Results 11 to 20 of about 8,819 (162)
Asymptotic Normality for Plug-In Estimators of Generalized Shannon’s Entropy [PDF]
Entropy, 2022 Shannon’s entropy is one of the building blocks of information theory and an essential aspect of Machine Learning (ML) methods (e.g., Random Forests).
Jialin Zhang, Jingyi Shi
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Asymptotic normality of quadratic estimators [PDF]
Stochastic Processes and their Applications, 2016 We prove conditional asymptotic normality of a class of quadratic U-statistics that are dominated by their degenerate second order part and have kernels that change with the number of observations. These statistics arise in the construction of estimators in high-dimensional semi- and non-parametric models, and in the construction of nonparametric ...
Robins, J.M. +3 more
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The asymptotic normality of internal estimator for nonparametric regression [PDF]
Journal of Inequalities and Applications, 2018 In this paper, we aim to study the asymptotic properties of internal estimator of nonparametric regression with independent and dependent data. Under some weak conditions, we present some results on asymptotic normality of the estimator.
Penghua Li, Xiaoqin Li, Liping Chen
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Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples [PDF]
Journal of Inequalities and Applications, 2018 In the present article, by utilizing some inequalities for linearly negative quadrant dependent random variables, we discuss the uniformly asymptotic normality of sample quantiles for linearly negative quadrant dependent samples under mild conditions ...
Xueping Hu +3 more
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A difference-based approach in the partially linear model with dependent errors
Journal of Inequalities and Applications, 2018 We study asymptotic properties of estimators of parameter and non-parameter in a partially linear model in which errors are dependent. Using a difference-based and ordinary least square (DOLS) method, the estimator of an unknown parametric component is ...
Zhen Zeng, Xiangdong Liu
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On asymptotic normality for m-dependent U-statistics
International Journal of Mathematics and Mathematical Sciences, 1988 Let (Xn) be a sequence of m-dependent random variables, not necessarily equally distributed. We give a Berry-Esseen estimate of the convergence to normality of a suitable normalization of a U-statistic of the (Xn).
Wansoo T. Rhee
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Semiparametric tail-index estimation for randomly right-truncated heavy-tailed data [PDF]
Arab Journal of Mathematical SciencesPurpose – The purpose of this paper is to propose a semiparametric estimator for the tail index of Pareto-type random truncated data that improves the existing ones in terms of mean square error.
Saida Mancer +2 more
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Test and asymptotic normality for mixed bivariate measure
Statistica, 2013 Consider a pair of random variables whose joint probability measure is the sum of an absolutely continuous measure, a discrete measure and a finite number of absolutely continuous measures on some lines called jum lines.
Rachid Sabre
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Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors
Modern Stochastics: Theory and Applications, 2021 A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known.
Mykyta Yakovliev, Alexander Kukush
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Metrika, 1970 The object of this paper is to show that — under certain regularity conditions — a dominated family of probability measures with Euclidean parameter space behaves approximately like a family of normal distributions if each probability measure is the independent product of a great number of identical components.
Michel, R., Pfanzagl, J.
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