Due to high–speed internet and the power and speed of the new generation of computers, a researcher now faces somevery challenging phenomena and must deal with an ever–increasing amount of data. In order to find useful information and hidden patterns underlying the data, a researcher may use various data–mining methods and techniques for random samples. Adding a time dimension to these large databases certainly introduces new aspects and challenges.
Following on from his highly successful and much lauded book,Time Series Analysis Univariate and Multivariate Methods
, this new work focuses is on high dimensional multivariate time series, illustrated with many high dimensional empirical time series.Multivariate Time Series Analysis and its Applications
includes many topics that are not found in general multivariate time series books:
- repeated measurements
- space time series modelling
- dimension reduction
This book is designed for an advanced time series analysis course, where research–oriented projects will be suggested rather than introductory topics covered. It is a must–have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.