There are 180 publications.

1) Meilán-Vila, A., Fernández-Casal, R., Crujeiras, R.M., Francisco-Fernández, M. (To appear) . A computational validation for nonparametric assessment of spatial trends Computational Statistics . Google Scholar

2) Meilán-Vila, A., Francisco-Fernández, M., Crujeiras, R.M. (To appear) . Goodness-of-fit tests for multiple regression with circular response Journal of Statistical Computation and SimulationTaylor and Francis. . Google Scholar

3) González-Manteiga, W., Crujeiras, R.M., García-Portugués, Eduardo (To appear) . A review of goodness-of-fit tests for models involving functional data TRENDS IN MATHEMATICAL, INFORMATION AND DATA SCIENCES: A TRIBUTE TO LEANDRO PARDO . Google Scholar

4) Fanjul Hevia, A., Pardo Fernández, Juan Carlos, Van Keilegom, I., González-Manteiga, W. (To appear) . "A test for comparison conditional ROC curves with multidimensional covariates". Journal of Applied Statistics . Google Scholar

5) Almomani, A., Saavedra-Nieves, P., Barreiro, P., Durán, R., Crujeiras, R.M., Loureiro, M., Sánchez-Vila, E, (To appear) . "Application of choice models in Tourism Recommender Systems". Expert Systems . Google Scholar

6) Meilán-Vila, A., Crujeiras, R.M., Francisco-Fernández, M. (To appear) . Nonparametric estimation for a functional-circular regression model Statistical Papers . Google Scholar

7) Febrero-Bande, M., Galeano, P., García-Portugués, Eduardo, González-Manteiga, W. (To appear) . Testing for linearity in scalar-on-function regression with responses missing at random Computational Statistics . Google Scholar

8) Vázquez-Mera, S., Martelo-Vidal, L., Miguéns-Suárez, P., Saavedra-Nieves, P., Arias, P., Antía Ferreiro-Pose, Juan Vázquez, Salgado, F. J., González-Barcala, F.J., Nieto-Fontarigo. J. J. (To appear) . "Exploring CD26-/lo subpopulations of lymphocytes in asthma phenotype and severity: a novel CD4+ T cell subset expressing archetypical granulocyte proteins ". Allergy, European Journal of Allergy and Clinical Immunology . Google Scholar

9) Saavedra-Nieves, P., Fernández Pérez, M. (To appear) . "Directional density-based clustering". Advances in Data Analysis and Classification . Google Scholar

10) Borrajo, M.I., González-Manteiga, W., Martínez-Miranda, M.D. (2024) . Goodness-of-fit test for point processes first-order intensity Computational Statistics and Data Analysis . Google Scholar

11) Ameijeiras-Alonso, J., I. Gijbels (2024) . Smoothed circulas: nonparametric estimation of circular cumulative distribution functions and circulas Bernoulli 30. pp. 2747-2769. ISSN: 1350-7265 . Google Scholar

12) Saavedra Nieves, A., Saavedra-Nieves, P. (2024) . On the estimation of the core for TU games Expert Systems with Applications 245. pp. 123132. Elsevier. . Google Scholar

13) Ameijeiras-Alonso, J.(2024) . A reliable data-based smoothing parameter selection method for circular kernel estimation Statistics and Computing 34. pp. 1-13. Springer. ISSN: 0960-3174 . Google Scholar

14) Ginzo-Villamayor, M.J., Molina-Valero, J.A., Martínez Calvo, Adela, Novo Pérez, M.A., Álvarez-González, J.G., Montes-Pita, F., Pérez-Cruzado, C. (2024) . Operationalizing TLS in Forest Inventories: The R Package FORTLS Anais do Seminário Internacional de Estatística com R 5(2). pp. 1-5. VIII Seminário Internacional de Estatística com R (VIII SER) , Niterói, 03-06 jun 2024. ISSN: 2526-7299 . Google Scholar

15) Chauca-Bajaña, L., Pérez-Jardón, A., Vieira E Silva, F.F., Conde Amboage M., Velásquez-Ron, B., Padín-Iruegas, M. E., Pérez-Sayans, M. (2024) . Root Coverage Techniques: Coronally Advancement Flap vs. Tunnel Technique: A Systematic Review and Meta-Analysis Dentistry Journal 12. pp. 341. ISSN: 2304-6767 . Google Scholar

