Markov Chain Monte Carlo: Innovations And Applications (lecture Notes Series, Institute For Mathematical Sciences, N)

Dynamics in Models of Coarsening, Coagulation, Condensation and Quantization (Lecture Notes Series, Institute for Mathematical

Dynamics in Models of Coarsening, Coagulation, Condensation and Quantization (Lecture Notes Series, Institute for Mathematical Sciences, N) (Lecture Note Series) By Weizhu Bao, Jian-Guo Liu
2007 | 308 Pages | ISBN: 9812708502 | PDF | 4 MB

Markov Chain Monte Carlo: Innovations And Applications (repost)  eBooks & eLearning

Posted by interes at Oct. 4, 2018
Markov Chain Monte Carlo: Innovations And Applications (repost)

Markov Chain Monte Carlo: Innovations And Applications by W. S. Kendall and J. S. Wang
English | 2006 | ISBN: 9812564276 | 240 pages | PDF | 3,5 MB

MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo  eBooks & eLearning

Posted by AvaxGenius at Oct. 23, 2022
MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo

MCMC from Scratch: A Practical Introduction to Markov Chain Monte Carlo by Masanori Hanada, So Matsuura
English | PDF,EPUB | 2022 | 198 Pages | ISBN : 9811927146 | 29.3 MB

This textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves.

An Introduction to Sequential Monte Carlo  eBooks & eLearning

Posted by AvaxGenius at Oct. 2, 2020
An Introduction to Sequential Monte Carlo

An Introduction to Sequential Monte Carlo by Nicolas Chopin
English | PDF,EPUB | 2020 | 390 Pages | ISBN : 3030478440 | 30 MB

This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics.

Monte Carlo-Algorithmen (Repost)  eBooks & eLearning

Posted by AvaxGenius at Aug. 28, 2022
Monte Carlo-Algorithmen (Repost)

Monte Carlo-Algorithmen by Thomas Müller-Gronbach, Erich Novak, Klaus Ritter
Deutsch | PDF | 2012 | 332 Pages | ISBN : 3540891404 | 8.1 MB

Der Text gibt eine Einführung in die Mathematik und die Anwendungsmöglichkeiten der Monte Carlo-Methoden und verwendet dazu durchgängig die Sprache der Stochastik. Der Leser lernt die Grundprinzipien und wesentlichen Eigenschaften dieser Verfahren kennen und wird dadurch in den Stand versetzt, dieses wichtige algorithmische Werkzeug kompetent einsetzen und die Ergebnisse interpretieren zu können.
Markov chain monte carlo simulations and their statistical analysis: with web-based fortran code (repost)

Markov chain monte carlo simulations and their statistical analysis: with web-based fortran code by Bernd A. Berg
English | 2004 | ISBN: 9812389350 | 380 pages | PDF | 14,7 MB

Markov Logic: An Interface Layer for Artificial Intelligence  eBooks & eLearning

Posted by AvaxGenius at Sept. 23, 2022
Markov Logic: An Interface Layer for Artificial Intelligence

Markov Logic: An Interface Layer for Artificial Intelligence by Pedro Domingos
English | PDF | 2009 | 155 Pages | ISBN : 1598296922 | 1.3 MB

Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit.

Infinity and Truth  eBooks & eLearning

Posted by interes at June 2, 2019
Infinity and Truth

Infinity and Truth (Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore) by Chitat Chong and Qi Feng
English | 2014 | ISBN: 9814571032 | 244 pages | PDF | 1,8 MB

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples  eBooks & eLearning

Posted by Free butterfly at March 5, 2024
Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples by Faming Liang, Chuanhai Liu, Raymond Carroll
English | August 23, 2010 | ISBN: 0470748265 | 384 pages | EPUB | 20 Mb

Bayesian Computation with R (Repost)  eBooks & eLearning

Posted by AvaxGenius at March 11, 2022
Bayesian Computation with R (Repost)

Bayesian Computation with R by Jim Albert
English | PDF | 2009 | 304 Pages | ISBN : 0387922970 | 3.2 MB

There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry.