Results 41 to 50 of about 92 (91)
Automatic estimation procedure in partial linear model with functional data
Bandwidth selection, Cross-validation, Functional data, Partial linear regression, MSC 62G08, MSC 62G20,
Vieu, Philippe +3 more
core +1 more source
Tree-based conditional copula estimation
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 +2 more
doaj +1 more source
Goodness-of-fit Tests in Nonparametric Regression [PDF]
AMS classifications: 62G08, 62G10, 62G20, 62G30; 60F17.Goodness-of-fit;nonparametric regression;test for independence;weak ...
Einmahl, J.H.J., Keilegom, I. van
core +2 more sources
Orthogonal prediction of counterfactual outcomes
Orthogonal meta-learners, such as DR-learner (Kennedy EH. Towards optimal doubly robust estimation of heterogeneous causal effects. arXiv preprint arXiv:2004.14497 2020), R-learner (Nie X, Wager S.
Vansteelandt Stijn, Morzywołek Paweł
doaj +1 more source
Causal additive models with smooth backfitting
A fully nonparametric approach to learning causal structures from observational data is proposed. The method is described in the setting of additive structural equation models with a link to causal inference.
Morville Asger B., Park Byeong U.
doaj +1 more source
Sequential Kernel Estimation of the Conditional Intensity of Nonstationary Point Processes
California earthquakes, exponential weighting, prediction error criteria, sequential nonparametric regression, space–time point processes, Primary: 60G55, 62G07, 62L12, Secondary: 62G08, 62M30, 86A32,
Carlo Grillenzoni, GRILLENZONI, CARLO
core +1 more source
Local polynomial estimation of a conditional mean function with dependent truncated data
Asymptotic normality, Local polynomial estimator, Conditional mean function, Truncated data, α-mixing, 62E20, 62G08,
Jacobo de Uña-Álvarez +4 more
core +1 more source
Conservative inference for counterfactuals
In causal inference, the joint law of a set of counterfactual random variables is generally not identified. But many interesting quantities are functions of the joint distribution.
Balakrishnan Sivaraman +2 more
doaj +1 more source
Robust estimation of multivariate regression model
Local M-estimator, Local polynomial regression, Multivariate regression model, One-step, Robustness, Primary 62G35, Secondary 62G08,
Jiantao Li +3 more
core +1 more source
Understanding the complex interactions among multiple environmental exposures is critical for assessing their combined impact on health outcomes. This study introduces InterXshift, a novel semiparametric method that provides a nonparametric definition of
McCoy David B. +3 more
doaj +1 more source

