Abstract
This monograph is primarily concerned with parameter estimation for a random process X t taking values in r-dimensional Euclidean space. The distribution of X t depends on a characteristic θ taking values in a open subset Θ of p-dimensional Euclidean space. The framework may be parametric or semiparametric; θ may be, for example, the mean of a stationary process. The object will be the “efficient” estimation of θ based on a sample X t , t ∈ T.
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© 1997 Springer-Verlag New York, Inc.
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(1997). Introduction. In: Heyde, C.C. (eds) Quasi-Likelihood and its Application. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/0-387-22679-6_1
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DOI: https://doi.org/10.1007/0-387-22679-6_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98225-0
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