One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. ( Katie St. Clair MAA Reviews)From the Publisher:
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 optimisation, 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'.
"Sobre este título" puede pertenecer a otra edición de este libro.
Descripción OUP Oxford, 2016. Paperback. Estado de conservación: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Nº de ref. de la librería ria9780198568315_lsuk
Descripción Oxford University Press, 2006. Hardcover. Estado de conservación: Brand New. 2nd edition. 246 pages. 9.25x6.25x0.75 inches. In Stock. Nº de ref. de la librería zk0198568312
Descripción Oxford University Press, USA, 2006. Hardcover. Estado de conservación: New. 2. Nº de ref. de la librería DADAX0198568312
Descripción Oxford University Press, 2006. Hardcover. Estado de conservación: New. book. Nº de ref. de la librería 0198568312