This book presents a general method for deriving higher-order statistics
of multivariate distributions with simple algorithms that allow for
actual calculations. Multivariate nonlinear statistical models require
the study of higher-order moments and cumulants. The main tool used for
the definitions is the tensor derivative, leading to several useful
expressions concerning Hermite polynomials, moments, cumulants,
skewness, and kurtosis. A general test of multivariate skewness and
kurtosis is obtained from this treatment. Exercises are provided for
each chapter to help the readers understand the methods. Lastly, the
book includes a comprehensive list of references, equipping readers to
explore further on their own.