In recent years, Fourier transform methods have emerged as one of the major methodologies for the evaluation of derivative contracts, largely due to the need to strike a balance between the extension of existing pricing models beyond the traditional Black-Scholes setting and a need to evaluate prices consistently with the market...
The teaching of appliedprobability needs a fresh approach. The fieldof applied probability has changedprofound ly in the past twenty years andyet the textbooks in use today do not fully reflect the changes. The development of computational methods has greatly contributed to a better understanding of the theory. It is my conviction that theory is...
This book and companion DVD provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods described in standard texts. The emphasis throughout is on techniques having a broad range of real-world applications in measurement science. Mainstream methods of data modeling and analysis...
Probability theory and fuzzy logic are the principal components of an array of methodologies
for dealing with problems in which uncertainty and imprecision play important roles.
In relation to probability theory, fuzzy logic is a new kid on the block. As such, it has been
and continues to be, though to a lesser degree, an object of...
Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples.
Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian...
This book gives a systematic treatment of singularly perturbed systems that naturally arise in control and optimization, queueing networks, manufacturing systems, and financial engineering. It presents results on asymptotic expansions of solutions of Komogorov forward and backward equations, properties of functional occupation measures,...
This volume contains the proceedings of the AMS Special Sessions on Algorithmic Probability and Combinatories held at DePaul University on October 5-6, 2007 and at the University of British Columbia on October 4-5, 2008.
This volume collects cutting-edge research and expository on algorithmic probability and combinatories. It...
This book is intended to have three roles and to serve three associated audiences: an
introductory text on Bayesian inference star ting from first principles, a graduate text on
effective current approaches to Bayesian modeling and computation in statistics and
related fields, and a handbook of Bayesian meth ods in applied...
Modern astronomical research is beset with a vast range of statistical challenges, ranging from reducing data from megadatasets to characterizing an amazing variety of variable celestial objects or testing astrophysical theory. Linking astronomy to the world of modern statistics, this volume is a unique resource, introducing astronomers to...
Many probability books are written by mathematicians and have the built-in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead,...
This text explains the tools of statistics and how to apply them effectively to improve processes and profitability in an organization, and also delineates the importance of collecting, analyzing, and interpreting data.
Researchers and professionals in all walks of life need to use the many tools offered by the statistical world, but...
A long time ago, when younger and rasher mathematicians, we both momentarily harboured the ambition that one day, older and wiser, we might write a multivolume treatise titled “On the Mathematical Foundations of Numerical Analysis”. And then it dawned that such a creation already exists: it is called ‘a mathematics library’....
