A comparison of data imputation methods using Bayesian compressive sensing and Empirical Mode Decomposition for environmental temperature data

Environmental Modelling and Software

Volumn 102, Issue , 2018, Pages 172-184

  Williams, D Alexandra ^a   Nelsen, Benjamin ^b   Berrett, Candace ^a   Williams, Gustavious P ^b   Moon, Todd K ^c  

^a BRIGHAM YOUNG UNIVERSITY   (United States)

^b Department of Electrical and Computer Engineering   (United States)

^c Utah State University   (United States)

Author keywords

Bayesian compressive sensing; Empirical mode decomposition; Environmental data imputation

Indexed keywords

COMPRESSED SENSING;

BAYESIAN; BAYESIAN COMPRESSIVE SENSING; COMPRESSIVE SENSING; DATA IMPUTATION; DATA IMPUTATION METHODS; EMPIRICAL MODE DECOMPOSITION; ENVIRONMENTAL DATA; ENVIRONMENTAL DATA IMPUTATION; SPARSE DATA; TEMPERATURE DATA;

EMPIRICAL MODE DECOMPOSITION;

BAYESIAN ANALYSIS; DATA ACQUISITION; DATA SET; DECOMPOSITION; NUMERICAL METHOD; NUMERICAL MODEL; SPATIOTEMPORAL ANALYSIS; TEMPERATURE EFFECT; TEMPORAL VARIATION;

EID: 85042942538     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2018.01.012     Document Type: Article

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