Parameterized complexity is currently a thriving field in complexity theory and algorithm design. A significant part of the success of …
This book is the first to treat the analytic aspects of combinatorial enumeration from a multivariate perspective. Analytic combinatorics is …
The three decades which have followed the publication of Heinz Neudecker's seminal paper `Some Theorems on Matrix Differentiation with Special …
This market leader offers a readable introduction to the statistical analysis of multivariate observations. Gives readers the knowledge necessary to …
This market leading text is appropriate for courses that teach statistical methods for describing and analyzing multivariate data in depts. …
This market-leading book offers a readable introduction to the statistical analysis of multivariate observations. Its overarching goal is to provide …
Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an …
This paperback reprint of the classic work on statistical inference remains highly applicable to statistical analysis. The purpose of this …
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on …
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings …
A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applicationsMultivariate Statistics: High-Dimensional and Large-Sample Approximations is the …
An accessible guide to the multivariate time series tools used in numerous real-world applicationsMultivariate Time Series Analysis: With R and …
This book is open access under a CC BY 4.0 licenseThis open access book brings together the latest genome base …
