It was written on another occasion* that "e;It is apparent that the scientific culture, if one means production of scientific papers, is growing exponentially, and chaotically, in almost every field of investigation"e;.
As computers proliferate and as the field of computer graphics matures, it has become increasingly important for computer scientists to understand how users perceive and interpret computer graphics.
This comprehensive book, rich with applications, offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods.
Comparative effectiveness research (CER) is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care (IOM 2009).
This book provides straightforward conceptual explanations of statistical methods for the life sciences, specially designed for students lacking a strong mathematical background.
This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago.
A core task in statistical analysis, especially in the era of Big Data, is the fitting of flexible, high-dimensional, and non-linear models to noisy data in order to capture meaningful patterns.
Emerging technologies generate data sets of increased size and complexity that require new or updated statistical inferential methods and scalable, reproducible software.
Incorporating a collection of recent results, Polya Urn Models deals with discrete probability through the modern and evolving urn theory and its numerous applications.
A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before.
Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers.
Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.
Helping you become a creative, logical thinker and skillful "e;simulator,"e; Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization.
Shortlisted for the William Hill Sports Book of the Year Award 2022Football has always measured success by what you win, but only in the last twenty years have clubs started to think about how you win.
Spatial predictive modeling (SPM) is an emerging discipline in applied sciences, playing a key role in the generation of spatial predictions in various disciplines.
This book offers a design research methodology intended to improve the quality of design research- its academic credibility, industrial significance and societal contribution by enabling more thorough, efficient and effective procedures.
This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning.
Michael Harrison returns to an important topic in stochastic process theory, and illustrates its many influential applications in business and economics.
Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on optimization techniques used to solve problems with adaptive, dynamic, and stochastic features.
This book provides detailed empirical analysis of countries in Asia to examine various dynamic models that incorporate the impact of technology and innovations on the industry evolution and overall economic growth.
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.
Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk s Probability and Finance, published in 2001, showed that perfect-information games can be used to define mathematical probability.
This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis.
The aim of this book is to show that the probabilistic formalisms of classical statistical mechanics and quantum mechanics can be unified on the basis of a general contextual probabilistic model.
