Results 31 to 40 of about 110 (98)

Mediated probabilities of causation

Journal of Causal Inference
We propose a set of causal estimands that we call “the mediated probabilities of causation.” These estimands quantify the probabilities that an observed negative outcome was induced via a mediating pathway versus a direct pathway in a stylized setting ...
Rubinstein Max, Cuellar Maria, Malinsky Daniel   +2 more
doaj   +1 more source

On certain transformations of Archimedean copulas: Application to the non-parametric estimation of their generators

Dependence Modeling, 2013
We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
doaj   +1 more source

Causal additive models with smooth backfitting

Journal of Causal Inference
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

Nonparametric expectile shortfall regression for functional data

Demonstratio Mathematica
This work addresses the issue of financial risk analysis by introducing a novel expected shortfall (ES) regression model, which employs expectile regression to define the shortfall threshold in financial risk management.
Almanjahie Ibrahim M., Abood Hanan, Bouzebda Salim, Alshahrani Fatimah, Laksaci Ali   +4 more
doaj   +1 more source

A study on discrete and discrete fractional pharmacokinetics-pharmacodynamics models for tumor growth and anti-cancer effects

Computational and Mathematical Biophysics, 2019
We study the discrete and discrete fractional representation of a pharmacokinetics - pharmacodynamics (PK-PD) model describing tumor growth and anti-cancer effects in continuous time considering a time scale hℕ0h$h\mathbb{N}_0^h$, where h > 0.
Atıcı Ferhan M., Atıcı Mustafa, Nguyen Ngoc, Zhoroev Tilekbek, Koch Gilbert   +4 more
doaj   +1 more source

An approach to nonparametric inference on the causal dose–response function

Journal of Causal Inference
The causal dose–response curve is commonly selected as the statistical parameter of interest in studies where the goal is to understand the effect of a continuous exposure on an outcome.
Hudson Aaron, Geng Elvin H., Odeny Thomas A., Bukusi Elizabeth A., Petersen Maya L., van der Laan Mark J.   +5 more
doaj   +1 more source

Valid causal inference with unobserved confounding in high-dimensional settings

Journal of Causal Inference
Various methods have recently been proposed to estimate causal effects with confidence intervals that are uniformly valid over a set of data-generating processes when high-dimensional nuisance models are estimated by post-model-selection or machine ...
Moosavi Niloofar, Gorbach Tetiana, de Luna Xavier   +2 more
doaj   +1 more source

Neyman meets causal machine learning: Experimental evaluation of individualized treatment rules

Journal of Causal Inference
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s ...
Li Michael Lingzhi, Imai Kosuke
doaj   +1 more source

Simulation analysis of non-respondent information in context of small domain

Heliyon
In the real-world, there are various situations when all units are not accessible of the respondent called unit non-response. The effect of unit non-response is a tricky matter for estimating the total number of unit.
Ashutosh Ashutosh, Marius Stefan, Piyush Kant Rai, Walid Emam, Soofia Iftikhar, Malik Muhammad Anas   +5 more
doaj   +1 more source

Strong laws for weighted sums of widely orthant dependent random variables and applications

Open Mathematics
In this study, the strong law of large numbers and the convergence rate for weighted sums of non-identically distributed widely orthant dependent random variables are established.
Zhu Yong, Wang Wei, Chen Kan
doaj   +1 more source