A Hilbert Transform Method for Estimating Distributed Lag Models With Randomly Missed or Distorted Observations

Conference paper
Part of the Lecture Notes in Statistics book series (LNS, volume 25)


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.


Consistent Estimator Cross Spectrum Good Trial Estimate Transfer Function Distorted Observation 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  1. 1.University of TexasAustinUSA
  2. 2.Virginia Polytechnic Institute and State UniversityBlacksburgUSA

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