High-dimensional ABC

02/27/2018
by   D. J. Nott, et al.
0

This Chapter, "High-dimensional ABC", is to appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). It details the main ideas and concepts behind extending ABC methods to higher dimensions, with supporting examples and illustrations.

READ FULL TEXT
research
02/27/2018

Overview of Approximate Bayesian Computation

This Chapter, "Overview of Approximate Bayesian Computation", is to appe...
research
03/24/2022

Computation of Centroidal Voronoi Tessellations in High Dimensional spaces

Owing to the natural interpretation and various desirable mathematical p...
research
09/18/2007

Bayesian Classification and Regression with High Dimensional Features

This thesis responds to the challenges of using a large number, such as ...
research
03/26/2021

Higher Dimensional Graphics: Conceiving Worlds in Four Spatial Dimensions and Beyond

While the interpretation of high-dimensional datasets has become a neces...
research
03/06/2018

ABC and Indirect Inference

This chapter will appear in the forthcoming Handbook of Approximate Baye...
research
02/15/2022

High-dimensional dynamic factor models: a selective survey and lines of future research

High-Dimensional Dynamic Factor Models are presented in detail: The main...
research
10/06/2022

Fast Automatic Bayesian Cubature Using Matching Kernels and Designs

Automatic cubatures approximate integrals to user-specified error tolera...

Please sign up or login with your details

Forgot password? Click here to reset