16) Conde Amboage M., Van Keilegom, I., González-Manteiga, W. (2023) . Application of Quantile Regression Models for Biomedical Data. In: Larriba, Y. (eds) Statistical Methods at the Forefront of Biomedical Advances. Springer, Cham. . Google Scholar

17) Ameijeiras-Alonso, J., Domingues, T.D., Malato, J., Grabowska, A.D., Lee, J.-S., Biecek, P., Graça, L., Mouriño, H., Scheibenbogen, C., Westermeier, F., Nacul, L., Cliff, J.M., Lacerda, E.M., Sepúlveda, N. (2023) . Association analysis between symptomology and herpesvirus IgG antibody concentrations in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and multiple sclerosis Heliyon 9. pp. e18250. CellPress. ISSN: 2405-8440 . Google Scholar

18) Fuentes-Santos, I., González-Manteiga, W., Mateu, J. (2023) . Testing similarity between first-order intensities of spatial point processes. A comparative study Communications in Statistics-Simulation and Computation 52 Issue 5. pp. 2210-2230. Taylor and Francis. . Google Scholar

19) Varela-Estevez, R., Castineiras-Tourino, M., Saavedra-Nieves, P., Vázquez-Quiñoy, C., Estany-Gestal, A. (2023) . "Ansiedad y depresión en matronas del Área de Santiago de Compostela durante la pandemia por la COVID-19". Matronas Profesión 24(1). pp. 4. ISSN: 1578-0740 . Google Scholar

20) Vázquez-Mera, S., Martelo-Vidal, L., Miguéns-Suárez, P., Saavedra-Nieves, P., Arias, P., González-Fernández. C., Mosteiro-Añón, M., Corbacho-Abelaira, M. D., Blanco-Aparicio, M., Méndez-Brea, P., Salgado, F.J., Nieto-Fontarigo, J.J., González-Barcala, F.J. (2023) . "Serum exosome inflamma-miRs are surrogate biomarkers for asthma phenotype and severity". Allergy: European Journal of Allergy and Clinical Immunology 78(1). pp. 141-155. . Google Scholar

21) Ameijeiras-Alonso, J., Crujeiras, R.M. (2023) . "Mutimodality tests for gene-based identification of oncological patients". Statistical Methods at the Forefront of Biomedical Advancespp. 45-61. Springer. . Google Scholar

22) Saavedra Nieves, A., Saavedra-Nieves, P. (2023) . "Estimation of bankruptcy rules with a priori unions for establishing new systems of quotas". BEIO 39(1). pp. 25-43. . Google Scholar

23) Fuentes-Santos, I., González-Manteiga, W., Mateu, J. (2023) . Bootstrap bandwidth selection for the pair correlation function of inhomogeneous spatial point processes Journal of Statistical Computation and Simulation 93 Issue 18. pp. 3329-3361 . Taylor-Francis. . Google Scholar

24) Jácome, M. A., López Cheda, A., Aneiros Pérez, German, Carpente, L., Costa, J., Estévez Pérez, Graciela, Francisco-Fernández, M., Ginzo-Villamayor, M.J., González-Rueda, A. M., Malheiro, M.T., Muiños-Roca, M.C., Oviedo, M, Piñeiro Lamas, B., Presedo Quindimil, Manuel Antonio, Rodríguez-Fraguela, L.F. (2023) . ACTAS XVI Congreso Galego de Estatística e Investigación de Operacións e I Xornadas Innovación Docente na Estatística e Investigación de Operacións ISBN: 978-84-09-50202-8. Comité Organizador. Jácome-Pumar,M.A, López-Cheda, A., Aneiros-Pérez, G., Carpente-Rodríguez, M.L., Costa-Bouzas, J., Estévez-Pérez, G., Francisco- Fernández, M., Ginzo-Villamayor, M.J., González-Rueda, A.M., Malheiro, M.T., Muiños-Roca, M.C., Oviedo de l. . Google Scholar

