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...

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and...

Introduction to Probability and Stochastic Processes with Applications presents a clear, easy-to-understand treatment of probability and stochastic processes, providing readers with a solid foundation they can build upon throughout their...

The use of open-source software (OSS)--readable software source code that can be copied, modified, and distributed freely--has expanded dramatically in recent years. The number of OSS projects hosted on SourceForge.net (the largest hosting Web site for OSS), for example, grew from just over 100,000 in 2006 to more than 250,000 at the...

• Get to grips with the application of Machine Learning methods using an extensive set of R packages
• Understand the benefits and potential pitfalls of using machine learning methods
...

Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions. There are two additional chapters, and all the original chapters of this classic text have been updated. Resources in this book will be valuable for researchers,...

• Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data
• Choose the right statistical technique to analyze different types of data and build efficient...