{ "item_title" : "Multivariate Statistical Methods", "item_author" : [" György Terdik "], "item_description" : "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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/3/03/081/391/3030813916_b.jpg", "price_data" : { "retail_price" : "119.99", "online_price" : "119.99", "our_price" : "119.99", "club_price" : "119.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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