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PLS regression on a stochastic process

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Cited by:

  1. Shang, Han Lin & Hyndman, Rob.J., 2011. "Nonparametric time series forecasting with dynamic updating," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(7), pages 1310-1324.
  2. Brunel, Élodie & Mas, André & Roche, Angelina, 2016. "Non-asymptotic adaptive prediction in functional linear models," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 208-232.
  3. Comte , Fabienne & Johannes, Jan, 2011. "Adaptive functional linear regression," LIDAM Discussion Papers ISBA 2011038, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  4. Kondylis, Athanassios & Whittaker, Joe, 2008. "Spectral preconditioning of Krylov spaces: Combining PLS and PC regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2588-2603, January.
  5. Berrendero, J.R. & Justel, A. & Svarc, M., 2011. "Principal components for multivariate functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2619-2634, September.
  6. Stéphanie Bougeard & Hervé Abdi & Gilbert Saporta & Ndèye Niang, 2018. "Clusterwise analysis for multiblock component methods," 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. 12(2), pages 285-313, June.
  7. Ana M. Aguilera, 2016. "Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 23-26, March.
  8. Fang Yao & Yichao Wu & Jialin Zou, 2016. "Rejoinder on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 52-58, March.
  9. Fernández-Alcalá, R.M. & Navarro-Moreno, J. & Ruiz-Molina, J.C., 2009. "Statistical inference for doubly stochastic multichannel Poisson processes: A PCA approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4322-4331, October.
  10. Aguilera, Ana M. & Escabias, Manuel & Valderrama, Mariano J., 2008. "Forecasting binary longitudinal data by a functional PC-ARIMA model," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3187-3197, February.
  11. Xavier Bry & Ndèye Niang & Thomas Verron & Stéphanie Bougeard, 2023. "Clusterwise elastic-net regression based on a combined information criterion," 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. 17(1), pages 75-107, March.
  12. Angelina Roche, 2018. "Local optimization of black-box functions with high or infinite-dimensional inputs: application to nuclear safety," Computational Statistics, Springer, vol. 33(1), pages 467-485, March.
  13. Ufuk Beyaztas & Han Lin Shang, 2021. "A partial least squares approach for function-on-function interaction regression," Computational Statistics, Springer, vol. 36(2), pages 911-939, June.
  14. Mareike Bereswill & Jan Johannes, 2013. "On the effect of noisy measurements of the regressor in functional linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 488-513, September.
  15. Tianyu Tan & Hye Suk & Heungsun Hwang & Jooseop Lim, 2013. "Functional fuzzy clusterwise regression analysis," 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. 7(1), pages 57-82, March.
  16. Ana Aguilera, 2016. "Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 23-26, March.
  17. Adil M. Bagirov & Julien Ugon & Hijran G. Mirzayeva, 2015. "Nonsmooth Optimization Algorithm for Solving Clusterwise Linear Regression Problems," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 755-780, March.
  18. D'Urso, Pierpaolo & Santoro, Adriana, 2006. "Fuzzy clusterwise linear regression analysis with symmetrical fuzzy output variable," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 287-313, November.
  19. Christian Acal & Manuel Escabias & Ana M. Aguilera & Mariano J. Valderrama, 2021. "COVID-19 Data Imputation by Multiple Function-on-Function Principal Component Regression," Mathematics, MDPI, vol. 9(11), pages 1-23, May.
  20. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
  21. Tingting Huang & Gilbert Saporta & Huiwen Wang & Shanshan Wang, 2021. "A robust spatial autoregressive scalar-on-function regression with t-distribution," 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. 15(1), pages 57-81, March.
  22. Sicard, E. & Sabatier, R., 2006. "Theoretical framework for local PLS1 regression, and application to a rainfall data set," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1393-1410, November.
  23. Manteiga, Wenceslao Gonzalez & Vieu, Philippe, 2007. "Statistics for Functional Data," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4788-4792, June.
  24. Escabias, M. & Aguilera, A.M. & Valderrama, M.J., 2007. "Functional PLS logit regression model," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4891-4902, June.
  25. Eduardo García‐Portugués & Javier Álvarez‐Liébana & Gonzalo Álvarez‐Pérez & Wenceslao González‐Manteiga, 2021. "A goodness‐of‐fit test for the functional linear model with functional response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 502-528, June.
  26. Luo, Ruiyan & Qi, Xin, 2015. "Sparse wavelet regression with multiple predictive curves," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 33-49.
  27. Bagirov, Adil M. & Ugon, Julien & Mirzayeva, Hijran, 2013. "Nonsmooth nonconvex optimization approach to clusterwise linear regression problems," European Journal of Operational Research, Elsevier, vol. 229(1), pages 132-142.
  28. Philip T. Reiss & Jeff Goldsmith & Han Lin Shang & R. Todd Ogden, 2017. "Methods for Scalar-on-Function Regression," International Statistical Review, International Statistical Institute, vol. 85(2), pages 228-249, August.
  29. Silvia Novo & Germán Aneiros & Philippe Vieu, 2021. "Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 481-504, June.
  30. Joki, Kaisa & Bagirov, Adil M. & Karmitsa, Napsu & Mäkelä, Marko M. & Taheri, Sona, 2020. "Clusterwise support vector linear regression," European Journal of Operational Research, Elsevier, vol. 287(1), pages 19-35.
  31. Aguilera, Ana M. & Escabias, Manuel & Valderrama, Mariano J., 2008. "Discussion of different logistic models with functional data. Application to Systemic Lupus Erythematosus," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 151-163, September.
  32. Ufuk Beyaztas & Han Lin Shang & Aylin Alin, 2022. "Function-on-Function Partial Quantile Regression," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 149-174, March.
  33. Cardot, Hervé & Johannes, Jan, 2010. "Thresholding projection estimators in functional linear models," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 395-408, February.
  34. Hernandez Roig, Harold Antonio & Aguilera Morillo, María del Carmen & Aguilera, Ana M. & Preda, Cristian, 2023. "Penalized function-on-function partial leastsquares regression," DES - Working Papers. Statistics and Econometrics. WS 37758, Universidad Carlos III de Madrid. Departamento de Estadística.
  35. Manuel Febrero-Bande & Pedro Galeano & Wenceslao González-Manteiga, 2017. "Functional Principal Component Regression and Functional Partial Least-squares Regression: An Overview and a Comparative Study," International Statistical Review, International Statistical Institute, vol. 85(1), pages 61-83, April.
  36. Fang Yao & Yichao Wu & Jialin Zou, 2016. "Rejoinder on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 52-58, March.
  37. Zhou, Zhiyang, 2019. "Functional continuum regression," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 328-346.
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