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A complete introduction to the multidisciplinary applications of mathematical methods In order to work with varying levels of engineering and physics research, it is important to have a firm understanding of key mathematical concepts such as advanced…

Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mi…

The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with …

* Considers neoclassical models in light of results that can go wrong with them to bring about better models. * Questions the assumption that markets clear quickly. * Offers a timely examination of the LTCM collapse. * Written by a group of well-resp…

Distance determination is an essential technique in astronomy, and is briefly covered in most textbooks on astrophysics and cosmology. It is rarely covered as a coherent topic in its own right. When it is discussed the approach is frequently very dry…

Written by selected astronomers at the forefront of their fields, this timely and novel book compiles the latest results from research on white dwarf stars, complementing existing literature by focusing on fascinating new developments in our understa…

This collection of fundamental formulae, up-to-date references and definitions in plasma physics is vital to anyone with an interest in plasmas or ionized gases, whether in physics, astronomy or engineering. Both theorists and experimentalists will f…

Simplifies the treatment of statistical inference focusing on how to specify and interpret models in the context of testing causal theories. Simple bivariate regression, multiple regression, multiple classification analysis, path analysis, logit regr…

Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discus…

Incorporates the many tools needed for modeling and pricing in finance and insurance Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathema…

This newly updated edition of the benchmark guide to computer-assisted clinical trials provides a comprehensive primer for prospective managers. It covers every critical issue of the design and conduct of clinical trials, including study design, orga…

One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls tog…

This new work by Wilfred Kaplan, the distinguished author of influential mathematics and engineering texts, is destined to become a classic. Timely, concise, and content-driven, it provides an intermediate-level treatment of maxima, minima, and optim…

Applies the well-developed tools of the theory of weak convergence of probability measures to large deviation analysis–a consistent new approach The theory of large deviations, one of the most dynamic topics in probability today, studies rare events …

A Probabilistic Analysis of the Sacco and Vanzetti Evidence is a Bayesian analysis of the trial and post-trial evidence in the Sacco and Vanzetti case, based on subjectively determined probabilities and assumed relationships among evidential events. …

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of very large datasets, and symbolic data analysis techn…

Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such di…

Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Uncertainty analysis aims to quantify the overall …

Assessing Weight-of-Evidence for DNA Profiles is an excellent introductory text to the use of statistical analysis for assessing DNA evidence. It offers practical guidance to forensic scientists with little dependence on mathematical ability as the b…

In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nucl…