Pairwise likelihood inference for the multivariate ordered probit model
Methodology
2019-01-30 v1
Abstract
This paper provides a closed form expression for the pairwise score vector for the multivariate ordered probit model. This result has several implications in likelihood-based inference. It is indeed used both to speed-up gradient based optimization routines for point estimation, and to provide a building block to compute standard errors and confidence intervals by means of the Godambe matrix.
Cite
@article{arxiv.1901.10186,
title = {Pairwise likelihood inference for the multivariate ordered probit model},
author = {Martina Bravo and Antonio Canale},
journal= {arXiv preprint arXiv:1901.10186},
year = {2019}
}