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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A sharp analysis on the asymptotic behavior of the Durbin-Watson statistic for the first-order autoregressive process [PDF]
, 2011 The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin-Watson statistic. We focus our attention on the first-order autoregressive process where the driven noise is also given by a first-order autoregressive ...
Bercu, Bernard, Proia, Frederic
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Strategies for Asymptotic Normalization
, 2022 FSCD ...
Faggian, Claudia, Guerrieri, Giulio
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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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Asymptotics for functionals of powers of a periodogram
Modern Stochastics: Theory and Applications, 2015 We present large sample properties and conditions for asymptotic normality of linear functionals of powers of the periodogram constructed with the use of tapered data.
Lyudmyla Sakhno
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Combining kernel estimators in the uniform deconvolution problem [PDF]
, 2010 We construct a density estimator and an estimator of the distribution function in the uniform deconvolution model. The estimators are based on inversion formulas and kernel estimators of the density of the observations and its derivative.
van Es, Bert
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Fisher informations and local asymptotic normality for continuous-time quantum Markov processes [PDF]
, 2014 We consider the problem of estimating an arbitrary dynamical parameter of an open quantum system in the input–output formalism. For irreducible Markov processes, we show that in the limit of large times the system-output state can be approximated by a ...
C. Cătană, L. Bouten, M. Guţă
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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
doaj
Asymptotics for penalized additive B-spline regression [PDF]
, 2011 This paper is concerned with asymptotic theory for penalized spline estimator in bivariate additive model. The focus of this paper is put upon the penalized spline estimator obtained by the backfitting algorithm.
Naito, K., Yoshida, T.
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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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