25) Alonso-Pena, M., Bolon, D., Ameijeiras-Alonso, J., Saavedra Nieves, A., Saavedra-Nieves, P. (2023) . Manual de R para prácticas de Bioestadística ISBN: 9788419679536. Universidade de Santiago de Compostela. . Google Scholar

26) Ameijeiras-Alonso, J., Ley, C. (2022) . Sine-skewed toroidal distributions and their application in protein bioinformatics Biostatistics 23 (3). pp. 685–704. Oxford Academic. ISSN: 1465-4644 . Google Scholar

27) Ameijeiras-Alonso, J., Crujeiras, R.M. (2022) . Flexible circular modeling: a case study of car accidents Directional Statistics for Innovative Applications: A Bicentennial Tribute to Florence Nightingalepp. 93-116. Springer. ISSN: 978981191 . Google Scholar

28) Saavedra-Nieves, P.(2022) . "Nonparametric estimation of highest density regions for COVID-19". Journal of Nonparametric Statistics 34(3). pp. 663-682. Taylor & Francis. . Google Scholar

29) Febrero-Bande, M., González-Manteiga, W., Oviedo, M (2022) . Prediction Models with Functional Data for Variables related with Energy Production Mathematics inspired by Applications. The European Consortium for Mathematics in Industry 38. pp. 271-297. Springer. ISSN: 1612-3956 . Google Scholar

30) Rodríguez-Casal, A., Saavedra-Nieves, P. (2022) . A data-adaptive method for estimating density level sets under shape conditions Annals of Statistics 50. pp. 1653-1668. ISSN: 0090-5364 . Google Scholar

31) Molina-Valero, J.A., Martínez Calvo, Adela, Ginzo-Villamayor, M.J., Novo Pérez, M.A., Álvarez-González, J.G., Montes-Pita, F., Pérez-Cruzado, C. (2022) . Operationalizing the use of TLS in forest inventories: The R package FORTLS Environmental Modelling and Software 150. pp. 1-18. Springer. ISSN: 1364-8152 . Google Scholar

32) Chantada-Vázquez, M.P., Conde Amboage M., Graña-López, L., Vázquez-Estévez, S., Bravo, S.B. , Núñez, C. (2022) . Circulating Proteins Associated with Response and Resistance to Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer Cancers 14. MDPI. ISSN: 2072-6694 . Google Scholar

33) Ameijeiras-Alonso, J., I. Gijbels, Verhasselt, A. (2022) . On a family of two-piece circular distributions Computational Statistics & Data Analysis 168. pp. 107403. Elsevier Science Bv. ISSN: 0167-9473 . Google Scholar

34) Pérez-Sayans, M., Castelo-Baz, P., Peñarrocha Oltra, D., Seijas Naya, F., Conde Amboage M., Somoza Martín, J.M. (2022) . Impact of abutment geometry on early implant marginal bone loss. A double-blind, randomised, 6-month clinical trial Clinical Oral Implants Research 33. pp. 1038 - 1048. Wiley Online Library. ISSN: 1600-0501 . Google Scholar

35) Lorenzo-Pouso, A.I., Bravo, S.B. , Carballo, J., Chantada-Vázquez, M.P., Bagán, J., Bagán, L., Chamorro-Petronacci, C.M., Conde Amboage M., López López, R., García-García, A., Pérez-Sayans, M. (2022) . Quantitative proteomics in medication-related osteonecrosis of the jaw: A proof-of-concept study Oral DiseasesWiley. ISSN: 1354-523X . Google Scholar

36) Ameijeiras-Alonso, J., Crujeiras, R.M., Ginzo-Villamayor, M.J., Rodríguez-Casal, A., Saavedra-Nieves, P. (2022) . ADISTA22: Advances in Directional Statistics. Santiago de Compostela15-17th June, 2022. Programme and Book of AbstractsISBN 978-84-19155-92-4 pp. 78. Servicio de Publicacións da Universidade de Santiago de Compostela. Editors: Ameijeiras-Alonso, J., Crujeiras, R.M., Ginzo-Villamayor, M.J., Rodríguez-Casal, A., Saavedra-Nieves, P.. . Google Scholar

