clespr: Composite Likelihood Estimation for Spatial Data

Composite likelihood approach is implemented to estimating statistical models for spatial ordinal and proportional data based on Feng et al. (2014) <doi:10.1002/env.2306>. Parameter estimates are identified by maximizing composite log-likelihood functions using the limited memory BFGS optimization algorithm with bounding constraints, while standard errors are obtained by estimating the Godambe information matrix.

Getting started

Package details

AuthorTing Fung (Ralph) Ma [cre, aut], Wenbo Wu [aut], Jun Zhu [aut], Xiaoping Feng [aut], Daniel Walsh [ctb], Robin Russell [ctb]
MaintainerTing Fung (Ralph) Ma <>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the clespr package in your browser

Any scripts or data that you put into this service are public.

clespr documentation built on May 2, 2019, 9:44 a.m.