期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2015
卷号：39
期号：1
页码：109-126
语种：English
出版社：SORT- Statistics and Operations Research Transactions
摘要：Likelihood estimates of the Dirichlet distribution parameters can be obtained only through numerical algorithms. Such algorithms can provide estimates outside the correct range for the parameters and/or can require a large amount of iterations to reach convergence. These problems can be aggravated if good starting values are not provided. In this paper we discuss several approaches that can partially avoid these problems providing a good trade-off between efficiency and stability. The performances of these approaches are compared on high-dimensional real and simulated data.
关键词：Levenberg-Marquardt algorithm, re-parametrization, starting values, metabolomics data
