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Imputation Methods for Missing Hydrometeorological Data Estimation / by Ramesh S.V. Teegavarapu

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Water Science and Technology Library ; 108Publisher: Cham : Springer International Publishing, 2024Publisher: Cham : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(XVII, 517 p. 292 illus., 22 illus. in color.)ISBN:
  • 9783031609466
Subject(s): Additional physical formats: 9783031609459 | 9783031609473 | 9783031609480 | Erscheint auch als: 9783031609459 Druck-Ausgabe | Erscheint auch als: 9783031609473 Druck-Ausgabe | Erscheint auch als: 9783031609480 Druck-AusgabeDDC classification:
  • 551.48 23
DOI: DOI: 10.1007/978-3-031-60946-6Online resources: Summary: 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.Summary: 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. .PPN: PPN: 1896063969Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-EES | ZDB-2-SXEE
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