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This paper studies the asymptotic behavior of the minimum Hellinger distance estimator of the underlying parameter in a supercritical branching process whose offspring distribution is known to belong to a parametric family. This estimator is shown to be asymptotically normal, efficient at the...
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For the critical and sub-critical branching process with immigration, the natural estimator of the offspring mean 'm' is shown to be strongly consistent uniformly over a whole class of offspring distributions with m [epsilon] (0, 1] and bounded variance.
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In this paper we consider bootstrap approximation to the sampling distribution of an estimator of the offspring mean m in a branching process with immigration. A modification of the standard parametric bootstrap procedure is shown to eliminate the invalidity of the standard bootstrap for the...
Persistent link: https://www.econbiz.de/10008873079
We show that if an appropriate stopping rule is used to determine the sample size when estimating the parameters in a stationary and ergodic threshold AR(1) model, then the sequential least-squares estimator is asymptotically risk efficient. The stopping rule is also shown to be asymptotically...
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