Model Selection and Model Averaging

Gerda Claeskens, Nils Lid Hjort

Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field.

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Symmetry Studies

Marlos A. G. Viana

Experimental data can often be associated with or indexed by certain symmetrically interesting structures or sets of labels that appear, for example, in the study of short symbolic sequences in molecular biology, in preference or voting data, in (corneal) curvature data, and in studies of the handedness and entropy of symbolic sequences and elementary images.

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Statistical Models

A.C. Davison

Models and likelihood are the backbone of modern statistics and data analysis. The coverage is unrivalled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics.

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Design of Comparative Experiments

R.A. Bailey

Design of Comparative Experiments develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams.

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Design of Comparative Experiments

R.A. Bailey

Design of Comparative Experiments develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams.

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Random Networks for Communication

Massimo Franceschetti, Ronald Meester

When is a random network (almost) connected? How much information can it carry? How can you find a particular destination within the network?

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Saddlepoint Approximations with Applications

Ronald W. Butler

Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer.

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Applied Asymptotics

A.R. Brazzale, A.C. Davison, N. Reid

In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable.

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