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LocalCop: An R package for local likelihood inference for conditional copulas

Year: 2024

Type: preprint

Abstract: Conditional copulas models allow the dependence structure between multiple response variables to be modelled as a function of covariates. LocalCop (Acar & Lysy, 2024) is an R/C++ package for computationally efficient semiparametric conditional copula modelling using a local likelihood inference framework developed in Acar, Craiu, & Yao (2011), Acar, Craiu, & Yao (2013) and Acar, Czado, & Lysy (2019).

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2403.18245

Authors: Acar, Elif F., Lysy, Martin, Kuchinsky, Alan

Institutions: Hospital for Sick Children, University of Manitoba, University of Waterloo

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: Natural Sciences and Engineering Research Council of Canada

Awards: G2271590008, Dependence Models for Complex and Massive Data, Statistical Computing in Modern Scientific Analysis

OpenAlex ID: W4393300057

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