Items related to Statistical Inference for Spatial Poisson Processes
Synopsis
1 Auxiliary Results.- 1.1 Poisson process.- 1.2 Estimation problems.- 2 First Properties of Estimators.- 2.1 Asymptotic of the maximum likelihood and Bayesian estimators.- 2.2 Minimum distance estimation.- 2.3 Special models of Poisson processes.- 3 Asymptotic Expansions.- 3.1 Expansion of the MLE.- 3.2 Expansion of the Bayes estimator.- 3.3 Expansion of the minimum distance estimator.- 3.4 Expansion of the distribution functions.- 4 Nonstandard Problems.- 4.1 Misspecified model.- 4.2 Nonidentifiable model.- 4.3 Optimal choice of observation windows.- 4.4 Optimal choice of intensity function.- 5 The Change-Point Problems.- 5.1 Phase and frequency estimation.- 5.2 Chess-field problem.- 5.3 Top-hat problem.- 6 Nonparametric Estimation.- 6.1 Intensity measure estimation.- 6.2 Intensity function estimation.- Remarks.
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About the Author
Yury A. Kutoyants, Professor of Mathematics at the University of Main, Le Mans, France, is a member of the Bernoulli Society, the Mathematical Society of France, and the Institute of Mathematical Statistics. He is associate editor of "Finance and Stochastics" and "Statistical Inference for Stochastic Processes."
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