Practical Bayesian Inference: A Primer for Physical Scientists

ISBN-13: 9781316642214 / Angielski / Miękka / 2017 / 320 str.

Coryn A. L. (Max-Planck-Institut fur Astronomi Bailer-Jones

Opis

This book introduces the major concepts of probability and statistics, along with the necessary computational tools, for undergraduates and graduate students.

Recenzje

'Practical Bayesian Inference provides the fundamental concepts of probability and statistics as well as the computational mechanisms that an average student may use to extract maximum information from data plagued with uncertainties.' Fred Boadu, The Leading Edge

Spis treści

Preface; 1. Probability basics; 2. Estimation and uncertainty; 3. Statistical models and inference; 4. Linear models, least squares, and maximum likelihood; 5. Parameter estimation: single parameter; 6. Parameter estimation: multiple parameters; 7. Approximating distributions; 8. Monte Carlo methods for inference; 9. Parameter estimation: Markov chain Monte Carlo; 10. Frequentist hypothesis testing; 11. Model comparison; 12. Dealing with more complicated problems; References; Index.