Equi-energy sampler with applications in statistical inference and statistical mechanics

• 成果类型: Editorial Material
• 署名作者: Kou, S. C.; Zhou, Qing; Wong, Wing Hung
• 署名单位: Harvard University; Stanford University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053606000000515
• 发表日期: 2006
• 页码: 1581-1619
• 关键词: chain monte-carlo; markov-chains; distributions; DISCOVERY; motifs; sites

摘要

We introduce a new sampling algorithm, the equi-energy sampler, for efficient statistical sampling and estimation. Complementary to the widely used temperature-domain methods, the equi-energy sampler, utilizing the temperature-energy duality, targets the energy directly. The focus on the energy function not only facilitates efficient sampling, but also provides a powerful means for statistical estimation, for example, the calculation of the density of states and microcanonical averages in statistical mechanics. The equi-energy sampler is applied to a variety of problems, including exponential regression in statistics, motif sampling in computational biology and protein folding in biophysics.