Results 21 to 30 of about 373,332 (254)
On the Use of Conditional Asymptotic Normality
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1979 Summary Methods for obtaining the limiting distribution of a complicated statistic which depends on another auxiliary statistic are discussed. Examples are given in which a general conditional approach due to Sethuraman is found to be extremely fruitful in solving this type of problem.
Fligner, Michael A. +1 more
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On Asymptotic Normality of the Hill Estimator [PDF]
, 1996 On Asymptotic Normality of the Hill ...
Resnick, S., de Haan, L.
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The asymptotic normality of internal estimator for nonparametric regression
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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Some Asymptotic Results of Kernel Density Estimator in Length-Biased Sampling [PDF]
Journal of Sciences, Islamic Republic of Iran, 2013 In this paper, we prove the strong uniform consistency and asymptotic normality of the kernel density estimator proposed by Jones [12] for length-biased data.The approach is based on the invariance principle for the empirical processes proved by Horváth [
M. Ajami, V. Fakoor, S. Jomhoori
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Estimating 𝐿-Functionals for Heavy-Tailed Distributions and Application
Journal of Probability and Statistics, 2010 𝐿-functionals summarize numerous statistical parameters and actuarial risk measures. Their sample estimators are linear combinations of order statistics (𝐿-statistics). There exists a class of heavy-tailed distributions for which the asymptotic normality
Abdelhakim Necir, Djamel Meraghni
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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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On asymptotic normality of the hill estimator [PDF]
Communications in Statistics. Stochastic Models, 1998 For iid observations from a common distribution Fwith regularly varying tail , a popular estimator of α is the Hill estimator. Regular variation of the distribution tail is equivalent to weak consistency of the Hill estimator in a manner made precise in Mason (1982) but necessary and sufficient conditions for asymptotic normality of this estimator are ...
de Haan, Laurens, Resnick, SI
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Asymptotics of the Empirical Bootstrap Method Beyond Asymptotic Normality
CoRR, 2020 One of the most commonly used methods for forming confidence intervals for statistical inference is the empirical bootstrap, which is especially expedient when the limiting distribution of the estimator is unknown. However, despite its ubiquitous role, its theoretical properties are still not well understood for non-asymptotically normal estimators. In
Morgane Austern, Vasilis Syrgkanis
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Test for Exponential Better (Worse) than Used EBU (EWU) Life Distributions Based on the U-Test [PDF]
The Egyptian Statistical Journal, 2003 The problem of testing exponentiality versus exponential better (worse) than used EBU (EWU) class of life distributions is considered through U-test. The percentiles of this test are tabulated for sample sizes n=5(1)50.
E. Elsherpieny, S. Abu-Youssef
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Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in
IEEE Access, 2022 The Gamma distribution based generalized linear model ( $Ga$ GLM) is a kind of statistical model feasible for the positive value of a non-stationary stochastic system, in which the location and the scale are regressed by the corresponding explanatory ...
Benchao Wang, Pan Qin, Hong Gu
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