Essentials of Monte Carlo Simulation

Statistical Methods for Building Simulation Models

Nonfiction, Science & Nature, Mathematics, Statistics, Computers, Application Software
Cover of the book Essentials of Monte Carlo Simulation by Nick T. Thomopoulos, Springer New York
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Nick T. Thomopoulos ISBN: 9781461460220
Publisher: Springer New York Publication: December 19, 2012
Imprint: Springer Language: English
Author: Nick T. Thomopoulos
ISBN: 9781461460220
Publisher: Springer New York
Publication: December 19, 2012
Imprint: Springer
Language: English

**Essentials of Monte Carlo Simulation **focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications.  The text also contains an easy to read  presentation with minimal use of difficult mathematical concepts.  Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

**Essentials of Monte Carlo Simulation **focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications.  The text also contains an easy to read  presentation with minimal use of difficult mathematical concepts.  Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics. 

More books from Springer New York

Cover of the book Pathological Potential of Neuroglia by Nick T. Thomopoulos
Cover of the book Justice, Conflict and Wellbeing by Nick T. Thomopoulos
Cover of the book Immunocomputing by Nick T. Thomopoulos
Cover of the book Multifunctional Nanoparticles for Drug Delivery Applications by Nick T. Thomopoulos
Cover of the book Calculus II by Nick T. Thomopoulos
Cover of the book The Archaeology of Interdependence by Nick T. Thomopoulos
Cover of the book Carbonate Microfabrics by Nick T. Thomopoulos
Cover of the book Human Development and Criminal Behavior by Nick T. Thomopoulos
Cover of the book Affirmative Action in Perspective by Nick T. Thomopoulos
Cover of the book Attention Deficit Hyperactivity Disorder Handbook by Nick T. Thomopoulos
Cover of the book Youth Criminal Justice Policy in Canada by Nick T. Thomopoulos
Cover of the book Foodborne Microbial Pathogens by Nick T. Thomopoulos
Cover of the book The Business of Bioscience by Nick T. Thomopoulos
Cover of the book Genetic Damage in Human Spermatozoa by Nick T. Thomopoulos
Cover of the book Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis by Nick T. Thomopoulos
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy