RSEML - Case-Based Least Squares Estimation of Nonlinear Structural Equation Models

Estimates structural equation models by case-based least squares: the latent scores of every observation are treated as free variables of a constrained optimization problem, so that arbitrary nonlinear model equations, bounds and constraints on latent variables and inequality constraints on parameters become possible. Model equations are specified as plain text (e.g. "y == a*exp(b*eta)"). Gradients are obtained by automatic differentiation via 'RTMB', and the constrained problem is solved with 'nloptr' (SLSQP or augmented Lagrangian). Missing data are handled case-wise. The methodology is described in Oldenburg (2024) <doi:10.19139/soic-2310-5070-1868> and Oldenburg (2025) <doi:10.19139/soic-2310-5070-2324>.