Kernel Smoothing In Matlab: Theory And Practice Of Kernel Smoothing

Discover the essential guide to statistical theory and practical application with Kernel Smoothing In Matlab: Theory And Practice Of Kernel Smoothing by Ivana Horová. Published by World Scientific Publishing Co Pte Ltd in 2012, this hardback edition spans 244 pages, making it a valuable resource for both students and professionals in the field of statistics.

This book offers a comprehensive overview of kernel smoothing techniques, emphasizing the implementation of these methods using Matlab. Inside, you'll find a variety of Matlab scripts designed to assist with kernel smoothing tasks, including density estimation, cumulative distribution functions, regression functions, hazard functions, quality indices, and bivariate density analysis.

Whether you're looking to enhance your statistical toolkit or deepen your understanding of kernel functions, Ivana Horová's insightful work is an indispensable addition to your library. Elevate your statistical skills today with this authoritative resource!