## Abstract The expectation maximization (EM) algorithm is an iterative procedure used to determine maximum likelihood estimators in situations of incomplete data. In the case of independent Poisson variables it converges to a solution of a problem of the form min β[γ__a__^i^,__x__γ β __b__~i~ log
Optimized convergence for multiple histogram analysis
β Scribed by Tristan Bereau; Robert H. Swendsen
- Publisher
- Elsevier Science
- Year
- 2009
- Tongue
- English
- Weight
- 377 KB
- Volume
- 228
- Category
- Article
- ISSN
- 0021-9991
No coin nor oath required. For personal study only.
β¦ Synopsis
We propose a new algorithm for solving the weighted histogram analysis method (WHAM) equations to estimate free energies out of a set of Monte Carlo (MC) or molecular dynamics (MD) simulations. The algorithm, based on free-energy differences, provides a more natural way of approaching the problem and improves convergence compared to the widely used direct iteration method. We also study how parameters (temperature, pressure, etc.) of the independent simulations should be chosen to optimize the accuracy of the set of free energies.
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