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Imputation methods for missing hydrometeorological data estimation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Imputation methods for missing hydrometeorological data estimationby Ramesh S.V. Teegavarapu.
作者:	Teegavarapu, Ramesh S. V.
出版者:	Cham :Springer International Publishing :2024.
面頁冊數:	xvii, 517 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Statistical matching.
電子資源:	https://doi.org/10.1007/978-3-031-60946-6
ISBN:	9783031609466$q(electronic bk.)

Imputation methods for missing hydrometeorological data estimation
Teegavarapu, Ramesh S. V.

Imputation methods for missing hydrometeorological data estimation[electronic resource] /by Ramesh S.V. Teegavarapu. - Cham :Springer International Publishing :2024. - xvii, 517 p. :ill. (some col.), digital ;24 cm. - Water science and technology library,v. 1081872-4663 ;. - Water science and technology library ;v.66..

Introduction to Missing Data -- Methods for Imputation of Missing Data -- Temporal Interpolation Methods -- Spatial Interpolation Methods -- Data Driven Modes for Imputation -- Multiple Imputation Methods -- Evaluation of Methods and Imputed Data.

This book serves as a unique reference that provides a comprehensive discussion about the state-of-the-art spatial and temporal, statistical, and data mining methods for imputation of missing hydrometeorological data. The primary audience for this book are researchers, scientists, graduate-level and higher students, modelers, data scientists working in hydrological, meteorological, climatological, and earth sciences. Data analysts in other disciplines will also be interested in this book. The book appeals to graduate students, researchers in civil and environmental engineering, geosciences, climatology, and hydrological and data sciences. It will be an ideal reference book for state and federal agencies that collect and process hydrometeorological and climatological data. Engineering professionals, hydrologists, meteorologists, and data and spatial analysts dealing with large hydrometeorological datasets. Researchers and modelers involve in the development of long-term datasets at national and international institutions.

ISBN: 9783031609466$q(electronic bk.)

Standard No.: 10.1007/978-3-031-60946-6doiSubjects--Topical Terms:

246260
Statistical matching.

LC Class. No.: GB2801.72.S7

Dewey Class. No.: 551.57

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