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Curves discrimination: a nonparametric functional approach

Citations

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Cited by:

  1. Guochang Wang & Xinyuan Song, 2018. "Functional Sufficient Dimension Reduction for Functional Data Classification," Journal of Classification, Springer;The Classification Society, vol. 35(2), pages 250-272, July.
  2. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
  3. Crawford, F. & Watling, D.P. & Connors, R.D., 2017. "A statistical method for estimating predictable differences between daily traffic flow profiles," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 196-213.
  4. Tengteng Xu & Riquan Zhang & Xiuzhen Zhang, 2023. "Estimation of spatial-functional based-line logit model for multivariate longitudinal data," Computational Statistics, Springer, vol. 38(1), pages 79-99, March.
  5. Mohamed Chaouch, 2023. "Probabilistic Wind Speed Forecasting for Wind Turbine Allocation in the Power Grid," Energies, MDPI, vol. 16(22), pages 1-15, November.
  6. Alicia Nieto-Reyes & Rafael Duque & Giacomo Francisci, 2021. "A Method to Automate the Prediction of Student Academic Performance from Early Stages of the Course," Mathematics, MDPI, vol. 9(21), pages 1-14, October.
  7. Bücher, Axel & Dette, Holger & Wieczorek, Gabriele, 2011. "Testing model assumptions in functional regression models," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1472-1488, November.
  8. Mirosław Krzyśko & Tomasz Górecki & Waldemar Wołyński, 2015. "Classification problems based on regression models for multi-dimensional functional data," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(1), pages 97-110, May.
  9. Fang Yao & Yichao Wu & Jialin Zou, 2016. "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 1-22, March.
  10. Olusola Samuel Makinde, 2019. "Classification rules based on distribution functions of functional depth," Statistical Papers, Springer, vol. 60(3), pages 629-640, June.
  11. repec:cte:wsrepe:ws131312 is not listed on IDEAS
  12. Manuel Febrero-Bande, 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 35-40, March.
  13. Han Lin Shang, 2014. "Bayesian bandwidth estimation for a functional nonparametric regression model with mixed types of regressors and unknown error density," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 599-615, September.
  14. Mousavi, Seyed Nourollah & Sørensen, Helle, 2017. "Multinomial functional regression with wavelets and LASSO penalization," Econometrics and Statistics, Elsevier, vol. 1(C), pages 150-166.
  15. Mohamed Chaouch & Salah Khardani, 2015. "Randomly censored quantile regression estimation using functional stationary ergodic data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(1), pages 65-87, March.
  16. Hazelton, Martin L., 2007. "Bias reduction in kernel binary regression," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4393-4402, May.
  17. Amandine Schmutz & Julien Jacques & Charles Bouveyron & Laurence Chèze & Pauline Martin, 2020. "Clustering multivariate functional data in group-specific functional subspaces," Computational Statistics, Springer, vol. 35(3), pages 1101-1131, September.
  18. Karl Mosler & Pavlo Mozharovskyi, 2017. "Fast DD-classification of functional data," Statistical Papers, Springer, vol. 58(4), pages 1055-1089, December.
  19. Helle Sørensen & Anders Tolver & Maj Halling Thomsen & Pia Haubro Andersen, 2012. "Quantification of symmetry for functional data with application to equine lameness classification," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 337-360, May.
  20. Casado, David & López Pintado, Sara, 2008. "A functional data based method for time series classification," DES - Working Papers. Statistics and Econometrics. WS ws087427, Universidad Carlos III de Madrid. Departamento de Estadística.
  21. 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.
  22. Hongxiao Zhu & Philip J. Brown & Jeffrey S. Morris, 2012. "Robust Classification of Functional and Quantitative Image Data Using Functional Mixed Models," Biometrics, The International Biometric Society, vol. 68(4), pages 1260-1268, December.
  23. Fabrizio Maturo & Antonio Balzanella & Tonio Di Battista, 2019. "Building Statistical Indicators of Equitable and Sustainable Well-Being in a Functional Framework," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(3), pages 449-471, December.
  24. Abdallah Amine Melakhsou & Mireille Batton-Hubert, 2023. "Welding monitoring and defect detection using probability density distribution and functional nonparametric kernel classifier," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1469-1481, March.
  25. M. Aguilera-Morillo & Ana Aguilera & Manuel Escabias & Mariano Valderrama, 2013. "Penalized spline approaches for functional logit regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 251-277, June.
