Results 81 to 90 of about 3,668 (232)

Predicting Win‐Loss Probabilities for Composite Time‐to‐Event Outcomes Under The Proportional Win‐Fractions Regression Model

Statistics in Medicine, Volume 45, Issue 10-12, May 2026.
ABSTRACT For composite time‐to‐event outcomes, the win ratio as a relative measure ignores ties resulting from non‐occurrence of events, which can obscure important context in regression settings where event rates—and hence the proportion of ties—vary over time and across covariate values.
Lu Mao
wiley   +1 more source

Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market [PDF]

This paper develops the method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as ...
Dominique Guegan, Jing Zhang
core  

Dependence properties of bivariate copula families

Dependence Modeling
Motivated by recently investigated results on dependence measures and robust risk models, this article provides an overview of dependence properties of many well known bivariate copula families, where the focus is on the Schur order for conditional ...
Ansari Jonathan, Rockel Marcus
doaj   +1 more source

Joint Frailty Mixture Cure Model for Recurrent Event Data With Dependent Censoring: An MCEM Approach

Statistics in Medicine, Volume 45, Issue 10-12, May 2026.
ABSTRACT Advancements in modern medical technology have enabled cures for a fraction of patients while extending survival times for those who are not cured. For non‐cured patients, disease recurrence is influenced by observed covariates and unobserved individual heterogeneity (random effects).
Nasrin Sultana, Moudud Alam, Md Hasinur Rahaman Khan   +2 more
wiley   +1 more source

Farlie-Gumbel-Morgenstern bivariate log-normal: applications and comparison of semiparametric and parametric methods for estimating copulas

Kuwait Journal of Science
This study introduces the Farlie-Gumbel-Morgenstern bivariate log-normal (bivariate FGM-LN) distribution, which was created using the FGM copula to describe dependent skewed data.
Shakila Bashir, Bushra Masood, Muhammad Aslam   +2 more
doaj   +1 more source

Testing the bivariate distribution of daily equity returns using copulas: an application to the Spanish stock market

, 2005
In this paper we deal with the identification of dependencies between time series of equity returns. Marginal distribution functions are assumed to be known, and a bivariate chi-square test of fit is applied in a fully parametric copula approach. Several
Roch, Oriol, Alegre Escolano, Antonio
core  

Copulas for bivariate probability distributions

Electronics Letters, 2007
Copulas offer interesting insights into the dependence structures between the distributions of random variables. This report introduces new copulas, and provides an analysis for copulas, associated with bivariate exponential and Rayleigh distributions that have relevance to signal processing.
Durrani, T.S., Xueing, Z.
openaire   +3 more sources

Vine copulas structures modeling on Russian stock market

Discrete and Continuous Models and Applied Computational Science, 2019
Pair-copula constructions have proven to be a useful tool in statistical modeling, particularly in the field of finance. The copula-based approach can be used to choose a model that describes the dependence structure and marginal behaviour of the data in
Eugeny Yu. Shchetinin
doaj   +1 more source

Bivariate copula regression models for semi-competing risks. [PDF]

Stat Methods Med Res, 2023
Wei Y, Wojtyś M, Sorrell L, Rowe P.
europepmc   +1 more source

A copula model for dependent competing risks [PDF]

Many popular estimators for duration models require independent competing risks or independent censoring. In contrast, copula based estimators are also consistent in presence of dependent competing risks.
Ralf Wilke, Simon M. S. Lo
core   +2 more sources