seasonal plot in the plot(decomp) call.
This is why the llr estimator doesn’t e...