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Global convergence and ascent property of a cyclic algorithm used for statistical analysis of crash data. (English. French summary) Zbl 06885664
Summary: 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.

MSC:
62F10 Point estimation
62H12 Estimation in multivariate analysis
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