Bøger af Jana Jureckova

Closely related to nonparametric methods, robust statistical methods are not unduly affected by data outliers or other small departures from model assumptions. This book presents a comprehensive overview of methodology for robust and nonparametric statistics. It covers both methods in parallel to demonstrate their relative strengths and weaknesses. Using examples to illustrate the methods, the text emphasizes applications in the fields of biomedical science, bioinformatics, finance, and engineering. The authors provide exercises in the text.

Closely related to nonparametric methods, robust statistical methods are not unduly affected by data outliers or other small departures from model assumptions. This book presents a comprehensive overview of methodology for robust and nonparametric statistics. It covers both methods in parallel to demonstrate their relative strengths and weaknesses. Using examples to illustrate the methods, the text emphasizes applications in the fields of biomedical science, bioinformatics, finance, and engineering. The authors provide exercises in the text.

While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.