The aim of this tutorial is to enable the participants to learn how to use the R package “SamplingStrata” in order to optimize the design of stratified samples. The package offers an approach for the ...

In Part 1 of this series, we covered the fundamental concepts and principles incorporated by flow meters along with various flow measurement methods used in mechanical flow meters. It covered in depth ...

The marginal likelihood plays an important role in many areas of Bayesian statistics such as parameter estimation, model comparison, and model averaging. In most applications, however, the marginal ...

This tutorial is a guide to understanding the Zig-Zag Process, a new sampling method, described in the document THE ZIG-ZAG PROCESS AND SUPER-EFFICIENT SAMPLING FOR BAYESIAN ANALYSIS OF BIG DATA ...

Abstract: Thompson sampling is an algorithm for online decision problems where actions are taken sequentially in a manner that must balance between exploiting what is known to maximize immediate ...

Abstract: This article describes a computational method, called the Fourier sampling algorithm. The algorithm takes a small number of (correlated) random samples from a signal and processes them ...

With increasingly efficient columns, eluite peaks are increasingly narrower. To take full advantage of this, choice of the detector response time and the data acquisition rate a.k.a. detector sampling ...