Results 11 to 20 of about 58,855 (160)

The Challenge of Time‐to‐Event Analysis for Multiple Events: A Guided Tour From Time‐to‐First‐Event to Recurrent Time‐to‐Event Analysis [PDF]

Biometrical Journal, Volume 68, Issue 1, February 2026.
ABSTRACT Clinical trials often compare a treatment to a control group concerning multiple possible combined time‐to‐event endpoints like hospital‐free survival. Thereby, the first endpoint may occur more than once (“recurrent”), whereas the second endpoint is absorbing. Inclusion of all observed events in the analysis can increase the power and provide
Sandra Schmeller, Alexandra Erdmann, Jan Beyersmann, Christiane Angermann, Ann‐Kathrin Ozga   +4 more
wiley   +2 more sources

Semiparametric minimax rates

Electronic Journal of Statistics, 2009
We consider the minimax rate of testing (or estimation) of non-linear functionals defined on semiparametric models. Existing methods appear not capable of determining a lower bound on the minimax rate of testing (or estimation) for certain functionals of interest.
Robins, James, Tchetgen Tchetgen, Eric, Li, Lingling, van der Vaart, Aad   +3 more
openaire   +4 more sources

Semiparametric Tail Index Regression [PDF]

Journal of Business & Economic Statistics, 2020
Abstract–Understanding why extreme events occur is often of major scientific interest in many fields. The occurrence of these events naturally depends on explanatory variables, but there is a severe lack of flexible models with asymptotic theory for understanding this dependence, especially when variables can affect the outcome nonlinearly.
Rui Li, Chenlei Leng, Jinhong You
openaire   +1 more source

Bayesian variants of some classical semiparametric regression techniques [PDF]

, 2004
This paper develops new Bayesian methods for semiparametric inference in the partial linear Normal regression model: y=zβ+f(x)+var epsilon where f(.) is an unknown function.
Koop, Gary, Poirier, Dale J.
core   +1 more source

Semiparametric theory and empirical processes in causal inference

, 2016
In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and ...
A. Belloni, A. Belloni, A.A. Tsiatis, A.R. Luedtke, A.W. Vaart van der, A.W. Vaart van der, A.W. Vaart van der, A.W. Vaart van der, B. Chakraborty, C.F. Manski, D. Pollard, D. Pollard, D.B. Rubin, D.B. Rubin, D.W.K. Andrews, D.W.K. Andrews, E. Tchetgen, E. Tchetgen, E. Tchetgen, E.H. Kennedy, E.L. Ogburn, G.R. Shorack, I. Diaz, I. Diaz, J. Hahn, J. Pearl, J. Pearl, J. Pfanzagl, J. Pfanzagl, J.D. Angrist, J.L. Horowitz, J.M. Begun, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, L.A. Stefanski, M. Carone, M.A. Hernan, M.G. Hudgens, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.L. Petersen, M.R. Kosorok, P.A. Dawid, P.J. Bickel, R. Neugebauer, R.D. Gill, S. Rose, S.A. Murphy, T.J. VanderWeele, T.J. VanderWeele, T.J. VanderWeele, T.J. VanderWeele, W. Zheng, W.K. Newey, W.K. Newey   +64 more
core   +1 more source

Rank‐based estimation of propensity score weights via subclassification

Canadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang, Yuexia Zhang, Thomas S. Richardson, Xiaohua Zhou   +3 more
wiley   +1 more source

Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions

Canadian Journal of Statistics, EarlyView.
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni, Luca Merlo, Lea Petrella   +2 more
wiley   +1 more source

Semiparametric CRB and Slepian-Bangs formulas for Complex Elliptically Symmetric Distributions

, 2019
The main aim of this paper is to extend the semiparametric inference methodology, recently investigated for Real Elliptically Symmetric (RES) distributions, to Complex Elliptically Symmetric (CES) distributions. The generalization to the complex field is
Fortunati, Stefano, Gini, Fulvio, Greco, Maria, Rangaswamy, Muralidhar, Zoubir, Abdelhak   +4 more
core   +1 more source

Semiparametric Additive Regression

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1992
SUMMARY A simple estimator for β is proposed for the model y = x'β + g(t)+ error, g smooth but unknown. The approach is to approximate the estimating equation obtained from a ***semiparametric likelihood and in the simplest case reduces to minimizing the distance between the 'pseudoresiduals' y - x'β and a local linear cross-validated ...
openaire   +2 more sources

Bayesian clustering of multivariate extremes

Canadian Journal of Statistics, EarlyView.
Abstract The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications ...
Sonia Alouini, Anthony C. Davison
wiley   +1 more source