Statistical techniques for modelling extreme value data and related applications / by Haroon M. Barakat, El-Sayed M. Nigm and Osama M. Khaled.

By:

Barakat, Haroon M

Contributor(s):

Material type: Text

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781527534650
1527534650

Subject(s): Genre/Form:

Additional physical formats: Print version:: No titleDDC classification:

511/.8 23

LOC classification:

TA342 B37 2019eb

Online resources:

Click here to access online

Summary: This book tackles some modern trends and methods in the modelling of extreme data. Usually such data arise from random phenomena such as floods, hurricanes, air and water pollutants, extreme claim sizes, life spans, and maximum sizes of ecological populations. It provides the latest statistical methods to model these random phenomena to understand and predict them, thus allowing the avoidance of damage or at least minimizing it. In addition, this book sheds light on the mathematical and statistical theories on which applied modelling methods were built. Therefore, it has both an applied and theoretical orientation, and represents a valuable addition to existing literature on the modelling of extreme value data.

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Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Includes bibliographical references and index.

This book tackles some modern trends and methods in the modelling of extreme data. Usually such data arise from random phenomena such as floods, hurricanes, air and water pollutants, extreme claim sizes, life spans, and maximum sizes of ecological populations. It provides the latest statistical methods to model these random phenomena to understand and predict them, thus allowing the avoidance of damage or at least minimizing it. In addition, this book sheds light on the mathematical and statistical theories on which applied modelling methods were built. Therefore, it has both an applied and theoretical orientation, and represents a valuable addition to existing literature on the modelling of extreme value data.

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