Global convergence and ascent property of a cyclic algorithm used for statistical analysis of crash data

Abstract

In this paper, we consider an estimation algorithm called cyclic iterative algorithm (CA) that is used in statistics to estimate the unknown vector parameter of a crash data model. We provide a theoretical proof of the global convergence of the CA that justifies the good numerical results obtained in early numerical studies of this algorithm. We also prove that the CA is an ascent algorithm, what ensures its numerical stability.

Keywords: Iterative method, Maximum likelihood, cyclic algorithm, global convergence, road safety

AMS 2010 Mathematics Subject Classification : 62-04, 62F10, 62H12, 62P99