.set_vc

<p>The input is given according to the reparameterization used by tramTMB</p>

as.theta

<p>Set the parameters of the random effect covariance matrix</p>

Likelihood-based estimation of mixed-effects transformation models using the Template
Model Builder (TMB, Kristensen et al., 2016, <doi:10.18637/jss.v070.i05>). The technical details
of transformation models are given in Hothorn et al. (2018, <doi:10.1111/sjos.12291>). Likelihood
contributions of exact, randomly censored (left, right, interval) and truncated observations are
supported. The random effects are assumed to be normally distributed on the scale of the
transformation function, the marginal likelihood is evaluated using the Laplace approximation,
and the gradients are calculated with automatic differentiation (AD).

Balint Tamasi

State of Data and AI Literacy Report 2025

.set_vc: Set the parameters of the random effect covariance matrix

Description

Usage

Arguments

Value