During the last decades long-memory processes have evolved as a vital and important part of time series analysis. This book attempts to give an overview of the theory and methods developed to deal with long-range dependent data as well as describe some applications of these methodologies to real-life time series. The topics are systematically organized in a progressive manner, starting from foundations (the first three chapters), progressing to the analysis of methodological implications (the next six chapters), and finally extending to more complex long-range dependent data structures (the final three chapters).