A parametric regression framework for the skew sinh-arcsinh t distribution
Sign Up to like & getrecommendations! Published in 2021 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2020.08.036
Abstract: Abstract On the basis of an interesting and tractable parametric family of distributions, which figures prominently as an empirical model for asymmetric and heavy-tailed data, we introduce a novel parametric regression model that is quite… read more here.
Keywords: parametric regression; skew sinh; regression; regression framework ... See more keywords
Semi-parametric Regression based on Machine Learning Methods for UAS Stall Identification
Sign Up to like & getrecommendations! Published in 2021 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2021.08.355
Abstract: Abstract A semi-parametric regression methodology is formulated to identify the unsteady lift characteristics of a small UAS undergoing dynamic stall. Based on the trailing edge separation model of Leishmann and Beddoes, the nonlinear evolution of… read more here.
Keywords: parametric regression; methodology; machine learning; semi parametric ... See more keywords
Non parametric regression estimations over Lp risk based on biased data
Sign Up to like & getrecommendations! Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2015.1044670
Abstract: Abstract Using a wavelet basis, Chesneau and Shirazi study the estimation of one-dimensional regression functions in a biased non parametric model over L2 risk (see Chesneau, C and Shirazi, E. Non parametric wavelet regression based… read more here.
Keywords: parametric regression; regression; biased data; based biased ... See more keywords
Robust equivariant non parametric regression estimators for functional ergodic data
Sign Up to like & getrecommendations! Published in 2020 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2019.1705980
Abstract: Abstract This article deals with the equivariant non parametric robust regression estimation for stationary ergodic processes valued in where is a semi-metric space. We consider a new robust regression estimator when the scale parameter is… read more here.
Keywords: regression estimators; parametric regression; regression; robust equivariant ... See more keywords
On the rate of asymptotic normality of integral weighted kernel estimator in a non parametric regression model for φ-mixing random variables
Sign Up to like & getrecommendations! Published in 2024 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2024.2316261
Abstract: Abstract. In this article, we study the convergence rate of asymptotic normality for the estimator in a non parametric regression model under φ-mixing random variables by using the blockwise technique. With different choices of the… read more here.
Keywords: parametric regression; estimator non; regression model; rate asymptotic ... See more keywords
Models as Approximations II: A Model-Free Theory of Parametric Regression
Sign Up to like & getrecommendations! Published in 2019 at "Statistical Science"
DOI: 10.1214/18-sts694
Abstract: We develop a model-free theory of general types of parametric regression for iid observations. The theory replaces the parameters of parametric models with statistical functionals, to be called "regression functionals'', defined on large non-parametric classes… read more here.
Keywords: parametric regression; regression functionals; regression; free theory ... See more keywords
Non-Parametric Regression and Riesz Estimators
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DOI: 10.3390/axioms12040375
Abstract: In this paper, we consider a non-parametric regression model relying on Riesz estimators. This linear regression model is similar to the usual linear regression model since they both rely on projection operators. We indicate that… read more here.
Keywords: regression; non parametric; riesz estimators; model ... See more keywords