Research papers

Multilevel Statistical Models

Harvey Goldstein

Comprehensive account of multilevel modelling theory and practice

Statistical Learning Theory

Yuhai Wu, Vladimir Vapnik

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.

Empirical Model Building and Response Surfaces

Anne E. Freeny, George E. P. Box, Norman R. Draper

Introduction to Response Surface Methodology. The Use of Graduating Functions. Least Squares for Response Surface Work. Factorial Designs at Two Levels. Blocking and Fractionating 2 k Factorial Designs. The Use of Steepest Ascent to Achieve System Improvement. Fitting Second--Order Models. Adequacy of Estimation and the Use of Transformation. Exploration of Maxima and Ridge Systems with Second--Order Response Surfaces. Occurrence and Elucidation of Ridge Systems, I. Occurrence and Elucidation of Ridge Systems, II. Links Between Emprirical and Theoretical Models. Design Aspects of Variance, Bias, and Lack of Fit. Variance----Optimal Designs. Practical Choice of a Response Surface Design. Subject Index. Index.

Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables

D. B. Owen, Milton Abramowitz, Irene A. Stegun