Statistical Inference, Econometric Analysis and Matrix Algebra : Festschrift in Honour of Götz Trenkler

Schipp, Bernhard (EDT); Krämer, Walter (EDT)

ISBN 10: 3790821209 / ISBN 13: 9783790821208

Published by Physica, 2008

About this Item

Seller Inventory # 5844773-n

Bibliographic Details

• Title: Statistical Inference, Econometric Analysis and Matrix Algebra : Festschrift in Honour of Götz Trenkler
• Publisher: Physica
• Publication Date: 2008
• Language: English
• ISBN 10: 3790821209
• ISBN 13: 9783790821208
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This Festschrift is dedicated to Götz Trenkler on the occasion of his 65th birthday. As can be seen from the long list of contributions, Götz has had and still has an enormous range of interests, and colleagues to share these interests with. He is a leading expert in linear models with a particular focus on matrix algebra in its relation to statistics. He has published in almost all major statistics and matrix theory journals. His research activities also include other areas (like nonparametrics, statistics and sports, combination of forecasts and magic squares, just to mention afew). Götz Trenkler was born in Dresden in 1943. After his school years in East G- many and West-Berlin, he obtained a Diploma in Mathematics from Free University of Berlin (1970), where he also discovered his interest in Mathematical Statistics. In 1973, he completed his Ph.D. with a thesis titled: On a distance-generating fu- tion of probability measures. He then moved on to the University of Hannover to become Lecturer and to write a habilitation-thesis (submitted 1979) on alternatives to the Ordinary Least Squares estimator in the Linear Regression Model, a topic that would become his predominant ?eld of research in the years to come.

From the Back Cover

This unique collection of essays extends the frontiers of knowledge in econometrics as well as classical fields of statistical inference. Among others, it presents advances in stochastic processes, in the design of experiments and in the analysis of variance. Moreover, several papers on modern matrix algebra provide insights into up-to-date approaches in quantitative methods and show once more how useful a tool this is in modern mathematics-based data analysis. The book will therefore be of key interest to anybody working as a practitioner in statistical data analysis or as a researcher in modern statistical science.