Results 31 to 40 of about 278 (169)

Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions

Dependence Modeling, 2019
We introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced.
Ahmad Aboubacrène Ag, Deme El Hadji, Diop Aliou, Girard Stéphane   +3 more
doaj   +1 more source

Asymptotic normality of the relative error regression function estimator for censored and time series data

Dependence Modeling, 2021
Consider a survival time study, where a sequence of possibly censored failure times is observed with d-dimensional covariate The main goal of this article is to establish the asymptotic normality of the kernel estimator of the relative error regression ...
Bouhadjera Feriel, Saïd Elias Ould
doaj   +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  

Bin width selection in multivariate histograms by the combinatorial method

, 2004
Multivariate density estimation, nonparametric estimation, variable histogram estimate, bandwith selection, 62G05,
Gábor Lugosi, Luc Devroye
core   +1 more source

About tests of the “simplifying” assumption for conditional copulas

Dependence Modeling, 2017
We discuss the so-called “simplifying assumption” of conditional copulas in a general framework. We introduce several tests of the latter assumption for non- and semiparametric copula models.
Derumigny Alexis, Fermanian Jean-David
doaj   +1 more source

All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples

Journal of Causal Inference, 2023
There is a long-standing debate in the statistical, epidemiological, and econometric fields as to whether nonparametric estimation that uses machine learning in model fitting confers any meaningful advantage over simpler, parametric approaches in finite ...
Rudolph Kara E., Williams Nicholas T., Miles Caleb H., Antonelli Joseph, Diaz Ivan   +4 more
doaj   +1 more source

Nonparametric regression on the hyper-sphere with uniform design [PDF]

, 2011
Nonparametric regression, Uniform design, Minimax rate, Needlets, Needlet-shrinkage, Stochastic thresholding, 62G08, 62G05, 62C20,
Monnier, Jean-Baptiste, Jean-Baptiste Monnier   +1 more
core   +1 more source

A note on efficient minimum cost adjustment sets in causal graphical models

Journal of Causal Inference, 2022
We study the selection of adjustment sets for estimating the interventional mean under an individualized treatment rule. We assume a non-parametric causal graphical model with, possibly, hidden variables and at least one adjustment set composed of ...
Smucler Ezequiel, Rotnitzky Andrea
doaj   +1 more source

Estimating Extreme Bivariate Quantile Regions [PDF]

, 2009
AMS 2000 subject classifications.
de Haan, L.F.M., Krajina, A., Einmahl, J.H.J.   +2 more
core  

Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions

Dependence Modeling
Kendall’s tau and conditional Kendall’s tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available estimators are computationally expensive and can be improved by averaging ...
van der Spek Rutger, Derumigny Alexis
doaj   +1 more source