An exposition of density estimation for statistics and data analysis. A volume in the Monographs on Statistics and Applied Probability series, it is designed for applied statisticians

This text presents a 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 models. A PDP is a Markov process that follows deterministic trajectories between random jumps, the latter occurring either spontaneously, in a Poisson-like fashion, or when the process hits the boundary of its state space.

Much of the data collected in medicine and the social sciences is categorical, for example, sex, marital status, blood group, whether a smoker or not and so on, rather than interval-scaled. Frequently the researcher collecting such data is interested in the relationships or associations between pairs, or between a set of such categorical variables; often the data is displayed in the form of a contingency table for example, smoker versus non-smoker against death from lung cancer or death from some other cause. This text gives a comprehensive account of the analysis of such tables, written at a...

Ever since the introduction by Rao in 1945 of the Fisher information metric on a family of probability distributions there has been interest among statisticians in the application of differential geometry to statistics. This interest has increased rapidly in the last couple of decades with the work of a large number of researchers. Until now an impediment to the spread of these ideas into the wider community of statisticians is the lack of a suitable text introducing the modern co-ordinate free approach to differential geometry in a manner accessible to statisticians.

This book is a follow-up to the authors' previous book Asymptotic Techniques in Statistics. It is a systematic account of an important area of theoretical statistics.

In the original edition of this book the emphasis was largely on exact methods, with permutation techniques being the main unifying theme. These features are retained, but two considerations have made it desirable to shift the emphasis. One is that there is more interest in estimation techniques within the general area on nonparametrics. This means that more emphasis on estimating equations is provided as a unifying notion. The other important consideration is applicability. It is clear that many practical problems do not have exact non-parametric solutions. Therefore asymptotic...

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. Nonparametric regression and density estimation are two of the most fundamental problems to which kernel smoothing provides a simple and effective solution.

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, and Latinized designs. It describes how appropriate and efficient designs can be constructed through the use of cyclic methods and recently developed computer algorithms. In this new edition, a greater emphasis is given to the construction and properties of resolvable block and row-column...

The analysis prediction and interpolation of economic and other time series has a long history and many applications. 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 and are intended to be an introduction accessible to readers from a range of backgrounds.
The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory...