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

ISBN-13: 9783790821208 / Angielski / Twarda / 2008 / 434 str.

Walter Kramer; Bernhard Schipp

Opis

This Festschrift is dedicated to Gotz Trenkler on the occasion of his 65th birthday. As can be seen from the long list of contributions, Gotz 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). Gotz 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.

Spis treści

Nonparametric Inference.- Adaptive Tests for the c-Sample Location Problem.- On Nonparametric Tests for Trend Detection in Seasonal Time Series.- Nonparametric Trend Tests for Right-Censored Survival Times.- Penalty Specialists Among Goalkeepers: A Nonparametric Bayesian Analysis of 44 Years of German Bundesliga.- Permutation Tests for Validating Computer Experiments.- Parametric Inference.- Exact and Generalized Confidence Intervals in the Common Mean Problem.- Locally Optimal Tests of Independence for Archimedean Copula Families.- Design of Experiments and Analysis of Variance.- Optimal Designs for Treatment-Control Comparisons in Microarray Experiments.- Improving Henderson's Method 3 Approach when Estimating Variance Components in a Two-way Mixed Linear Model.- Implications of Dimensionality on Measurement Reliability.- Linear Models and Applied Econometrics.- Robust Moment Based Estimation and Inference: The Generalized Cressie-Read Estimator.- More on the F-test under Nonspherical Disturbances.- Optimal Estimation in a Linear Regression Model using Incomplete Prior Information.- Minimum Description Length Model Selection in Gaussian Regression under Data Constraints.- Self-exciting Extreme Value Models for Stock Market Crashes.- Consumption and Income: A Spectral Analysis.- Stochastic Processes.- Improved Estimation Strategy in Multi-Factor Vasicek Model.- Bounds on Expected Coupling Times in a Markov Chain.- Multiple Self-decomposable Laws on Vector Spaces and on Groups: The Existence of Background Driving Processes.- Matrix Algebra and Matrix Computations.- Further Results on Samuelson's Inequality.- Revisitation of Generalized and Hypergeneralized Projectors.- On Singular Periodic Matrices.- Testing Numerical Methods Solving the Linear Least Squares Problem.- On the Computation of the Moore—Penrose Inverse of Matrices with Symbolic Elements.- On Permutations of Matrix Products.- Special Topics.- Some Comments on Fisher's ? Index of Diversity and on the Kazwini Cosmography.- Ultimatum Games and Fuzzy Information.- Are Bernstein's Examples on Independent Events Paradoxical?.- A Classroom Example to Demonstrate Statistical Concepts.

O autorze

Walter Krämer, geb. 1948, ist Professor für Wirtschafts- und Sozialstatistik an der Universität Dortmund.

Blurb

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.