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Topics in Optimal Design
  • Language: en
  • Pages: 173

Topics in Optimal Design

This book covers a wide range of topics in both discrete and continuous optimal designs. The topics discussed include designs for regression models, covariates models, models with trend effects, and models with competition effects. The prerequisites are a basic course in the design and analysis of experiments and some familiarity with the concepts of optimality criteria.

Statistical Inference, Econometric Analysis and Matrix Algebra
  • Language: en
  • Pages: 438

Statistical Inference, Econometric Analysis and Matrix Algebra

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 obt...

Weighted Empirical Processes in Dynamic Nonlinear Models
  • Language: en
  • Pages: 444

Weighted Empirical Processes in Dynamic Nonlinear Models

This book presents a unified approach for obtaining the limiting distributions of minimum distance. It discusses classes of goodness-of-t tests for fitting an error distribution in some of these models and/or fitting a regression-autoregressive function without assuming the knowledge of the error distribution. The main tool is the asymptotic equi-continuity of certain basic weighted residual empirical processes in the uniform and L2 metrics.

Statistical Paradigms
  • Language: en
  • Pages: 308

Statistical Paradigms

This volume consists of a collection of research articles on classical and emerging Statistical Paradigms — parametric, non-parametric and semi-parametric, frequentist and Bayesian — encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. For advances in theory, the topics include: Bayesian Inference, Directional Data Analysis, Distribution Theory, Econometrics and Multiple Testing Procedures. The areas in emerging applications include: Bioinformatics, Factorial Experiments and Linear Models, Hotspot Geoinformatics and Reliability. Contents:Reviews:Weak Paradoxes and Paradigms (Jayanta K Ghosh)Nonparametrics in Modern Interdisciplinary Res...

Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
  • Language: en
  • Pages: 418

Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series

Time series play a crucial role in modern economies at all levels of activity and are used by decision makers to plan for a better future. Before publication time series are subject to statistical adjustments and this is the first statistical book to systematically deal with the methods most often applied for such adjustments. Regression-based models are emphasized because of their clarity, ease of application, and superior results. Each topic is illustrated with real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed a real data example is followed throughout the book.

Weak Dependence: With Examples and Applications
  • Language: en
  • Pages: 326

Weak Dependence: With Examples and Applications

This book develops Doukhan/Louhichi's 1999 idea to measure asymptotic independence of a random process. The authors, who helped develop this theory, propose examples of models fitting such conditions: stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Applications are still needed to develop a method of analysis for nonlinear times series, and this book provides a strong basis for additional studies.

Multivariate Dispersion, Central Regions, and Depth
  • Language: en
  • Pages: 303

Multivariate Dispersion, Central Regions, and Depth

This book has many applications to stochastic comparison problems in economics and other fields. It covers theory of lift zonoids and demonstrates its usefulness in multivariate analysis, an informal introduction to basic ideas, and a comprehensive investigation into the theory, as well as various applications of the lift zonoid approach and may be separately studied. Readers are assumed to have a firm grounding in probability at the graduate level.

Space, Structure and Randomness
  • Language: en
  • Pages: 402

Space, Structure and Randomness

Space, structure, and randomness: these are the three key concepts underlying Georges Matheron’s scientific work. He first encountered them at the beginning of his career when working as a mining engineer, and then they resurfaced in fields ranging from meteorology to microscopy. What could these radically different types of applications possibly have in common? First, in each one only a single realisation of the phenomenon is available for study, but its features repeat themselves in space; second, the sampling pattern is rarely regular, and finally there are problems of change of scale. This volume is divided in three sections on random sets, geostatistics and mathematical morphology. Th...

Innovations in Multivariate Statistical Analysis
  • Language: en
  • Pages: 302

Innovations in Multivariate Statistical Analysis

The three decades which have followed the publication of Heinz Neudecker's seminal paper `Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products' in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines. Amongst these are the disciplines to which Neudecker has contributed directly - namely econometrics, economics, psychometrics and multivariate analysis. This book aims to illustrate how powerful the tools of matrix analysis have become as weapons in the statistician's armoury. The majority of its chapters are concerned primarily with theoretical innovations, but all of th...

Computation of Multivariate Normal and t Probabilities
  • Language: en
  • Pages: 130

Computation of Multivariate Normal and t Probabilities

Multivariate normal and t probabilities are needed for statistical inference in many applications. Modern statistical computation packages provide functions for the computation of these probabilities for problems with one or two variables. This book describes recently developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. The book discusses methods for specialized problems as well as methods for general problems. The book includes examples that illustrate the probability computations for a variety of applications.