37) Saavedra-Nieves, P., Crujeiras, R.M. (2022) . "HDiR: An R Package for Computation and Nonparametric Plug-in Estimation of Directional Highest Density Regions and General Level Sets". The R Journal 14(3). pp. 121-141. . Google Scholar

38) França, F., Padín-Iruegas, M. E., Caponio, V. C. A., Lorenzo-Pouso, A. I., Saavedra-Nieves, P., Chamorro-Petronacci, C.M., Suárez-Peñaranda José M, Pérez-Sayans, M. (2022) . Caspase 3 and Cleaved Caspase 3 Expression in Tumorogenesis and Its Correlations with Prognosis in Head and Neck Cancer: A Systematic Review and Meta-Analysis International Journal of Molecular Sciences 23(19). pp. 11937. . Google Scholar

39) Faraldo Roca, Pedro, Crujeiras, R.M., Pérez Rodríguez, M., Martínez Calvo, Adela, Lombardía, M. J., Naya Fernández, Salvador, Matías, J.M., Fernández de Castro, Belén M., Carreira V. (2022) . Estudo da inserción laboral dos titulados no Sistema Universitario de Galicia 2014-2015 (EIL1415)pp. 24. Axencia para a Calidade do Sistema Universitario de Galicia (ACSUG). ISSN: 978-84-12 . Google Scholar

40) Marey Pérez, Manuel F., Fuentes-Santos, I., Saavedra-Nieves, P., González-Manteiga, W. (2022) . Nonparametric comparative analysis of the spatiotemporal pattern of human caused and natural wildfires in Galicia International Journal of Wildland Fire 32 Issue 2. pp. 178-194. CSIRO PUBLISHING. ISSN: 1049-8001 . Google Scholar

41) Sánchez Sellero, C., Ginzo-Villamayor, M.J., Ameijeiras-Alonso, J., Borrajo, M.I., Conde Amboage M., Diéguez-Taboada, M., Faraldo Roca, Pedro, López Vizcaíno, María Esther, Martín Vila, M., Saavedra Nieves, A., Saavedra-Nieves, P. (2021) . ACTAS XV CONGRESO GALEGO DE ESTATÍSTICA E INVESTIGACIÓN DE OPERACIÓNS. Santiago de Compostela, 4-5-6 de novembro de 2021 ISBN: 978-84-09-35306-4. pp. 278. Departamento de Estadística, Análisis Matemático y Optimización (USC). Editors: Sánchez Sellero, C., Ginzo-Villamayor, M.J., Ameijeiras-Alonso, J., Borrajo, M.I., Conde, M., Diéguez-Taboada, M., Faraldo Roca, P., López Vizcaíno, M.E., Martín Vila, M., Saa. . Google Scholar

42) Ameijeiras-Alonso, J., Crujeiras, R.M., Rodríguez-Casal, A. (2021) . multimode: an R package for mode assessment Journal of Statistical Software 97 (9). pp. 1-32. ISSN: 1548-7660 . Google Scholar

43) Ameijeiras-Alonso, J., Ley, C., Pewsey, A., Verdebout, T. (2021) . Simple optimal tests for circular reflective symmetry about an unknown central direction Statistical Papers 62. pp. 1651-1674. Springer. ISSN: 0932-5026 . Google Scholar

44) Saavedra-Nieves, P., Crujeiras, R.M., Vieira-Lanero, R., Caballero, P., Cobo Gradín, F. (2021) . Assessing the effect of recovery programs for salmon (Salmo salar Linnaeus, 1758) at its Southern limit in Europe: application of segmented regression models to long-term data from the Ulla Limnetica 40. Asociación Ibérica de Limnología. . Google Scholar

45) Fuentes-Santos, I., González-Manteiga, W., Zubelli, J. (2021) . Nonparametric spatiotemporal analysis of violent crime. A case study in the Rio de Janeiro metropolitan area. Spatial Statistics 42. pp. 100431. Elsevier. ISSN: 2211-6753 . Google Scholar

