weightedCL-package: Efficient and feasible inference for high-dimensional normal...

In weightedCL: Efficient and Feasible Inference for High-Dimensional Normal Copula Regression Models

Efficient and feasible inference for high-dimensional normal copula regression models

Description

The weighted composite likelihood estimating equations for high-dimensional normal copula regression models in Nikoloulopoulos (2023).

Details

This package contains R functions to estimate high-dimensional MVN copula regression models with the WCL estimating equations in Nikoloulopoulos (2022). It provides ARMA(p, q) correlation structures and binary, ordinal, Poisson, and negative binomial (both NB1 and NB2 parametrizations) regressions.

Author(s)

Aristidis K. Nikoloulopoulos.

References

Nikoloulopoulos, A.K. (2023) Efficient and feasible inference for high-dimensional normal copula regression models. Computational Statistics and Data Analysis, 179, 107654. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.csda.2022.107654")}.

weightedCL documentation built on June 8, 2025, 11:36 a.m.