Computational Probability Computational Probability
International Series in Operations Research & Management Science

Computational Probability

Algorithms and Applications in the Mathematical Sciences

John H. Drew 및 다른 저자
    • US$109.99
    • US$109.99

출판사 설명

This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. 
Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.

장르
비즈니스 및 개인 금융
출시일
2016년
12월 15일
언어
EN
영어
길이
347
페이지
출판사
Springer International Publishing
판매자
Springer Nature B.V.
크기
5.7
MB
Elements of Simulation Elements of Simulation
2018년
Random-Like Multiple Objective Decision Making Random-Like Multiple Objective Decision Making
2011년
Data Science for Business and Decision Making Data Science for Business and Decision Making
2019년
Computer Intensive Methods in Statistics Computer Intensive Methods in Statistics
2019년
Uncertainty Quantification and Stochastic Modelling with EXCEL Uncertainty Quantification and Stochastic Modelling with EXCEL
2022년
Time Series Analysis and Forecasting Time Series Analysis and Forecasting
2018년
Public Systems Modeling Public Systems Modeling
2022년
Business Analytics Business Analytics
2012년
Hidden Markov Models in Finance Hidden Markov Models in Finance
2007년
Linear Programming Linear Programming
2020년
Measuring Time Measuring Time
2009년
Game Theory and Business Applications Game Theory and Business Applications
2013년