Data Analysis

TRAMA

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. <BR>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<BR>processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design. <BR>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<BR>for Bayesian computation called 'nested sampling'.

SOMMARIO

1 - The Basics2 - Parameter Estimation I3 - Parameter Estimation II4 - Model Selection5 - Assigning Probabilities6 - Non-parametric Estimation7 - Experimental Design8 - Least-Squares Extensions9 - Nested Sampling10 - Quantification

AUTORE

Devinderjit Singh Sivia Rutherford Appleton Laboratory Chilton Oxon OX11 5DJ John Skilling Maximum Entropy Data Consultants 42 Southgate Street Bury St Edmonds Suffolk IP33 2AZ

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9780198568322
• Dimensioni: 233 x 15.0 x 159 mm Ø 408 gr
• Formato: Brossura
• Illustration Notes: 68 line drawings + 1 halftone
• Pagine Arabe: 264