Abstract
The Kalman filter, as proposed by Kalman(1960), has been widely applied to time-series analysis and statistical modelling. Results proposed in several disciplines, particularly in engineering, seem to show that the Kalman filter is a powerful tool for statistical estimation and forecast. However, in practice, some problems have to be solved before confidently using the Kalman filter. These problems are related both with the numerical accuracy of the algorithm proposed by Kalman, and with the estimation of parameters that in the conventional Kalman filter are assumed to be known.2
Prepared for the 1989 GLIM Conference and 4th International Workshop on Statistical Modelling, Trento, 17–21.7.89. The author thanks Gregory Chow and Andrew Harvey for helpful conversations.
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Carraro, C. (1989). A Few Problems with Application of the Kalman Filter. In: Decarli, A., Francis, B.J., Gilchrist, R., Seeber, G.U.H. (eds) Statistical Modelling. Lecture Notes in Statistics, vol 57. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3680-1_9
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