| Rick Durrett - Mathematics - 2010
This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains ... | |
| Frank Beichelt - Business & Economics - 2016 - 562 pages
Applied Probability and Stochastic Processes, Second Edition presents a self-contained introduction to elementary probability theory and stochastic processes with a special ... | |
| Jean-Michel Marin, Christian Robert - Computers - 2007 - 255 pages
This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on ... | |
| Christian Robert, George Casella - Computers - 2009 - 284 pages
This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the ... | |
| Jonathan Borwein, Matthew P. Skerritt - Mathematics - 2011 - 216 pages
Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of ... | |
| Jonathan Borwein, Matthew P. Skerritt - Mathematics - 2012 - 224 pages
Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of ... | |
| Jim Albert - Mathematics - 2009 - 300 pages
There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number ... | |
| Karline Soetaert, Jeff Cash, Francesca Mazzia - Computers - 2012 - 248 pages
Mathematics plays an important role in many scientific and engineering disciplines. This book deals with the numerical solution of differential equations, a very important ... | |
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