Nonparametric Statistics with Applications to Science and Engineering Paul H. Kvam Brani Vidakovic Contents 1 Introduction 2 Probability Basics 3 Statistics Basics 4 Bayesian Statistics 5 Order Statistics 6 Goodness of Fit 7 Rank Tests 8 Designed Ex
this is a book about the L1 convergence of density estimates that are based on a smple of rd-valued in independent identically distributed random vectors
This book is the fruit of recent advances concerning both nonparametric statistical modelling and functional variables,presents in a original way new nonparametric statistical methods for functional data analysis.
This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is als
This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate co
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic
The theory and methods of smoothing have been developed mainly in the last ten years. The intensive interest in smoothing over this last decade had two reasons: statisticians realized that pure parametric thinking in curve estimations often does not
