log_likelihood_ind {lddmm}

Log-likelihood computation for a single observation

Description

Compute the log-likelihood for the drift-diffusion model, including the censored data contribution, for a single observation.

Usage

log_likelihood_ind(tau, mu, b, delta, cens, D)

Arguments

tau

vector of size n containing the response times

mu

matrix of size (n x d1) containing the drift parameters corresponding to the n response times for each possible d1 decision

b

matrix of size (n x d1) containing the boundary parameters corresponding to the n response times for each possible d1 decision

delta

vector of size n containing the offset parameters corresponding to the n response times

cens

vector of size n containing censoring indicators (1 censored, 0 not censored) corresponding to the n response times

D

(n x 2) matrix whose first column has the n input stimuli, and whose second column has the n decision categories