This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics.
Empirical likelihood (EL) for time series and spatial data is an active area of research in statistics and econometrics. This book provides an accessible account of the empirical likelihood methodology and an up-to-date account of the latest advances on the topic. Applications for time series, econometrics, high-dimensional data and spatial data are covered as well as frequency domain empirical likelihood and long-range dependence.The book is intended for statisticians who want to learn about EL methodology and conduct research in this area. It is also useful for practitioners who want to apply the EL methodology in their work, but do not have the time to cover the literature scattered over various journal articles. In addition to statisticians, researchers working in economics, finance, electrical engineering (signal processing, communications), climatology and environmental sciences will find the book useful.
"The book can be used as a graduate-level text for a special topics course on resampling methods for dependent data and also as a research monograph for statisticians and econometricians who want to learn more about the topic and want to apply the methods in their own research."--BOOK JACKET.