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- W3120218768 abstract "We propose and investigate a new estimation method for the parameters of models consisting of smooth density functions on the positive half axis. The procedure is based on a recently introduced characterization result for the respective probability distributions, and is to be classified as a minimum distance estimator, incorporating as a distance function the L$^{q}$-norm. Throughout, we deal rigorously with issues of existence and measurability of these implicitly defined estimators. Moreover, we provide consistency results in a common asymptotic setting, and compare our new method with classical estimators for the exponential-, the Rayleigh-, and the Burr Type XII distribution in Monte Carlo simulation studies. We also assess the performance of different estimators for non-normalized models in the context of an exponential-polynomial family." @default.
- W3120218768 created "2021-01-18" @default.
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- W3120218768 date "2020-01-01" @default.
- W3120218768 modified "2023-09-23" @default.
- W3120218768 title "Minimum L$^{q}$-distance estimators for non-normalized parametric models [in press]" @default.
- W3120218768 hasPublicationYear "2020" @default.
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