Results 31 to 40 of about 8,819 (162)

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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A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data

Entropy, 2023
Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming ...
Huaping Chen, Jiayue Zhang, Xiufang Liu
doaj   +1 more source

Discretization and Asymptotic Normality of Drift Parameters Estimator in the Cox-Ingersoll-Ross Model

Austrian Journal of Statistics
This paper investigates the simultaneous estimation of two drift parameters of a Cox-Ingersoll-Ross (CIR) model, for which observations can be made either continuously or at discrete time instants.
Olha Prykhodko, Kostiantyn Ralchenko
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Integral Least-Squares Inferences for Semiparametric Models with Functional Data

Journal of Applied Mathematics, 2014
The inferences for semiparametric models with functional data are investigated. We propose an integral least-squares technique for estimating the parametric components, and the asymptotic normality of the resulting integral least-squares estimator is ...
Limian Zhao, Peixin Zhao
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Asymptotic normality and mean consistency of LS estimators in the errors-in-variables model with dependent errors

Open Mathematics, 2020
In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu, Liu Xinsheng, Yu Yuncai, Hu Hongchang   +3 more
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Hybrid Wavelet–Difference M-Estimation for Partially Linear Models With m-Dependent Errors

Journal of Mathematics
In this paper, we employ difference-based M-estimation to estimate the parameters β in a partially linear model with m-dependent errors and establish the asymptotic normality of these estimators.
Yu Zhang, Zhiqi Chen
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Asymptotic normality of discretized maximum likelihood estimator for drift parameter in homogeneous diffusion model

Modern Stochastics: Theory and Applications, 2015
We prove the asymptotic normality of the discretized maximum likelihood estimator for the drift parameter in the homogeneous ergodic diffusion model.
Kostiantyn Ralchenko
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Asymptotic normality of associated Lah numbers

Mathematical Foundations of Computing, 2021
<p style='text-indent:20px;'>Based on the results given by Ahuja and Enneking, we show that the generating function of the associated Lah numbers having only real zeros, and further obtain the asymptotic normality of the associated Lah numbers. As application, we get the asymptotic normality of the signless Lah numbers.</p>
Wen Zhang, Lily Li Liu
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A central limit theorem for numbers satisfying a class of triangular arrays associated with Hermite polynomials

Lietuvos Matematikos Rinkinys, 2021
The paper extends the investigations of limit theorems for numbers satisfying a class of triangular arrays. We obtain analytical expressions for the semiexponential generating function the numbers, associated with Hermite polynomials.
Igoris Belovas
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Comparison of Weibull Tail-Coefficient Estimators

Revstat Statistical Journal, 2006
We address the problem of estimating the Weibull tail-coefficient which is the regular variation exponent of the inverse failure rate function. We propose a family of estimators of this coefficient and an associate extreme quantile estimator.
Laurent Gardes , Stéphane Girard
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