Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size.

Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size.

Meteorological data acquired with precision, quality, and reliability are crucial in various agronomy fields, especially in studies related to reference evapotranspiration (ETo). ETo plays a fundamental role in the hydrological cycle, irrigation system planning and management, water demand modeling,...

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Bibliographic Details
Main Authors: Valter Cesar de Souza, Sergio Augusto Rodrigues, Luís Roberto Almeida Gabriel Filho
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0315574
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