This book provides sample exercises, techniques, and solutions to employ mathematical modeling to solve problems in Operations Research and Business Analytics.
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies.
While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners.
Expert Guidance on the Math Needed for 3D Game ProgrammingDeveloped from the authors' popular Game Developers Conference (GDC) tutorial, Essential Mathematics for Games and Interactive Applications, Third Edition illustrates the importance of mathematics in 3D programming.
This book presents the theory of rational decisions involving the selection of stopping times in observed discrete-time stochastic processes, both by single and multiple decision-makers.
Understand Up-to-Date Statistical Techniques for Financial and Actuarial ApplicationsSince the first edition was published, statistical techniques, such as reliability measurement, simulation, regression, and Markov chain modeling, have become more prominent in the financial and actuarial industries.
Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples.
Competitive Innovation and Improvement: Statistical Design and Control explains how to combine two widely known statistical methods'statistical design and statistical control in a manner that can solve any business, government, or research problem quickly with sustained results.
Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures.
This book describes some approaches for developing the numerical models to efficiently predict the formation of extreme waves which can pose a threat to the safety of marine structures.
This book describes some approaches for developing the numerical models to efficiently predict the formation of extreme waves which can pose a threat to the safety of marine structures.
Actuarial loss models are statistical models used by insurance companies to estimate the frequency and severity of future losses, set premiums, and reserve funds to cover potential claims.
As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences.
Interpreting poll data as a prediction of election outcomes is a practice as old as the field, rooted in a fundamental misunderstanding of what poll data means.
Designed for a one-semester course, Applied Statistics for Business and Economics offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world.
This book provides a concise overview of a variety of techniques for analyzing statistical, scientific, and financial data, using MATLAB(R) to integrate several approaches to data analysis and statistics.
Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility?
This book offers a comprehensive overview of using artificial intelligence and quantitative approaches in many phases of flight safety management, from proactive assessment of potential risks of flights before taking-off to automatic analysis of occurred flight events, for commercial airlines.
This book provides a practical guide on annotating emotions in natural language data and showcases how these annotations can improve Natural Language Processing (NLP) and Natural Language Understanding (NLU) models and applications.
This book provides a practical guide on annotating emotions in natural language data and showcases how these annotations can improve Natural Language Processing (NLP) and Natural Language Understanding (NLU) models and applications.
Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models.
Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide.
Interpreting poll data as a prediction of election outcomes is a practice as old as the field, rooted in a fundamental misunderstanding of what poll data means.
This book presents the proceedings of the international conference Particle Systems and Partial Differential Equations X, which was held at the University of Minho, Braga, Portugal, from 2022.
This book offers a comprehensive overview of using artificial intelligence and quantitative approaches in many phases of flight safety management, from proactive assessment of potential risks of flights before taking-off to automatic analysis of occurred flight events, for commercial airlines.
This book presents the proceedings of the international conference Particle Systems and Partial Differential Equations X, which was held at the University of Minho, Braga, Portugal, from 2022.
Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area.