  26. López Pintado, Sara, 2005. "Depth-based classification for functional data," DES - Working Papers. Statistics and Econometrics. WS ws055611, Universidad Carlos III de Madrid. Departamento de Estadística.
  27. Amovin-Assagba, Martial & Gannaz, Irène & Jacques, Julien, 2022. "Outlier detection in multivariate functional data through a contaminated mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  28. Alonso, Andrés M. & Casado, David & Romo, Juan, 2012. "Supervised classification for functional data: A weighted distance approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2334-2346.
  29. Manuel Escabias & Ana Aguilera & M. Aguilera-Morillo, 2014. "Functional PCA and Base-Line Logit Models," Journal of Classification, Springer;The Classification Society, vol. 31(3), pages 296-324, October.
  30. Adam B. Kashlak & John A. D. Aston & Richard Nickl, 2019. "Inference on Covariance Operators via Concentration Inequalities: k-sample Tests, Classification, and Clustering via Rademacher Complexities," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 214-243, February.
  31. Akkal Fatima & Kadiri Nadia & Rabhi Abbes, 2021. "Asymptotic Normality of Conditional Density and Conditional Mode in the Functional Single Index Model," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(1), pages 1-24, March.
  32. Mojirsheibani, Majid & Shaw, Crystal, 2018. "Classification with incomplete functional covariates," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 40-46.
  33. Dabo-Niang, Sophie & Ferraty, Frederic & Vieu, Philippe, 2007. "On the using of modal curves for radar waveforms classification," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4878-4890, June.
  34. Fang Yao & Yichao Wu & Jialin Zou, 2016. "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 1-22, March.
  35. Casado, David, 2009. "Classification of functional data: a weighted distance approach," DES - Working Papers. Statistics and Econometrics. WS ws093915, Universidad Carlos III de Madrid. Departamento de Estadística.
  36. Chen, Lu-Hung & Jiang, Ci-Ren, 2018. "Sensible functional linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 39-52.
  37. Llop, P. & Forzani, L. & Fraiman, R., 2011. "On local times, density estimation and supervised classification from functional data," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 73-86, January.
  38. Ahmedou, Aziza & Marion, Jean-Marie & Pumo, Besnik, 2016. "Generalized linear model with functional predictors and their derivatives," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 313-324.
  39. Sudaraka Tholkage & Qi Zheng & Karunarathna B. Kulasekera, 2022. "Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data," Stats, MDPI, vol. 5(4), pages 1-17, November.
  40. Poskitt, D.S. & Sengarapillai, Arivalzahan, 2013. "Description length and dimensionality reduction in functional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 98-113.
  41. Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.
  42. 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.
  43. Tian, Tian Siva & James, Gareth M., 2013. "Interpretable dimension reduction for classifying functional data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 282-296.
  44. Zhang, Tao & Zhang, Qingzhao & Wang, Qihua, 2014. "Model detection for functional polynomial regression," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 183-197.
  45. Han Lin Shang & Jiguo Cao & Peijun Sang, 2022. "Stopping time detection of wood panel compression: A functional time‐series approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1205-1224, November.
  46. Martínez-Camblor, Pablo & Corral, Norberto, 2011. "Repeated measures analysis for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3244-3256, December.
  47. Martin-Barragan, Belen & Lillo, Rosa & Romo, Juan, 2014. "Interpretable support vector machines for functional data," European Journal of Operational Research, Elsevier, vol. 232(1), pages 146-155.
  48. O. I. Traore & P. Cristini & N. Favretto-Cristini & L. Pantera & P. Vieu & S. Viguier-Pla, 2019. "Clustering acoustic emission signals by mixing two stages dimension reduction and nonparametric approaches," Computational Statistics, Springer, vol. 34(2), pages 631-652, June.
  49. 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.
  50. Mante, Claude & Yao, Anne-Francoise & Degiovanni, Claude, 2007. "Principal component analysis of measures, with special emphasis on grain-size curves," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4969-4983, June.
  51. Tomasz Górecki & Mirosław Krzyśko & Waldemar Wołyński, 2015. "Classification Problems Based On Regression Models For Multi-Dimensional Functional Data," Statistics in Transition New Series, Polish Statistical Association, vol. 16(1), pages 97-110, March.
  52. Manuel Febrero-Bande, 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 35-40, March.
  53. J. A. Cuesta-Albertos & M. Febrero-Bande & M. Oviedo de la Fuente, 2017. "The $$\hbox {DD}^G$$ DD G -classifier in the functional setting," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 119-142, March.
