functional to be minimized and includes the iteratively reweighted least squares algorithm as a special case. We prove … unconstrained settings. The algorithm is applied to TV penalized quantile regression and is compared with a step size corrected … Newton-Raphson algorithm. It is found that typically in the first steps the iteratively reweighted least squares algorithm …

various ways. The core algorithm determines the generality of terms and iteratively inserts them in a growing taxonomy …. Variants of the algorithm are created by altering the way and the frequency, generality of terms is calculated. We analyse the …

nested fixed-point (NFXP) approach. We propose a new constrained optimization approach for structural estimation. We show … that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally … optimization approach can be significantly faster. -- structural estimation ; dynamic discrete choice models ; constrained …