Mathematics, 2023 This paper studies a linear regression model in which the errors are asymptotically almost negatively associated (AANA, in short) random variables. Firstly, the central limit theorem for AANA sequences of random variables is established. Then, we use the
Yu Zhang
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Asymptotic normality of recursive algorithms via martingale difference arrays [PDF]
Discrete Mathematics & Theoretical Computer Science, 2001 We propose martingale central limit theorems as an tool to prove asymptotic normality of the costs of certain recursive algorithms which are subjected to random input data.
Werner Schachinger
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Asymptotic Normality in Linear Regression with Approximately Sparse Structure
Mathematics, 2022 In this paper, we study the asymptotic normality in high-dimensional linear regression. We focus on the case where the covariance matrix of the regression variables has a KMS structure, in asymptotic settings where the number of predictors, p, is ...
Saulius Jokubaitis, Remigijus Leipus
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Asymptotic inference for a stochastic differential equation with uniformly distributed time delay [PDF]
, 2015 For affine stochastic differential equation with uniformly distributed time delay the local asymptotic properties of the likelihood function are studied.
Benke, János Marcell, Pap, Gyula
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Problems for combinatorial numbers satisfying a class of triangular arrays
Lietuvos Matematikos Rinkinys, 2023 Numbers satisfying a class of triangular arrays, defined by a bivariate first-order linear difference equation with linear coefficients, include a wide range of combinatorial numbers: binomial coefficients, Morgan numbers, Stirling numbers of the first ...
Igoris Belovas
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A central limit theorem for the sample autocorrelations of a L\'evy driven continuous time moving average process [PDF]
, 2012 In this article we consider L\'evy driven continuous time moving average processes observed on a lattice, which are stationary time series. We show asymptotic normality of the sample mean, the sample autocovariances and the sample autocorrelations.
Alexander Lindner +10 more
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New fat-tail normality test based on conditional second moments with applications to finance [PDF]
, 2020 In this paper we introduce an efficient fat-tail measurement framework that is based on the conditional second moments. We construct a goodness-of-fit statistic that has a direct interpretation and can be used to assess the impact of fat-tails on central
Jelito, Damian, Pitera, Marcin
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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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Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Czado, Claudia, Min, Aleksey
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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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