Results 21 to 30 of about 236 (144)

Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data

Journal of Mathematics, Volume 2025, Issue 1, 2025.
The primary objective of this research is to investigate the asymptotic properties of the conditional density nonparametric estimator. The main areas of focus are the estimator’s consistency (with rates), including those involving censored data and quasi‐associated dependent variables, as well as its performance when the covariate is functional in ...
Hamza Daoudi, Abderrahmane Belguerna, Zouaoui Chikr Elmezouar, Fatimah Alshahrani, Jun Fan   +4 more
wiley   +1 more source

Projection Estimates of Constrained Functional Parameters [PDF]

, 2005
AMS classifications: 62G05; 62G07; 62G08; 62G20 ...
Segers, J., Guillou, A., Fils-Villetard, A.   +2 more
core  

Variable importance for causal forests: breaking down the heterogeneity of treatment effects

Journal of Causal Inference
Causal random forests provide efficient estimates of heterogeneous treatment effects. However, forest algorithms are also well-known for their black-box nature, and therefore, do not characterize how input variables are involved in treatment effect ...
Bénard Clément, Josse Julie
doaj   +1 more source

On the asymptotic covariance of the multivariate empirical copula process

Dependence Modeling, 2019
Genest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample ...
Genest Christian, Mesfioui Mhamed, Nešlehová Johanna G.   +2 more
doaj   +1 more source

Aligned Rank Statistics for Repeated Measurement Models with Orthonormal Design, Employing a Chernoff-Savage Approach [PDF]

, 2004
AMS classifications: 62G10, 62G20 ...
Einmahl, J.H.J., Puri, M.L., Ruymgaart, F.H., Omolo, B.O.   +3 more
core  

On internally corrected and symmetrized kernel estimators for nonparametric regression

, 2010
Multivariate regression, Smoothing matrix, Symmetry, 62G08, 62G20,
Jacho-Chávez, David, Linton, Oliver, David Jacho-Chávez, Oliver Linton   +3 more
core   +1 more source

Treatment effect estimation with observational network data using machine learning

Journal of Causal Inference
Causal inference methods for treatment effect estimation usually assume independent units. However, this assumption is often questionable because units may interact, resulting in spillover effects between them.
Emmenegger Corinne, Spohn Meta-Lina, Elmer Timon, Bühlmann Peter   +3 more
doaj   +1 more source

On kernel-based estimation of conditional Kendall’s tau: finite-distance bounds and asymptotic behavior

Dependence Modeling, 2019
We study nonparametric estimators of conditional Kendall’s tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic pointwise and uniform bounds, that hold with high probabilities.
Derumigny Alexis, Fermanian Jean-David
doaj   +1 more source

Estimation for spatial semi-functional partial linear regression model with missing response at random

Demonstratio Mathematica
The aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR).
Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi   +3 more
doaj   +1 more source

Tree-based conditional copula estimation

Dependence Modeling
This article proposes a regression tree procedure to estimate conditional copulas. The associated algorithm determines classes of observations based on covariate values and fits a simple parametric copula model on each class.
Bonacina Francesco, Lopez Olivier, Thomas Maud   +2 more
doaj   +1 more source