Books by Randall L. Eubank

This text provides a self-contained, "no frills," mathematically rigorous derivation from first principles of all basic Kalman filter recursions. This approach relies on a pared-down version of more general state-space models found most often in the literature. Such simplification saves notational complexity without sacrificing conceptual understanding. The rigor found in the book ensures a fundamental understanding of how the Kalman filter actually works, which builds confidence for those employing the filter in their research and writing code to implement it in practice. The author provides implementations of the Kalman filter in Java available for download from his Web site.

Parallel processing can be ideally suited for the solving of more complex problems in statistical computing. This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It requires a working knowledge of both the basic concepts in statistics and experience in programming.

The Kalman filter is an important tool for estimating the variables in a system in the presence of noise. This title offers a fundamental understanding of how the Kalman filter actually works, which builds confidence for those employing the filter in their research and writing code to implement it in practice.