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ЖУРНАЛЫ // Theory of Stochastic Processes // Архив

Theory Stoch. Process., 2005, том 11(27), выпуск 3, страницы 82–91 (Mi thsp287)

Parameter estimators of nonlinear quantile regression

A. V. Ivanov, I. V. Orlovsky

National Technical of University of Ukraine ``KPI'', Peremogy Ave., Kyiv, Ukraine

Аннотация: We have obtained the asymptotic normality of parameter estimators of a nonlinear quantile regression with nonsymmetric random noise. Introduction Here, we examine the asymptotic normality of Koenker and Basset estimators [1] or the generalized least moduli estimators (GLME) of nonlinear regression model parameters that generalize least moduli estimators for non-symmetric observation errors. The consistency property of GLME has been considered in [2].

Ключевые слова: Nonlinear quantile regression, parameter estimator.

MSC: Primary 62J02; Secondary 62J99

Язык публикации: английский



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