Estimation and Clustering of Directional Wave Spectra
Author
Abstract
Suggested Citation
DOI: 10.1007/s13253-023-00543-4
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- López-Pintado, Sara & Romo, Juan, 2009. "On the Concept of Depth for Functional Data," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 718-734.
- Oliveira, María & Crujeiras, Rosa M. & Rodríguez-Casal, Alberto, 2014. "NPCirc: An R Package for Nonparametric Circular Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i09).
- García-Portugués, Eduardo & Crujeiras, Rosa M. & González-Manteiga, Wenceslao, 2013. "Kernel density estimation for directional–linear data," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 152-175.
- Ribeiro, P.J.C. & Henriques, J.C.C. & Campuzano, F.J. & Gato, L.M.C. & Falcão, A.F.O., 2020. "A new directional wave spectra characterization for offshore renewable energy applications," Energy, Elsevier, vol. 213(C).
- Di Marzio, Marco & Panzera, Agnese & Taylor, Charles C., 2009. "Local polynomial regression for circular predictors," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 2066-2075, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Paula Saavedra-Nieves & Rosa M. Crujeiras, 2022. "Nonparametric estimation of directional highest density regions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(3), pages 761-796, September.
- Bedouhene Kahina & Zougab Nabil, 2020. "A Bayesian procedure for bandwidth selection in circular kernel density estimation," Monte Carlo Methods and Applications, De Gruyter, vol. 26(1), pages 69-82, March.
- Claudio Durastanti, 2016. "Quantitative central limit theorems for Mexican needlet coefficients on circular Poisson fields," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 651-673, November.
- Sümeyra Sert & Filiz Kardiyen, 2023. "A method for detecting outliers in linear-circular non-parametric regression," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-17, June.
- Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
- Francesca Ieva & Anna Paganoni, 2015. "Discussion of “multivariate functional outlier detection” by M. Hubert, P. Rousseeuw and P. Segaert," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 217-221, July.
- Fernández de Marcos Giménez de los Galanes, Alberto & García Portugués, Eduardo, 2022. "Data-driven stabilizations of goodness-of-fit tests," DES - Working Papers. Statistics and Econometrics. WS 35324, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Carlo Sguera & Pedro Galeano & Rosa Lillo, 2014.
"Spatial depth-based classification for functional data,"
TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(4), pages 725-750, December.
- Sguera, Carlo & Galeano San Miguel, Pedro & Lillo Rodríguez, Rosa Elvira, 2012. "Spatial depth-based classification for functional data," DES - Working Papers. Statistics and Econometrics. WS ws120906, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Daniel Kosiorowski & Dominik Mielczarek & Jerzy. P. Rydlewski, 2017. "Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for Day and Night Air Pollution in Silesia Region: A Critical Overview," Papers 1712.03797, arXiv.org.
- Nieto-Reyes, Alicia & Battey, Heather, 2021. "A topologically valid construction of depth for functional data," Journal of Multivariate Analysis, Elsevier, vol. 184(C).
- Flores Díaz, Ramón Jesús & Lillo Rodríguez, Rosa Elvira & Romo, Juan, 2014. "Homogeneity test for functional data based on depth measures," DES - Working Papers. Statistics and Econometrics. WS ws140101, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Stanislav Zámečník & Ivana Horová & Stanislav Katina & Kamila Hasilová, 2024. "An adaptive method for bandwidth selection in circular kernel density estimation," Computational Statistics, Springer, vol. 39(4), pages 1709-1728, June.
- Miguel Flores & Salvador Naya & Rubén Fernández-Casal & Sonia Zaragoza & Paula Raña & Javier Tarrío-Saavedra, 2020. "Constructing a Control Chart Using Functional Data," Mathematics, MDPI, vol. 8(1), pages 1-26, January.
- Nagy, Stanislav & Ferraty, Frédéric, 2019. "Data depth for measurable noisy random functions," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 95-114.
- Alba M. Franco-Pereira & Rosa E. Lillo, 2020. "Rank tests for functional data based on the epigraph, the hypograph and associated graphical representations," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(3), pages 651-676, September.
- Andrea Meilán-Vila & Rosa M. Crujeiras & Mario Francisco-Fernández, 2024. "Nonparametric estimation for a functional-circular regression model," Statistical Papers, Springer, vol. 65(2), pages 945-974, April.
- Han, Qinkai & Chu, Fulei, 2021. "Directional wind energy assessment of China based on nonparametric copula models," Renewable Energy, Elsevier, vol. 164(C), pages 1334-1349.
- Francesca Ieva & Anna Maria Paganoni, 2020. "Component-wise outlier detection methods for robustifying multivariate functional samples," Statistical Papers, Springer, vol. 61(2), pages 595-614, April.
- Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
- Moliner, Jesús & Epifanio, Irene, 2019. "Robust multivariate and functional archetypal analysis with application to financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 195-208.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jagbes:v:28:y:2023:i:3:d:10.1007_s13253-023-00543-4. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.