The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics.
The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.
Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. Special attention is paid to the derivation of prior distributions in each case and...
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models ...
Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns of risk management are addressed by the study of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Principal...
Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial proble...
This book presents numerous exercises with solutions to help the reader better understand different aspects of modern statistics. It features applications with R and Matlab code that show how to practically use the methods.
This book presents numerous exercises with solutions to help the reader better understand different aspects of modern statistics. It features applicat...
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering.
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financi...
Probability for Statisticians is intended as a text for a one year graduate course aimed especially at students in statistics. The choice of examples illustrates this intention clearly. The material to be presented in the classroom constitutes a bit more than half the text, and the choices the author makes at the University of Washington in Seattle are spelled out. The rest of the text provides background, offers different routes that could be pursued in the classroom, ad offers additional material that is appropriate for self-study. Of particular interest is a presentation of the major...
Probability for Statisticians is intended as a text for a one year graduate course aimed especially at students in statistics. The choice of examples ...
This book offers a step-by-step guide to the experimental planning process and the ensuing analysis of normally distributed data, emphasizing the practical considerations governing the design of an experiment. Data sets are taken from real experiments and sample SAS programs are included with each chapter. Experimental design is an essential part of investigation and discovery in science; this book will serve as a modern and comprehensive reference to the subject.
This book offers a step-by-step guide to the experimental planning process and the ensuing analysis of normally distributed data, emphasizing the prac...
This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines.
The textbook contains enough material for a...
This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject ...
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.
The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level...
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequ...
Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course.� The ease of computation with advanced calculators and statistical software, both of which factor into this text, allows important techniques to be introduced earlier in the study of statistics.
Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course.� The...