46) García-Portugués, Eduardo, Álvarez-Liébana, J., Álvarez-Pérez, G., González-Manteiga, W. (2021) . A goodness-of-fit test for the functional linear model with functional response Scandinavian Journal of Statistics 48. pp. 502–528. . Google Scholar

47) Alonso-Pena, M., Ameijeiras-Alonso, J., Crujeiras, R.M. (2021) . Nonparametric tests for circular regression Journal of Statistical Computation and Simulation 91(3). pp. 477-500. Taylor & Francis Ltd. ISSN: 0094-9655 . Google Scholar

48) Fanjul Hevia, A., Pardo Fernández, Juan Carlos, González-Manteiga, W. (2021) . A non-parametric test for comparing conditional ROC curves Computational Statistics and Data Analysis 157. pp. 107146. ELSEVIER. ISSN: 0167-9473 . Google Scholar

49) Molina-Valero, J.A., Ginzo-Villamayor, M.J., Novo Pérez, M.A., Álvarez-González, J.G., Montes-Pita, F., Martínez Calvo, Adela, Pérez-Cruzado, C. (2021) . FORTLS: an R Package for Processing TLS data and Estimating Stand Variables in Forest Inventories Environmental Sciences Proceedings 3(38). pp. 1-9. MDPI. . Google Scholar

50) Blair, G., R. Basset, Bastin, L., Beevers, L., Borrajo, M.I. (2021) . The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord Patterns ISSN: 26663899 . Google Scholar

51) Crujeiras, R.M., Saavedra-Nieves, P. (2021) . "Comments on: Recent advances in directional statistics". TESTpp. 1-4. . Google Scholar

52) Conde Amboage M., Van Keilegom, I., González-Manteiga, W. (2021) . A new lack-of-fit test for quantile regression with censored data Scandinavian Journal of Statistics 48. pp. 655-688. Wiley-Blackwell Publishing, Inc. ISSN: 0303-6898 . Google Scholar

53) Saavedra Nieves, A., Saavedra-Nieves, P. (2021) . IndexNumber: An R Package for Measuring the Evolution of Magnitudes R Journal 13. pp. 253-275. . Google Scholar

54) Proverbio, D., Kemp, F., Magni, S., Husch, A., Aalto, A., Mombaerts, L., Skupin, A., Gonçalves, J., Ameijeiras-Alonso, J., Ley, C. (2021) . Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks PLoS ONE 16 (5). pp. 1-21. Public Library of Science. ISSN: 1932-6203 . Google Scholar

55) Domingues, T.D., Grabowska, A.D., Lee, J.-S., Ameijeiras-Alonso, J., Westermeier, F., Scheibenbogen, C., Cliff, J.M., Nacul, L., Lacerda, E.M., Mouriño, H., Sepúlveda, N. (2021) . Herpesviruses serology distinguishes different subgroups of patients from the United Kingdom Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Biobank Frontiers in Medicine 8. pp. 959-970. ISSN: 2296-858X . Google Scholar

56) Saavedra-Nieves, P., Crujeiras, R.M. (2021) . Nonparametric estimation of directional highest density regions Advances in Data Analysis and Classification DOI: 10.1007/s11634-021-00457-4. . Google Scholar

57) Saavedra-Nieves, P., Saavedra Nieves, A. (2021) . On gender perspective in Statistics and Operations Research BEIO 37(2). pp. 148-164. ISSN: 2387-1725 . Google Scholar

58) Rodríguez-Casal, A., Saavedra-Nieves, P. (2021) . "Spatial distribution of invasive species: an extent of ocurrence approach". TESTDOI: 10.1007/s11749-021-00783-x. . Google Scholar

59) Borrajo, M.I., Comas, C., Costafreda-Aumedes, S., Mateu, J. (2021) . Stochastic smoothing of point processes for wildlife-vehicle collisions on road networks Stochastic Environmental Research and Risk Assessment ISSN: 1436-3240 . Google Scholar

60) García-Portugués, Eduardo, Navarro-Esteban, P., Cuesta-Albertos, JA (2021) . A Cramér–von Mises test of uniformity on the hypersphere Statistical Learning and Modeling in Data Analysispp. 107–116. Springer. . Google Scholar

