ABSTRACT
Various models used in time series analysis can be treated entirely within
the state-space model framework.Many problems of time series analysis
can be formulated in terms of the state estimation of a state-space model.
This chapter presents algorithms for the Kalman filter and a smoothing
algorithm for efficient state estimation. In addition, applications to the
increasing horizon prediction, interpolation and parameter estimation of
a time series are dealt with.