  54. repec:cte:wsrepe:ws120906 is not listed on IDEAS
  55. Górecki Tomasz & Krzyśko Mirosław & Wołyński Waldemar, 2015. "Classification Problems Based on Regression Models for Multi-Dimensional Functional Data," Statistics in Transition New Series, Statistics Poland, vol. 16(1), pages 97-110, March.
  56. Bongiorno, Enea G. & Goia, Aldo, 2016. "Classification methods for Hilbert data based on surrogate density," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 204-222.
  57. Zheng, Shurong, 2008. "Selection of components and degrees of smoothing via lasso in high dimensional nonparametric additive models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 164-175, September.
  58. Jacques, Julien & Preda, Cristian, 2014. "Model-based clustering for multivariate functional data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 92-106.
  59. Pigoli, Davide & Sangalli, Laura M., 2012. "Wavelets in functional data analysis: Estimation of multidimensional curves and their derivatives," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1482-1498.
  60. Peter Radchenko & Xinghao Qiao & Gareth M. James, 2015. "Index Models for Sparsely Sampled Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(510), pages 824-836, June.
  61. Andrés Alonso & David Casado & Sara López-Pintado & Juan Romo, 2014. "Robust Functional Supervised Classification for Time Series," Journal of Classification, Springer;The Classification Society, vol. 31(3), pages 325-350, October.
  62. Park, Yeonjoo & Simpson, Douglas G., 2019. "Robust probabilistic classification applicable to irregularly sampled functional data," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 37-49.
  63. González, Javier & Muñoz, Alberto, 2010. "Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification," DES - Working Papers. Statistics and Econometrics. WS ws102713, Universidad Carlos III de Madrid. Departamento de Estadística.
  64. 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.
  65. Shin, Hyejin, 2008. "An extension of Fisher's discriminant analysis for stochastic processes," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1191-1216, July.
  66. Tomasz Górecki & Mirosław Krzyśko & Waldemar Wołyński, 2019. "Variable Selection In Multivariate Functional Data Classification," Statistics in Transition New Series, Polish Statistical Association, vol. 20(2), pages 123-138, June.
  67. Fabrizio Maturo & Rosanna Verde, 2023. "Supervised classification of curves via a combined use of functional data analysis and tree-based methods," Computational Statistics, Springer, vol. 38(1), pages 419-459, March.
  68. Manteiga, Wenceslao Gonzalez & Vieu, Philippe, 2007. "Statistics for Functional Data," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4788-4792, June.
  69. Górecki Tomasz & Krzyśko Mirosław & ński Waldemar Woły, 2019. "Variable Selection In Multivariate Functional Data Classification," Statistics in Transition New Series, Statistics Poland, vol. 20(2), pages 123-138, June.
  70. Chung Chang & Yakuan Chen & R. Ogden, 2014. "Functional data classification: a wavelet approach," Computational Statistics, Springer, vol. 29(6), pages 1497-1513, December.
  71. Ling, Nengxiang & Xu, Qian, 2012. "Asymptotic normality of conditional density estimation in the single index model for functional time series data," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2235-2243.
  72. Prieto, Francisco J. & Rendón, Carolina, 2014. "Independent components techniques based on kurtosis for functional data analysis," DES - Working Papers. Statistics and Econometrics. WS ws141006, Universidad Carlos III de Madrid. Departamento de Estadística.
  73. 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.
  74. Maria Ruiz-Medina & Rosa Espejo & Elvira Romano, 2014. "Spatial functional normal mixed effect approach for curve classification," 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. 8(3), pages 257-285, September.
  75. Zhu, Hanbing & Li, Rui & Zhang, Riquan & Lian, Heng, 2020. "Nonlinear functional canonical correlation analysis via distance covariance," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
  76. Huaihou Chen & Philip T. Reiss & Thaddeus Tarpey, 2014. "Optimally weighted L-super-2 distance for functional data," Biometrics, The International Biometric Society, vol. 70(3), pages 516-525, September.
  77. M'hamed Ezzahrioui & Elias Ould Saïd, 2010. "Some asymptotic results of a non‐parametric conditional mode estimator for functional time‐series data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 171-201, May.
  78. Zhou, Jie, 2011. "Maximum likelihood ratio test for the stability of sequence of Gaussian random processes," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2114-2127, June.
  79. Epifanio, Irene & Ventura-Campos, Noelia, 2011. "Functional data analysis in shape analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2758-2773, September.
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