61) Oviedo, M, Cabo, C., Ordóñez Galán, C., Roca Pardiñas, Javier (2021) . A Distance Correlation Approach for Optimum Multiscale Selection in 3D Point Cloud Classification Mathematics 9. pp. 1-19. MDPI. ISSN: 2227-7390 . Google Scholar

62) Pewsey, A., García-Portugués, Eduardo (2021) . Recent advances in directional statistics TEST 30. pp. 1-58. Springer. ISSN: 1133-0686 . Google Scholar

63) García-Portugués, Eduardo, Paindaveine, D., Verdebout, T. (2020) . On optimal tests for rotational symmetry against new classes of hyperspherical distributions Journal of the American Statistical Association 115. pp. 1873–1887. Amer Statistical Assoc. ISSN: 0162-1459 . Google Scholar

64) Borrajo, M.I., González-Manteiga, W., Martínez-Miranda, M.D. (2020) . Testing for significant differences between two spatial patterns using covariates Spatial StatisticsElsevier. ISSN: 2211-6753 . Google Scholar

65) Meilán-Vila, A., Opsomer, J., Francisco-Fernández, M., Crujeiras, R.M. (2020) . A goodness-of-fit test for regression models with spatially correlated errors Test 29. pp. 728-749. Springer. ISSN: 1133-0686 . Google Scholar

66) Borrajo, M.I., González-Manteiga, W., Martínez-Miranda, M.D. (2020) . Bootstrapping kernel intensity estimation for imhomogeneous poit processes with spatial covariates Computational Statistics and Data Analysis ISSN: 0167-9473 . Google Scholar

67) Saavedra Nieves, A., Saavedra-Nieves, P. (2020) . On systems of quotas from bankruptcy perspective: the sampling estimation of the random arrival rule European Journal of Operational Research 285. pp. 655-669. Elsevier. ISSN: 0377-2217 . Google Scholar

68) Oviedo, M, Ordóñez Galán, C., Roca Pardiñas, Javier (2020) . Functional Location-Scale Model to Forecast Bivariate Pollution Episodes Mathematics 8. pp. 1-12. MDPI. ISSN: 2227-7390 . Google Scholar

69) Meilán-Vila, A., Francisco-Fernández, M., Crujeiras, R.M., Panzera, A. (2020) . Nonparametric multiple regression estimation for circular response Testpp. 1-23. . Google Scholar

70) Meilán-Vila, A., Crujeiras, R.M., Francisco-Fernández, M. (2020) . Nonparametric estimation of circular trend surfaces with application to wave directions Stochastic Environmental Research and Risk Assessmentpp. 1-17. Springer. ISSN: 1436-3240 . Google Scholar

71) Rodríguez-Casal, A., Saavedra-Nieves, P. (2020) . "Estimación non paramétrica de rexións de elevada densidade do COVID-19". Díxitos Outubro 2020. pp. 12-13. FUNDACIÓN CESGA. ISSN: 1139-563X . Google Scholar

72) Macho Stadler, M., Padrón Fernández, E., Calaza Díaz, L., Casanellas Rius, M., Conde Amboage M., Lorenzo García, E., Vázquez-Abal, M.E. (2020) . Igualdad de género en el ámbito de las Matemáticas Libro Blanco de las Matemáticas (Ed.: Martín de Diego, D.; Chacón Rebollo, T; Curbera Costello, G.; Marcellán Español, F.; Siles Molina, M.))pp. 375-420. Fundación Ramón Areces. Dep. Legal: M-24906-2020. . Google Scholar

73) Calaza Díaz, L., Conde Amboage M. (2020) . Prexuízos, ideas preconcibidas, estereotipos e linguaxe non inclusiva: o papel da coeducación Boletín de la SGAPEIO (Informest) 56. pp. 3-5. SGAPEIO. ISSN: 1695-7083 . Google Scholar

74) García-Portugués, Eduardo, Álvarez-Liébana, J., Álvarez-Pérez, G., González-Manteiga, W. (2020) . Goodness-of-fit tests for functional linear models based on integrated projections Functional and High-Dimensional Statistics and Related Fieldspp. 107-114. Springer. . Google Scholar

