Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.
This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image
processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design.
The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique
for Bayesian computation called 'nested sampling'.
| Autorius: | D. S. Sivia |
| Leidėjas: | OUP UK |
| Išleidimo metai: | 2006 |
| Knygos puslapių skaičius: | 260 |
| ISBN-10: | 0198568320 |
| ISBN-13: | 9780198568322 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Bayesian inference |
Parašykite atsiliepimą apie „Data Analysis: A Bayesian Tutorial“
