optimizing: Maximum-likelihood estimation

In RStanTVA: TVA Models in 'Stan' using 'R' and 'StanTVA'

Maximum-likelihood estimation

Description

Obtain a point estimate by maximizing the joint posterior from the StanTVA model.

Usage

optimizing(object, ...)

## S4 method for signature 'stantvamodel'
optimizing(object, data, init, seed = sample.int(.Machine$integer.max, 1), ...)

Arguments

object	The StanTVA model object.
...	Further arguments passed to rstan::optimizing().
data	The data to which the model should be fitted, usually a data.frame.
init	How to initialize the individual chains, see rstan::optimizing(). Note that for random, any lower-level hierarchical (e.g., subject-level) parameters are initialized to zero.
seed	Seed for random number generation and chain initialization

Value

A list, representing the maximum-likelihood estimate, see rstan::optimizing().

Functions

• optimizing(stantvamodel): method

RStanTVA documentation built on Dec. 17, 2025, 1:06 a.m.