The use of Bayesian inference for the analysis of complex statistical models has increased dramatically in recent years, in part due to the increasing availability of computing power. There are a range of techniques available for carrying out Bayesian inference, but the lack of analytic tractability for the vast majority of models of interest means that most of the techniques are numeric, and m...

We study inference for parameters defined by either classical extremum estimators or Laplace-type subject to general nonlinear constraints on the parameters. show that running MCMC penalized version of problem offers a computationally attractive alternative solving original constrained optimization problem. Bayesian credible intervals are asymptotically valid confidence in pointwise sense, prov...

Abstract Efficient sampling of many-dimensional and multimodal density functions is a task great interest in many research fields. We describe an algorithm that allows parallelizing inherently serial Markov chain Monte Carlo (MCMC) by partitioning the space function parameters into multiple subspaces each them independently. The samples different are then reweighted their integral values stitch...

Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews the main challenges sampling from parameter posterior of a network via MCMC. Such culminate to lack convergence posterior. Nevertheless, this shows that nonconverged chain, generated MCMC space network, can yield marginalization valuable predictive distribution ...

نقش سلولهای خونی به عنوان اجزای اصلی دفاع فیزیولوژیک حشرات مهم گزارش شده است. اولین فاکتورهای سیستم گردش خون هستند که در مقابله با انواع تنشها و عوامل بیگانه مشارکت می کنند. تحقیق حاضر، چهار نوع هموسیت همولنف لارو سن چهارم خرطوم بلند دمبرگ چغندرقند شناسایی شد شامل پروهموسیتها، گرانولوسیتها، پلاسموتوسیتها انوسیتوئیدها هستند. بزرگترین از نظر اندازه بودند مجموع فراوانی گرانولوسیتها لاروهای سنین سو...

In geostatistics, Gaussian random fields are often used to model heterogeneities of soil or subsurface parameters. To give spatial approximations these fields, they discretized. Then, different techniques geostatistical inversion condition them on measurement data. Among techniques, Markov chain Monte Carlo (MCMC) stand out, because yield asymptotically unbiased conditional realizations. Howeve...