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Statistical Inference Econometric Analysis And Matrix Algebra Festschrift In Honour Of Gtz Trenkler 2009th Edition Bernhard Schipp

  • SKU: BELL-33292290
Statistical Inference Econometric Analysis And Matrix Algebra Festschrift In Honour Of Gtz Trenkler 2009th Edition Bernhard Schipp
$ 31.00 $ 45.00 (-31%)

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Statistical Inference Econometric Analysis And Matrix Algebra Festschrift In Honour Of Gtz Trenkler 2009th Edition Bernhard Schipp instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 16.52 MB
Pages: 450
Author: Bernhard Schipp, Walter Krämer
ISBN: 9783790821208, 9783790821215, 3790821209, 3790821217
Language: English
Year: 2009
Edition: 2009

Product desciption

Statistical Inference Econometric Analysis And Matrix Algebra Festschrift In Honour Of Gtz Trenkler 2009th Edition Bernhard Schipp by Bernhard Schipp, Walter Krämer 9783790821208, 9783790821215, 3790821209, 3790821217 instant download after payment.

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.

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