Recent Advances in Robust Statistics: Theory and Applications

Recent Advances in Robust Statistics: Theory and Applications

Claudio Agostinelli , Ayanendranath Basu , Peter Filzmoser
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2016 · Английский · Kindle
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Описание

This book offers a comprehensive exploration of the latest advancements in robust statistics, a vital area of study that focuses on methods to ensure accuracy and reliability in statistical analysis, even in the presence of outliers and anomalies. The authors, renowned experts in the field, combine profound theoretical insights with practical applications, making complex concepts accessible to a broad audience.

Readers will find discussions on a variety of topics, including innovative techniques and methodologies that enhance statistical robustness. The collaboration of the authors lends depth to the content, offering diverse perspectives that enrich the understanding of statistical tools' real-world applicability.

Through case studies and examples, the book demonstrates how robust statistics can be effectively utilized across different fields, ranging from data science to environmental studies. This not only highlights the theoretical underpinnings but also illustrates how these advancements can lead to better decision-making and more accurate interpretations of data in various sectors.

Детали книги

Формат Kindle
Язык Английский
Опубликовано Nov 10, 2016
Издатель Springer
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