Gaussian process methods for nonparametric functional regression with mixed predictors

DOI10.1016/J.CSDA.2018.07.009zbMath1471.62204OpenAlexW2883039040WikidataQ129457120 ScholiaQ129457120MaRDI QIDQ1615264

Aiping Xu, Bo Wang

Publication date: 2 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2381/43080

zbMATH Keywords

functional principal component analysisGaussian process regressionfunctional regressionnonparametric methodssemi-metric

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10)

Related Items (3)

Editorial for the special issue on high-dimensional and functional data analysis ⋮ On Some Characteristics of Gaussian Covariance Functions ⋮ Statistical test for anomalous diffusion based on empirical anomaly measure for Gaussian processes

Uses Software

• fda (R)

Cites Work

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