Our website is made possible by displaying online advertisements to our visitors.
Please consider supporting us by disabling your ad blocker.

Download links will be available after you disable the ad blocker and reload the page.
Showing: 1-10 results of 6505

This book offers solutions to such topical problems as developing mathematical models and descriptions of typical distortions in applied forecasting problems; evaluating robustness for traditional forecasting procedures under distortionism and more.

This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than... more...

This volume contains 15 articles based on invited talks given at an AMS Special Session on Stochastic Inequalities and Their Applications held at Georgia Institute of Technology, Atlanta, USA. The session drew international experts who exchanged ideas and presented state-of-the-art results and techniques in the field. Together, the articles in the book are intended to give a comprehensive picture of this area of mathematical probability and statistics.

This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book’s highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational... more...

In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more... more...


An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data.Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the... more...

This book presents the fundamentals of modern tensor calculus for students in engineering and applied physics, emphasizing those aspects that are crucial for applying tensor calculus safely in Euclidian space and for grasping the very essence of the smooth manifold concept. After introducing the subject, it provides a brief exposition on point set topology to familiarize readers with the subject, especially with those topics required... more...

We can best understand many fundamental processes in analysis by studying and comparing the summability of series in various modes of convergence. This text provides the reader with basic knowledge of real and functional analysis, with an account of p-summing and related operators. The account is panoramic, with detailed expositions of the core results and highly relevant applications to harmonic analysis, probability and measure theory, and operator... more...

The purpose of this book, written by world-renowned authorities in this field, is to guide the reader in learning about new developments in approximation theory that have come up over the last 20 years. The emphasis is on multivariate approximation theory. Most of the topics appear for the first time here in a systematic textbook and many are still current areas of research. The authors cover positive definite functions, radial basis interpolation,... more...

A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these... more...