A quadrature method for Bayesian sequential threshold estimation

Bayesian Gaussian Processes for Sequential Prediction, Optimisation and Quadrature

Robust Sequential Approximate Bayesian Estimation

An approximation tothe sequential updating of the distribution flocation parameters of a linear time series model is developed for non-normal observations. The behaviour of the resulting non-linear recursive filtering algorithm isexamined and shown to have certain desirable properties for a variety of non-normal error distributions. Illustrative examples are given and relationships with previou...

Bayesian Quadrature for Ratios: Now With Even More Bayesian Quadrature

We describe a novel approach to quadrature for ratios of probabilistic integrals, such as are used to compute posterior probabilities. This approach offers performance superior to Monte Carlo methods by exploiting a Bayesian quadrature framework. We improve upon previous Bayesian quadrature techniques by explicitly modelling the nonnegativity of our integrands, and the correlations that exist b...

Bayesian Quadrature for Ratios

We describe a novel approach to quadrature for ratios of probabilistic integrals, such as are used to compute posterior probabilities. This approach offers performance superior to Monte Carlo methods by exploiting a Bayesian quadrature framework. We improve upon previous Bayesian quadrature techniques by explicitly modelling the nonnegativity of our integrands, and the correlations that exist b...

A Statistical Method for Sequential Images – Based Process Monitoring

Today, with the growth of technology, monitoring processes by the use of video and satellite sensors have been more expanded, due to their rich and valuable information. Recently, some researchers have used sequential images for image defect detection because a single image is not sufficient for process monitoring. In this paper, by adding the time dimension to the image-based process monitorin...