Topics in Statistical Information Theory (Lecture Notes in Statistics) by John C. Keegel
English | July 28, 1987 | ISBN: 0387965122 | 169 Pages | PDF | 4 MB
English | July 28, 1987 | ISBN: 0387965122 | 169 Pages | PDF | 4 MB
The relevance of information theory to statistical theory and its applications to stochastic processes is a unifying influence in these TOPICS. The integral representation of discrimination information is presented in these TOPICS reviewing various approaches used in the literature, and is also developed herein using intrinsically information-theoretic methods. Log likelihood ratios associated with various stochastic processes are computed by an application of minimum discrimination information estimates. Linear discriminant functionals are used in the information-theoretic analysis of a variety of stochastic processes. Sections are numbered serially within each chapter, with a decimal notation for subsections.