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weightedCL (version 0.5)

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

Description

Estimates high-dimensional multivariate normal copula regression models with the weighted composite likelihood estimating equations in Nikoloulopoulos (2022) . It provides autoregressive moving average correlation structures and binary, ordinal, Poisson, and negative binomial regressions.

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Version

Install

install.packages('weightedCL')

Monthly Downloads

493

Version

0.5

License

GPL (>= 3.5.0)

Maintainer

Aristidis Nikoloulopoulos

Last Published

October 10th, 2022

Functions in weightedCL (0.5)

cl

COMPOSITE LIKELIHOOD ESTIMATION FOR MVN COPULA
weightMat

WEIGHT MATRICES FOR THE WEIGHTED COMPOSITE LIKELIHOOD ESTIMATING EQUATIONS
godambe

INVERSE GODAMBE MATRIX
iee.ord

Maximum Likelihood for Ordinal Model
polio

Polio cases in USA from Jan 1970 till Dec 1983
iee

INDEPENDENT ESTIMATING EQUATIONS FOR BINARY AND COUNT REGRESSION
wcl

SOLVING THE WEIGHTED COMPOSITE LIKELIHOOD ESTIMATING EQUATIONS WITH INPUTS THE WEIGHT MATRICES AND DATA
sleep

Infant sleep status data
weightedCL-package

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

DENSITY AND CDF OF THE UNIVARIATE MARGINAL DISTRIBUTION
pbvt

BIVARIATE NORMAL AND STUDENT CDFs WITH VECTORIZED INPUTS