A note on convergence requirements for nonlinear maximum-likelihood estimation of parameters from mixture models

DOI10.1016/0305-0548(85)90048-6zbMath0603.62030OpenAlexW2022340033MaRDI QIDQ1082735

Carl M. Harris, Jay Mandelbaum

Publication date: 1985

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0305-0548(85)90048-6

zbMATH Keywords

algorithmsmaximum-likelihood estimationmixed exponential and Weibull distributions

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Nonlinear programming (90C30)

Cites Work

• Unnamed Item

This page was built for publication: A note on convergence requirements for nonlinear maximum-likelihood estimation of parameters from mixture models