Non-Uniform Random Variate Generation
by Luc Devroye
Publisher: Springer 1986
ISBN/ASIN: 0387963057
ISBN-13: 9780387963051
Number of pages: 843
Description:
This text is about one small field on the crossroads of statistics, operations research and computer science. Statisticians need random number generators to test and compare estimators before using them in real life. In operations research, random numbers are a key component in large scale simulations. Computer scientists need randomness in program testing, game playing and comparisons of algorithms.
Download or read it online for free here:
Download link
(37MB, ZIP/PDF)
Download mirrors:
Mirror 1
Similar books
Think Stats: Probability and Statistics for Programmersby Allen B. Downey - Green Tea Press
Think Stats is an introduction to Probability and Statistics for Python programmers. This new book emphasizes simple techniques you can use to explore real data sets and answer interesting statistical questions. Basic skills in Python are assumed.
(27179 views)
Bayesian Spectrum Analysis and Parameter Estimationby G. Larry Bretthorst - Springer
This work is a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis.
(21073 views)
Seeing Theory: A visual introduction to probability and statisticsby T. Devlin, J. Guo, D. Kunin, D. Xiang - Brown University
The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...
(12829 views)
Markov Chains and Stochastic Stabilityby S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(24728 views)