75) Oviedo, M, Cabo, C., Ordoñez, C., Roca Pardiñas, Javier (2020) . Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation Functional and High-Dimensional Statistics and Related Fields. IWFOS 2020. Contributions to Statistics. Springer, ChamAneiros G., Horová I., Hušková M., Vieu P. (eds) . . Google Scholar

76) García-Portugués, Eduardo, Sørensen, M., Mardia, K.V., Hamelryck, T. (2019) . Langevin diffusions on the torus: estimation and applications Statistics and Computing 29. pp. 1-22. Springer. ISSN: 0960-3174 . Google Scholar

77) Conde Amboage M., Sánchez Sellero, C. (2019) . A plug-in bandwidth selector for nonparametric quantile regression TEST 28. pp. 423-450. Springer. ISSN: 1133-0686 . Google Scholar

78) Cuesta-Albertos, JA, García-Portugués, Eduardo, Febrero-Bande, M., González-Manteiga, W. (2019) . Goodness-of-fit tests for the functional linear model based on randomly projected empirical processes Annals of Statistics 47, Nº 1. pp. 439-467. IMS. ISSN: 0090-5364 . Google Scholar

79) Ameijeiras-Alonso, J., Lagona, F., Ranalli, M., Crujeiras, R.M. (2019) . A circular hidden Markov random field for the spatial segmentation of fire occurrence Environmetrics 30. pp. e2501. John Wiley & Sons Ltd . ISSN: 1180-4009 . Google Scholar

80) Ameijeiras-Alonso, J., Crujeiras, R.M., Rodríguez-Casal, A. (2019) . Mode testing, critical bandwidth and excess mass Test 28. pp. 900-919. Springer. ISSN: 1133-0686 . Google Scholar

81) Febrero-Bande, M., González-Manteiga, W., Oviedo, M (2019) . Variable selection in Functional Additive Regression Models Computational Statistics 34. pp. 469-487. Springer. ISSN: 0943-4062 . Google Scholar

82) Ameijeiras-Alonso, J., Benali, A., Crujeiras, R.M., Rodríguez-Casal, A., Pereira, J. M. C. (2019) . Fire seasonality identification with multimodality tests Annals of Applied Statistics 13. pp. 2120-2139. ISSN: 1932-6157 . Google Scholar

83) Oviedo, M(2019) . O paquete fda.usc Boletín de la SGAPEIO (Informest) 53. pp. 5-6. SGAPEIO. ISSN: 1695-7083 . Google Scholar

84) Faraldo Roca, Pedro, Crujeiras, R.M., Martínez Calvo, Adela, Lombardía, M. J., Naya Fernández, Salvador, Matías, J.M., Fernández de Castro, Belén M., Carreira V. (2019) . Estudo da inserción laboral dos titulados no Sistema Universitario de Galicia 2013-2014 (EIL1314)pp. 24. Axencia para a Calidade do Sistema Universitario de Galicia (ACSUG). . Google Scholar

85) Oviedo, M, Febrero-Bande, M., Muñoz, MP, Domínguez, A. (2018) . Predicting seasonal influenza transmission using functional regression models with temporal dependence PloS One 13 (4). pp. 1-18. Public Library of Science. ISSN: 1932-6203 . Google Scholar

86) Fuentes-Santos, I., González-Manteiga, W., Mateu, J. (2018) . A first-order ratio based nonparametric separability test for spatiotemporal point processes Environmetrics 29 (1). pp. e2482. John Wiley & Sons Ltd . ISSN: 1180-4009 . Google Scholar

87) Fanjul Hevia, A., González-Manteiga, W. (2018) . A comparative study of methods for testing the equality of two or more ROC curves Computational Statistics 33. pp. 357-377. Springer Berlin Heidelberg. ISSN: 0943-4062 . Google Scholar

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CoDyNP is organized in four workpackages (WP), which are intimately interrelated, namely WP1. Complex data, WP2. Nonparametric inference, WP3. Software and WP4. Data application. The first two WPs (which comprise 4 and 3 research lines, respectively) gather the methodological objectives and some of them are joint objectives, but primarily assigned to the line where more challenges are expected. Responsibilities of PI and Co-PI will be organized by research line for WP1 and WP2, facilitating the exchange of experience between these WPs. The PI will be also the coordinator of WP3 and WP4.



