Posted by **nebulae** at May 19, 2015

English | ISBN: 0956372848 | 2013 | 180 pages | PDF | 6 MB

Posted by **roxul** at June 2, 2015

English | ISBN: 1584888490 | 2013 | 399 pages | PDF | 3 MB

Posted by **libr** at Feb. 19, 2016

English | 2001 | 306 Pages | ISBN: 0415234646 , 0415234654 | PDF | 7 MB

Posted by **interes** at Feb. 9, 2013

2 edition 2001 | 306 Pages | ISBN: 0415234646 , 0415234654 | PDF | 7 MB

This best-selling introduction to language studies includes a huge range of activities and projects, introducing core areas of language structure and grammar through analysis of real texts. Ideal for both A level and beginning undergraduate students, this second edition includes:

Posted by **hill0** at Feb. 5, 2017

English | 4 Aug. 2016 | ISBN: 3319324276 | 250 Pages | EPUB | 3.28 MB

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students.

Posted by **interes** at Nov. 21, 2016

English | 2016 | ISBN: 3319324276 | 232 pages | PDF | 4 MB

Posted by **interes** at Feb. 1, 2015

English | 2006-08-28 | ISBN: 0387400842 | PDF | 352 pages | 4,6 MB

Posted by **ChrisRedfield** at Dec. 3, 2013

Published: 2006-08-28 | ISBN: 0387400842 | PDF | 352 pages | 4 MB

Posted by **Direktor69** at June 20, 2013

ISBN: 0387400842 | edition 2006 | PDF | 356 pages | 15 mb

This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing.

Posted by **mowmow** at July 4, 2007

Publisher:Springer (2006-07-27) | ISBN-10: 0387400842 | PDF | 3.3 Mb | 352 pages

This book is a contemporary introduction to theory, methods and computation in Bayesian Analysis. It focuses on topics that have stood the test of time and emerging areas such as reference priors, objective Bayes testing, Bayesian model selection and wavelets. No other such book is available in the market.