Statistical Theory & Methods

This book provides a systematic account of robust statistical methods, an area where the existing literature is dated, narrow, or treated in an overly theoretical manner. The authors discuss the entire range of robust statistical methods at an accessible level appropriate for students at a Master's..

With worked examples and problems based on real-world scenarios, this book takes readers through the process of calculating the sample size for many types of clinical trials. It covers the most common types of clinical trials across all phases. The author discusses how assumptions made in a sample s..

Seemingly Unrelated Regression Equations Models..

This book provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical method for investigating associations between outcome events and time-varying exposures...

Semimartingales and their Statistical Inference presents a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. It includes applications of stochastic modeling from engineering, e..

Reviewing advances in skew-elliptical distributions, this book collates developments, theory, results and applications in a single source, discussing theory and inference for skew-elliptical distribution, and examining applications and case studies...

The book gathers information on the theories, applications, advantages, and limitations of all the small area estimation methodologies. It covers direct small area estimation methods, indirect statistical approaches, including empirical best linear unbiased prediction, empirical Bayes and hierarchic..

Disparities represent a lack of efficiency within the healthcare system and therefore account for unnecessary costs. With the affirmation of the Patient Protection and Affordable Care Act, reducing health disparities through enhanced public health data infrastructure and analytical capability has be..

With many real-world examples, this book shows how to apply the powerful methods of smoothing splines in practice. It covers basic smoothing spline models as well as more advanced models, such as spline smoothing with correlated random errors. It also presents methods for model selection and inferen..

In this book the author presents with elegance and precision some of the basic mathematical theory required for statistical inference at a level which will make it readable by most students of statistics...

Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods,..

Statistical Inference Based on the Likelihood introduces likelihood-based statistical theory and related methods. It takes a classical point of view and denonstrates how the main body of statistical techniques can be generated from a few key concepts. Focusing on those methods that have both a solid..