Results 71 to 80 of about 6,198,544 (193)

Robust Functional Regression via FPCA, Copula-Scale Design, and Multivariate Bernstein Smoothing

Mathematics
We introduce a robust nonparametric regression framework for functional covariates that combines functional principal component analysis (FPCA), marginal copula-scale normalization, bounded-score M-estimation, and multivariate Bernstein smoothing.
Wahiba Bouabsa, Fatimah Alshahrani
doaj   +1 more source

Estimation and inference for multi-kink expectile regression with nonignorable dropout

Statistical Theory and Related Fields
In this paper, we consider parameter estimation, kink points testing and statistical inference for a longitudinal multi-kink expectile regression model with nonignorable dropout.
Dongyu Li, Lei Wang
doaj   +1 more source

Statistical inference for inverse problems [PDF]

In this paper we study statistical inference for certain inverse problems. We go beyond mere estimation purposes and review and develop the construction of confidence intervals and confidence bands in some inverse problems, including deconvolution and ...
Bissantz, Nicolai, Holzmann, Hajo
core  

Leveraging density ratio models in a binary instrumental variable inference with a binary outcome: A retrospective approach

Statistical Theory and Related Fields
Conditional Local Risk Ratio (CLRR) is a widely used metric for assessing heterogeneous treatment effects of binary outcomes in randomized clinical trials involving noncompliance.
Wenli Liu, Jing Qin, Yukun Liu
doaj   +1 more source

LA CONDITION L.A.N (LOCAL ASYMPTOTIC NORMALITY

, 2015
Dans ce travail nous nous sommes penchés sur la condition de la normalité asymptotique qui est un outil puissant introduit par Ibragimov et Has’minskii. Cette condition permet notamment de résoudre des problèmes statistiques concernant l’estimation, pour des modèles divers et des problèmes réels dans la 45 physique, la médecine,...
openaire   +2 more sources

Testing for Non-Normality in the Presence of One-Sided Slope Parameters [PDF]

In a recent paper, Hughes (1999) showed that the power of tests of linear regression parameters could be improved by utilizing one-sided information regarding the nuisance parameters in the testing problem.
Anthony W. Hughes
core  

Dirichlet–Kernel Methods for Geometric Conditional Quantiles: Bahadur Expansions and Boundary Adaptivity on the d-Simplex

Mathematics
This article develops a boundary-adaptive nonparametric methodology for estimating the geometric conditional quantiles of a multivariate response when the conditioning covariate is supported on the simplex—an important case, as it is the natural domain ...
Abdulghani Alwadeai, Salim Bouzebda, Salah Khardani   +2 more
doaj   +1 more source

Advanced Statistical Learning: Limit Theorems for Nonparametric Conditional U-Statistics Smoothed by Asymmetric Kernels Under Missing-at-Random Sampling

Mathematics
This paper develops a boundary-sensitive asymptotic theory for nonparametric conditional U-statistics smoothed by support-adapted asymmetric kernels when the response variable is subject to Missing-at-Random observation.
Salim Bouzebda
doaj   +1 more source

ESTIMATION AND ASYMPTOTIC THEORY FOR A NEW CLASS OF MIXTURE MODELS [PDF]

In this paper a new model of mixture of distributions is proposed, where the mixing structure is determined by a smooth transition tree architecture.
Eduardo Mendes, MArcelo Cunha Medeiros, Alvaro Veiga   +2 more
core  

Quantum phase transition of infrared radiation

Journal of High Energy Physics
We describe a phase transition of infrared radiation, driven by quantum fluctuations, which takes place at the boundary of (the conformal diagram of) Minkowski spacetime.
Bartosz Biadasiewicz, Wojciech Dybalski
doaj   +1 more source