calc_log_like: Calculate the Log-Likelihood

In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

Calculate the Log-Likelihood

Description

Wrapper function around log_like_heart

Usage

calc_log_like(pdfs, t_vec, obs_data, conds)

log_like_heart(pdf_u, pdf_l, t_vec, rts_u, rts_l)

Arguments

pdfs	a list of pdfs (see details)
t_vec	time space
obs_data	a list of obs_data
conds	all conditions of a model
pdf_u, pdf_l	numeric vectors of the pdfs (unpacked)
rts_u, rts_l	numeric vectors of the observed RTs (unpacked)

Details

calc_log_like

Iterates over all conditions, and passes forward the (unpacked) arguments to log_like_heart, adding each log-likelihood of a condition.

pdfs must be a list with entries named as the conditions, and then each condition being a list of the two PDFs (named pdf_u and pdf_l)

obs_data must be a list with entries "rts_u" and "rts_l", and then each rts_* entry being a named list with the RT values for each condition

log_like_heart

Gets the density values for RTs in rts_u/rts_l via stats::approx(), takes the log of that, and then sums across both. Wraps up the calculation in a tryCatch statement, throwing warnings when log_like_values can not be calculated

Value

a single value of the log-likelihood

dRiftDM documentation built on April 3, 2025, 7:48 p.m.