Binary Outcome Copula Regression Model with Sampling Gradient Fitting

2021/01/03 by Weijian Luo, Luo, Weijian, Mai Wo +1
Economics, Econometrics and Finance · Mathematics · #Advanced Statistical Methods and Models #Applications (stat.AP) #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.2101.00592

openalex publication_date 2021/01/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Use copula to model dependency of variable extends multivariate gaussian assumption. In this paper we first empirically studied copula regression model with continous response. Both simulation study and real data study are given. Secondly we give a novel copula regression model with binary outcome, and we propose a score gradient estimation algorithms to fit the model. Both simulation study and real data study are given for our model and fitting algorithm.

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