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Statistical Models
Models and likelihood are the backbone of modern statistics and data analysis. Anthony Davison here blends theory and practice to provide an integrated text for advanced …
Random Graphs and Complex Networks: Volume 2
Complex networks are key to describing the connected nature of the society that we live in. This book, the second of two volumes, describes the local structure of random graph …
Spectral Analysis for Univariate Time Series
Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts …
Statistical Hypothesis Testing in Context: Volume 52
Fay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation. The emphasis is on equipping applied …
Statistical Mechanics of Disordered Systems
This self-contained book is a graduate-level introduction for mathematicians and for physicists interested in the mathematical foundations of the field, and can be used as a …
Confidence, Likelihood, Probability
This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from …
From Finite Sample to Asymptotic Methods in Statistics
Exact statistical inference may be employed in diverse fields of science and technology. As problems become more complex and sample sizes become larger, mathematical and …
Applied Asymptotics
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 …
Design of Comparative Experiments
This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. …
Essentials Of Statistical Inference
Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and …
Markov Chains
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate …
Fundamentals of Nonparametric Bayesian Inference
Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding …