Abstract
Least-squares estimation of the lag coefficients of a distributed lag model is not a straightforward regression problem when the sample has missed or distorted observations. Even though the normal equations can be computed using sums of the available cross products, the asymptotic properties of a solution of these equations are unknown. Since a special computer program is required to compute these normal equations when observations are missed, it is practical to consider another approach to the problem.
Paper prepared for the Office of Naval Research Symposium on Time Series Analysis of Irregularly Observed Data, Texas A&M University.
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© 1984 Springer-Verlag Berlin Heidelberg
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Hinich, M.J., Weber, W.E. (1984). A Hilbert Transform Method for Estimating Distributed Lag Models With Randomly Missed or Distorted Observations. In: Parzen, E. (eds) Time Series Analysis of Irregularly Observed Data. Lecture Notes in Statistics, vol 25. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-9403-7_7
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DOI: https://doi.org/10.1007/978-1-4684-9403-7_7
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