Abstract

The author analyzes the convergence properties of the EM algorithm for iteratively approximating the maximum likelihood estimate. A radius of convergence is specified and the asymptotic rate of convergence of the algorithm derived via the multivariate Taylor expansion with remainder. The radius and rate of convergence generally depend on the choice of complete data. The results can be used to evaluate different choices of complete data space in terms of algorithm performance. >

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.