Research lines in WP1. Complex data are organized according to data nature (which can be obviously combined and interrelated): incomplete (including biased, truncated and/or censored data, as well as missing data; L1.1) and aggregated data; functional and high-dimensional data (L1.2); directional data (with circular, cylindrical and toroidal data as particular/derived cases; L1.3); and spatio-temporal processes (L1.4). The PI will be responsible of L1.3 and L1.4 and the Co-PI will coordinate L1.1 and L1.2.

The second package, WP2. Nonparametric inference is set up by three research lines devoted to set estimation (L2.1; responsible PI); methods beyond mean regression (L2.2; responsible PI) and correlation distance (L2.3; responsible Co-PI).

Within WP3. Software, we aim to update and improve our R packages related to the research lines in WP1 and WP2, namely alphahull and alphahull3d for set estimation; NPCirc for circular data; DOvalidation for incomplete and aggregated data; multimode for multimodality tests, fda.usc for functional data and the more recent (HDiR) for directional highest density regions. We also aim to produce at least a package on quantile regression (BwQuant) and another one on ROC comparisons.

Regarding WP4. Data application, we will describe some areas of application within ongoing collaborations with other groups (COVID-19, medical imaging, genetics, environmental sciences, ecology, security, linguistics) all of them directly related with areas of intervention in Pillar 2 of Horizon Europe (and subsequently, with the Estrategia Española de Ciencia, Tecnología e Innovación).



Keywords: Nonparametric inference, functional data, directional data, modal regression, quantile regression, incomplete data, specification tests, set estimation, spatial processes.

Beyond all the technical challenges that the big data era brought about, in terms of data storage and data management capacity, the design and implementation of new approaches to data analysis and inference has inevitably drawn the attention of statistical research groups working on the interface between statistics and machine learning, devoted to the design and implementation of statistical tools for handling high dimensional data.

However, dealing with huge amounts of data is not the only problem that we, as statisticians, must confront in order to effectively extract information from data. Data are not only big, but complex; and complexity arises not only by their nature, but also by the dynamics they follow. Our proposal, Complex dynamics and nonparametric inference (CoDyNP) aims to provide nonparametric tools for understanding data evolution, dependence and relations (dynamics) in non-standard settings (incomplete and aggregated, functional, directional and spatio-temporal data). CoDyNP is structured in four workpackages, whose design enable us to continue exploiting our capacities and know-how in different areas (e.g. functional or directional data analysis) as well as exploring new methodologies and applications contexts (e.g. correlation distance methods, modal regression or network structures).

CoDyNP is organized in four workpackages.

  • The first one considers research lines associated to the complexity of the data nature (and this lines can be obviously combined and interrelated): incomplete (including biased, truncated and/or censored data, as well as missing data; L1.1) and aggregated data; functional and high-dimensional data (L1.2); directional data (with circular, cylindrical and toroidal data as particular/derived cases; L1.3); and spatio-temporal processes (L1.4).
  • The second package, WP2. Nonparametric inference is set up by three research lines devoted to set estimation (L2.1); methods beyond mean regression (L2.2) and correlation distance (L2.3).
  • Within WP3. Software, we aim to update and improve our R packages related to the research lines in WP1 and WP2, namely alphahull and alphahull3d for set estimation; NPCirc for circular data; DOvalidation for incomplete and aggregated data; multimode for multimodality tests, fda.usc for functional data and the more recent (HDiR) for directional high density regions. We also aim to produce at least a package on quantile regression (BwQuant) and another one on ROC comparisons.
  • Regarding WP4. Data application, we will describe some areas of application within ongoing collaborations with other groups (COVID-19, medical imaging, genetics, environmental sciences, ecology, security, linguistics) all of them directly related with areas of intervention in Pillar 2 of Horizon Europe (and subsequently, with the Estrategia Española de Ciencia, Tecnología e Innovación).

This project is a continuation from MTM2016-76969-P (Innpar2D), more details in http://eio.usc.es/pub/innpar2d/.



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