Xi'an's Og

Hurray, our signed mixture simulation paper has been accepted by Statistics & Computing! If Og’s readers remember my earlier post about this problem, things get surprisingly more complicated when the mixture weights can take negative values. For instance, the naïve solution consisting in first simulating from the associated mixture of positive weight components and then using an accept-reject step may prove highly inefficient since the overall probability of acceptance can get arbitrarily close to zero. Substituting to this naïve version, we construct an alternative accept-reject scheme based on pairing positive and negative components as efficiently as possible, partitioning the real line, and finding tighter upper and lower bounds on positive and negative components, respectively, towards yielding a higher acceptance rate on average. In retrospect, the problem was beyond the reach of the undergraduate students we supervised (pre-COVID) on a research internship!

This entry was posted on December 17, 2024 at 12:24 am and is filed under pictures, Running with tags academic publisher, accept-reject algorithm, acceptance, acceptance probability, article, COVID-19, inverse cdf, master project, PSL Research University, publication, signed mixture, simulation, Statistics and Computing, Université Paris Dauphine, ziggurat algorithm. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.