grad_vclogit: Evaluate gradient of the log likelihood

In kuriwaki/clusterCVR: A Clustering Algorithm for Cast Vote Records

Evaluate gradient of the log likelihood

Description

Evaluate gradient of the log likelihood

Usage

grad_vclogit(par, y_j, zeta_k, m_j)

Arguments

par	The parameter of interest. A (L)-length vector of mlogit coefficients for cluster k and office j. The coefficient for the reference category, corresponding to abstention, is abbreviated here. That coefficient is constrained to be 0. Therefore, the log likelihood appends 0 to the beginning each time.
y_j	N length vector of outcomes
zeta_k	N-length vector of posterior for membership in cluster k
m_j	N by (L + 1) matrix of missingness indicators

kuriwaki/clusterCVR documentation built on July 31, 2024, 8:28 p.m.