Each chapter closes with references for further reading which keeps the book the size of a handy handbook containing an overview of the most important information on the topic while offering further references [for] the interested reader. The book is well structured and easy to read. The book is well written for any researcher with any background.
It is an excellent up-to-date reference book for beginning researchers and practitioners interested in using ROC curve. They explain various aspects of ROC analysis very simply, using only the necessary mathematics. Hence, the reading is easy, interesting, and bound to stimulate curiosity for further exploration of the literature. I therefore recommend it to all researchers and practitioners who work with multivariate data, especially those who are concerned with classification problems.
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For both formats the functionality available will depend on how you access the ebook via Bookshelf Online in your browser or via the Bookshelf app on your PC or mobile device. Stay on CRCPress. Preview this Book. Krzanowski, David J. Add to Wish List. Close Preview. Toggle navigation Additional Book Information. By Adelchi Azzalini. The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods.
This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical…. Edited by D. Cox , D. Hinkley , O. The analysis prediction and interpolation of economic and other time series has a long history and many applications.
Minimum distance estimation of the binormal ROC curve
Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints…. By Jianqing Fan , Irene Gijbels. Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. Gower , David J.
Biplots are the multivariate analog of scatter plots, approximating the multivariate distribution of a sample in a few dimensions to produce a graphic display. In addition, they superimpose representations of the variables on this display so that the relationships between the sample and the…. John , E.
Cyclic and Computer Generated Designs is a much-expanded and updated version of the well-received monograph, Cyclic Designs. The book is primarily concerned with the construction and analysis of designs with a number of different blocking structures, such as revolvable designs, row-column designs,…. By Marie Davidian , David. Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data.
Nonlinear Models for Repeated Measurement Data provides the first unified…. Distribution-free statistical methods enable users to make statistical inferences with minimum assumptions about the population in question. They are widely used, especially in the areas of medical and psychological research. This new edition is aimed at senior undergraduate and graduate level. Wand , M.
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Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function. This book provides uninitiated readers with a feeling for the principles, applications, and…. By Jan Beran. Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence.
Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations,…. By Bradley Efron , R. Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics.
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The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as….
Cox , O. This book provides a systematic account of some developments in asymptotic parametric inference from a likelihood-based perspective. It focuses on first-order asymptotic theory, and discusses the need for higher-order theory.
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By Michael E. Tarter , Michael D. Model-Free Curve Estimation details the Fourier series approach to density estimation and explores how model-free technology can be expanded to deal with other statistical curves, such as survival and regression functions. It also describes the implementation of some curves for exploratory data…. Daykin , T. Pentikainen , Martti Pesonen. This classic textbook covers all aspects of risk theory in a practical way. It builds on from the late R. Beard's extremely popular book Risk Theory, but features more emphasis on simulation and modeling and on the use of risk theory as a practical tool.
Practical Risk Theory is a textbook for…. By Kai-Tai Fang , Y. This book is a survey of recent work on the application of number theory in statistics. The essence of number-theoretic methods is to find a set of points that are universally scattered over an s-dimensional unit cube. In certain circumstances this set can be used instead of random numbers in the…. This book presents a radically new approach to problems of evaluating and optimizing the performance of continuous-time stochastic systems.
This approach is based on the use of a family of Markov processes called Piecewise-Deterministic Processes PDPs as a general class of stochastic system…. This volume consists of a collection of tutorial papers by leading experts on statistical and probabilistic aspects of chaos and networks, in particular neural networks. While written for the non-expert, they are intended to bring the reader up to the forefront of knowledge and research in the….
By Seymour Geisser. The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference. While the book discusses a variety of approaches to prediction…. Green , Bernard. In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics.
This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method…. Smoothing Splines Methods and Applications, 1st Edition By Yuedong Wang A general class of powerful and flexible modeling techniques, spline smoothing has attracted a great deal of research attention in recent years and has been widely used in many application areas, from medicine to economics.
McKean Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models. Small Asymptotic methods provide important tools for approximating and analysing functions that arise in probability and statistics.
ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.
The fundamental theory of ROC curves The book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated. Further building on the theory, the authors present statistical tests for ROC curves and their summary statistics.