State Space Time Series Analysis - Part 1
State space models make up a suite of powerful time series analysis techniques which utilize the Kalman filter to model seasonal, trend, and level components of time series separately. State space methodology gives the developer considerably greater control over how the time series is modeled than most popular time series analysis techniques while also seemlessly allowing the analysis of exogenous variables alongside autoregressive and moving average terms. »