Posted by **libr** at Oct. 23, 2015

English | 2013 | ISBN: 1466504056 | 626 pages | PDF | 3,2 MB

Posted by **interes** at Oct. 23, 2013

English | 2013 | ISBN: 1466504056 | 626 pages | PDF | 3,2 MB

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include…

Posted by **step778** at Aug. 17, 2017

2003 | pages: 258 | ISBN: 1590471415 | PDF | 3,3 mb

Posted by **fdts** at Dec. 1, 2016

by Carl Graham and Denis Talay

English | 2013 | ISBN: 3642393624 | 264 pages | PDF | 2.07 MB

Posted by **house23** at Nov. 10, 2016

MP4 | AVC 928kbps | English | 1280x720 | 30fps | 11h 42mins | AAC stereo 60kbps | 3.79 GB

Learn to program statistical applications and Monte Carlo simulations with numerous "real-life" cases and R software.

Posted by **naag** at Sept. 18, 2015

MP4 | Video: 1280x720 | 62 kbps | 44 KHz | Duration: 12 Hours | 3.79 GB

Learn to program statistical applications and Monte Carlo simulations with numerous "real-life" cases and R software.

Posted by **arundhati** at Dec. 6, 2014

2009 | ISBN-10: 0470772697 | 278 pages | PDF | 2 MB

Posted by **libr** at Sept. 26, 2014

English | ISBN: 3642393624 | 2013 | 264 pages | PDF | 2 MB

In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems.

Posted by **tanas.olesya** at Sept. 7, 2014

Wiley | March 12, 2007 | English | ISBN: 0470854944 | 348 pages | PDF | 3 MB

Simulation and Monte Carlo is aimed at students studying for degrees in Mathematics, Statistics, Financial Mathematics, Operational Research, Computer Science, and allied subjects, who wish an up-to-date account of the theory and practice of Simulation. Its distinguishing features are in-depth accounts of the theory of Simulation, including the important topic of variance reduction techniques, together with illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation.

Posted by **interes** at May 9, 2014

English | ISBN: 3642393624 | 2013 | 264 pages | PDF | 2 MB

In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems.