Mean Field Simulation for Monte Carlo Integration (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Image 1

£47.83

CRC Press Mean Field Simulation for Monte Carlo Integration (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Name: Mean Field Simulation for Monte Carlo Integration (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Brand: CRC Press
Price: 47.83 GBP
Availability: InStock

Probability & Statistics

This is the usual price. Wait for it to drop, or tell us your number.

£48 today · usual range £0–£0 · best ever £42

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 602 days • 602 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 602 days • 5 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £47-49 (233 days, 38.7%)

Price range: £42 - £50

Price levels: 5 price ranges over 602 days

Description

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 nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods. Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology. This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.

Product Specifications

Brand: CRC Press
Format: Paperback
ASIN: 1138198730
Category: Books > Subjects > Science, Nature & Maths > Mathematics > Probability & Statistics
Domain: Amazon UK
Release Date: 31 October 2016
Listed Since: 30 August 2016

Barcode

No barcode data available

CRC Press Mean Field Simulation for Monte Carlo Integration (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Mean Field Simulation for Monte Carlo Integration (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Springer An Introduction to Sequential Monte Carlo - Particle Filters

Markov chain monte carlo simulations and their statistical analysis: with web-based fortran code

Measure-Valued Branching Markov Processes: 103 (Probability Theory and Stochastic Modelling, 103)

An Introduction to Stochastic Modeling

Stochastic Simulation and Monte Carlo Methods: Mathematical Foundations of Stochastic Simulation: 68 (Stochastic Modelling and Applied Probability, 68)

Complex Stochastic Systems: 87 (CRC Monographs on Statistics & Applied Probability (Hardcover))

Genealogies Of Interacting Particle Systems: 38 (Lecture Notes Series, Institute for Mathematical Sciences, National University of Singapore)

Stochastic Analysis and Related Topics: In Honour of Ali Süleyman Üstünel, Paris, June 2010: 22 (Springer Proceedings in Mathematics & Statistics, 22)

Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear

Introduction to Stochastic Integration (Modern Birkhäuser Classics)

Introducing Monte Carlo Methods with R (Use R!)

Springer Monte Carlo and Quasi-Monte Carlo Methods 2012 Book

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems: Second Edition: 19 (Series on Concrete & Applicable Mathematics)

Elements of Applied Stochastic Processes: 378 (Wiley Series in Probability and Statistics)

Advanced Markov Chain Monte Carlo Methods: Learning from Past Samples (Wiley Series in Computational Statistics)

Stochastic Analysis and Diffusion Processes (Oxford Graduate Texts in Mathematics): 24

Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

Stationary Processes and Discrete Parameter Markov Processes: 293 (Graduate Texts in Mathematics, 293)

Measure Theory, Probability, and Stochastic Processes: 295 (Graduate Texts in Mathematics, 295)

Springer Stochastic Models, Statistics and Their Applications

Introduction to the Theory of Random Processes (Graduate Studies in Mathematics)

Diffusion Models & Score-Based Generative Modeling: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)

Probability: Theory and Examples: 49 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 49)