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Stochastic finance and financial engineering have been rapidly expanding fields of science over the past four decades, mainly due to the success of sophisticated quantitative methodologies in helping professionals manage financial risks. In recent ye…
Stochastic finance and financial engineering have been rapidly expanding fields of science over the past four decades, mainly due to the success of sophisticated quantitative methodologies in helping professionals manage financial risks. In recent ye…
Praise for the First Edition «. . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises.»—Zentralblatt MATH «. . . carefully structured with many detailed worked ex…
Praise for the First Edition «. . . outstandingly appealing with regard to its style, contents, considerations of requirements of practice, choice of examples, and exercises.»—Zentralblatt MATH «. . . carefully structured with many detailed worked ex…
A complete and comprehensive collaboration providing insight on future approaches to telephone survey methodology Over the past fifteen years, advances in technology have transformed the field of survey methodology, from how interviews are conducted …
A complete and comprehensive collaboration providing insight on future approaches to telephone survey methodology Over the past fifteen years, advances in technology have transformed the field of survey methodology, from how interviews are conducted …
Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration, interpolation and density estimation. Includes a copious amount of problems an…
Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration, interpolation and density estimation. Includes a copious amount of problems an…
Praise for the First Edition «Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners.» —Computing Reviews This ne…
Praise for the First Edition «Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners.» —Computing Reviews This ne…
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well w…
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well w…
Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numer…
Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences. They are also ideal for civil engineering applications, given the numer…
A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. «This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitio…
A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews. «This book is a reflection of the vast experience and knowledge of the author. It is a useful reference for students and practitio…
Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and fir…
Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathematical statistics for upper-undergraduates and fir…
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well w…
A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well w…
[b]A comprehensive yet accessible introduction to the conceptual tools used to explore real-world environmental problems [/b]
[i]Environment and Society: A Critical Introduction, Third Edition[/i] demonstrates how theoretical approaches such as envir…
[b]A comprehensive yet accessible introduction to the conceptual tools used to explore real-world environmental problems [/b]
[i]Environment and Society: A Critical Introduction, Third Edition[/i] demonstrates how theoretical approaches such as envir…
Praise for the First Edition «. . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists.» —International Statistical Institute A new edition of the definitive guide to classical and modern methods of biosta…
Praise for the First Edition «. . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists.» —International Statistical Institute A new edition of the definitive guide to classical and modern methods of biosta…
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…
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…
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…
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…
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…
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…
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 …
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. …
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. …