This study is divided into two seemingly disjoint parts -- one containing EMPIRICAL (Bayesian and Non-Bayesian) approach and the second containing INFORMATION-THEORETICAL techniques in problems of statistical estimation and tests of hypotheses. But in the end, both approaches have been brought together for solving ENCODING problems of COMMUNICATION THEORY to unify the whole dissertation
This article is envisioned to form a base uponwhich a full-blown exhaustive discussion ofhypothesis-...
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts ...
This book is unique in that it covers the philosophy of model-based data analysis and an omnibus str...
Adopting a broad view of statistical inference, the text concentrates on what various techniques do,...
Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this b...
For many years, traditional Bayesian (TB) and information theoretic (IT) procedures for learning fro...
This group is interested in a variety of problems in statistical communication theory. Current resea...
The presented volume addresses some vital problems in contemporary statistical reasoning [...
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybe...
Reviews probability and introduces statistical inference. Point and interval estimation. The maximum...
This chapter reviews research on the learning of statistical inference, focusing in particular on re...
Statistical inference is about using statistical data (x) to formulate an opinion about something th...
This book addresses contemporary statistical inference issues when no or minimal assumptions on the ...
We review two foundations of statistical inference, the theory of likelihood and the Bayesian paradi...
Often scientific information on various data generating processes are presented in the from of numer...
This article is envisioned to form a base uponwhich a full-blown exhaustive discussion ofhypothesis-...
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts ...
This book is unique in that it covers the philosophy of model-based data analysis and an omnibus str...
Adopting a broad view of statistical inference, the text concentrates on what various techniques do,...
Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this b...
For many years, traditional Bayesian (TB) and information theoretic (IT) procedures for learning fro...
This group is interested in a variety of problems in statistical communication theory. Current resea...
The presented volume addresses some vital problems in contemporary statistical reasoning [...
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybe...
Reviews probability and introduces statistical inference. Point and interval estimation. The maximum...
This chapter reviews research on the learning of statistical inference, focusing in particular on re...
Statistical inference is about using statistical data (x) to formulate an opinion about something th...
This book addresses contemporary statistical inference issues when no or minimal assumptions on the ...
We review two foundations of statistical inference, the theory of likelihood and the Bayesian paradi...
Often scientific information on various data generating processes are presented in the from of numer...
This article is envisioned to form a base uponwhich a full-blown exhaustive discussion ofhypothesis-...
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts ...
This book is unique in that it covers the philosophy of model-based data analysis and an omnibus str...