An Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing / Edition 1

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Overview

This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book’s highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational science, but do not need to be fully immersed in detailed statistical analysis.

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Product Details

Table of Contents

Introduction .- Inverse Problems and Subjective Computing.- Basic Problem of Statistical Inference.-The Praise Of Ignorance: Randomness as Lack of Information.- Basic Problem in Numerical Linear Algebra.- Sampling: First Encounter.- Statistically Inspired Preconditioners.- Conditional Gaussian Densities and Predictive Envelopes.- More Applications of the Gaussian Conditioning.- Sampling: The Real Thing.- Wrapping up: Hypermodel, Dynamic Priorconditioners and Bayesian Learning.

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