Basic Stochastic Models

Abstract

So far, we have considered two approaches for modelling time series. The first is based on an assumption that there is a fixed seasonal pattern about a trend.We can estimate the trend by local averaging of the deseasonalised data, and this is implemented by the R function decompose. The second approach allows the seasonal variation and trend, described in terms of a level and slope, to change over time and estimates these features by exponentially weighted averages. We used the HoltWinters function to demonstrate this method.