Functional regression on remote sensing data in oceanography-Reference-Cited by-同舟云学术

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Functional regression on remote sensing data in oceanography

Published:2018-05-02 Issue:2 Volume:25 Page:277-304
ISSN:1352-8505
Container-title:Environmental and Ecological Statistics
language:en
Short-container-title:Environ Ecol Stat

Author:

Acar-Denizli Nihan^ORCID,Delicado Pedro^ORCID,Başarır Gülay,Caballero Isabel

Funder

Ministerio de Ciencia e Innovacion and Fondo Europeo de Desarrollo Regional

Mimar Sinan Fine Arts University Coordinatorship of Scientific Research Projects

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,General Environmental Science,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s10651-018-0405-7/fulltext.html

Reference48 articles.

1. Acar-Denizli N, Delicado P, Başarır G, Caballero I (2017) Functional linear regression models for scalar responses on remote sensing data: an application to oceanography. In: Functional statistics and related fields, Springer, Brelin, pp 15–21

2. Aguilera AM, Escabias M, Preda C, Saporta G (2010) Using basis expansions for estimating functional PLS regression: applications with chemometric data. Chemom Intell Lab Syst 104(2):289–305

3. Bernardello R, Serrano E, Coma R, Ribes M, Bahamon N (2016) A comparison of remote-sensing sst and in situ seawater temperature in near-shore habitats in the western mediterranean sea. Mar Ecol Prog Ser 559:21–34

4. Besse PC, Cardot H, Faivre R, Goulard M (2005) Statistical modelling of functional data. Appl Stoch Models Bus Ind 21(2):165–173

5. Binding C, Bowers D, Mitchelson-Jacob E (2003) An algorithm for the retrieval of suspended sediment concentrations in the irish sea from seawifs ocean colour satellite imagery. Int J Remote Sens 24(19):3791–3806

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