STABLE ALGORITHMS FOR THE STATE SPACE MODEL

Piet De Jong

Journal of Time Series Analysis, 1991, vol. 12, issue 2, 143-157

Abstract: Abstract. Numerically stable algorithms are developed for filtering, likelihood evaluation, generalized least squares computation and smoothing where data are generated by a state space model. The algorithms handle diffuse initial states in a numerically safe way. Singular innovation covariance matrices, such as those which arise in series with missing values, are dealt with. The algorithms generalize stable algorithms for ordinary least‐squares computations.

Date: 1991
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