There are 182 publications.

1) 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

2) 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

3) 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

4) 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

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

6) Febrero-Bande, M., Oviedo, M, Darbalaei, M., Morteza, A. (2024 (online)) . Functional regression models with functional response: a new approach and a comparative study Computational StatisticsSpringer. . Google Scholar

7) 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

8) 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

9) 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

10) 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

11) 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

12) 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

13) 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

14) 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

15) 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

16) 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

17) 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

18) 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

19) 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

20) 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

21) 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

22) 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

23) 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

24) 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

25) 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

26) 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

27) 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

28) 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

29) 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

30) 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

31) 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

32) 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

33) 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

34) 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

35) 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

36) 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

37) 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

38) 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

39) 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

40) 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

41) 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

42) 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

43) 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

44) 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

45) 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

46) 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

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

48) 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

49) 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

50) 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

51) 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

52) 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

53) 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

54) 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

55) 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

56) 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

57) 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

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

59) 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

60) 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

61) 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

62) 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

63) 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

64) 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

65) 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

66) 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

67) 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

68) 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

69) 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

70) 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

71) 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

72) 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

73) 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

74) 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

75) 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

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

77) 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

78) 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

79) 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

80) Ordóñez Galán, C., Oviedo, M, Roca Pardiñas, Javier, Rodríguez-Pérez, J.R. (2018) . Determining optimum wavelengths for leaf water content estimation from reflectance: A distance correlation approach Chemometrics and Intelligent Laboratory Systems 173. pp. 41-50. Elsevier. ISSN: 0169-7439 . Google Scholar

81) Oliveira, M., Pérez-Alberti, Augusto, Crujeiras, R.M., Rodríguez-Casal, A., Castillo-Rodríguez, F. (2018) . A new method for analysing and representing ground temperature variations in cold environments. The Fuegian Andes, Tierra del Fuego, Argentina Geographical Research Letters 44. pp. 293-320. . Google Scholar

82) Luca, Oviedo, M, Torner, N., Martínez, A., Jané M (2018) . Real-time predictive seasonal influenza model in Catalonia, Spain PLoS One 13(3). pp. 1-15 . Public Library of Science. ISSN: 1932-6203 . Google Scholar

83) García-Portugués, Eduardo, Crujeiras, R.M., González-Manteiga, W. (2018) . "Smoothing-Based Tests with Directional Random Variables". Studies in Systems, Decision and Control. The Mathematics of the Uncertain A Tribute to Pedro Gil 142. pp. 175-184. Springer. . Google Scholar

84) Jordà, J.P., Ameijeiras-Alonso, J., Pujadas-Mora, J.M. (2018) . Chronicle of an early demise, surname extinction in the fifteenth and the seventeenth centuries Historical Methods: A Journal of Quantitative and Interdisciplinary History 51. pp. 190-201. Taylor and Francis Group. . Google Scholar

85) Conde Amboage M., González-Manteiga, W., Sánchez Sellero, C. (2018) . Quantile regression: estimation and lack-of-fit tests Boletín de Estadística e Investigación Operativa (BEIO) 32. pp. 97-116. SEIO. ISSN: 2387-1725 . Google Scholar

86) Ameijeiras-Alonso, J., Crujeiras, R.M., Rodríguez-Casal, A. (2018) . Directional statistics for wildfires Applied Directional Statistics: Modern Methods and Case StudiesCRC Press. . Google Scholar

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Innpar2D is divided in two blocks: a first block focused on methodological developments and a second one devoted to exploratory methods, software implementation and practical applications.

B1. Nonparametric inference: modelling, estimation and testing

L1. Random effects models

L2. Structured models

L3. Quantile regression

L4. Functional and high dimensional data

L5. Directional data

L6. Incomplete data

L7. Spatial and spatio-temporal processes

L8. Set estimation


B2. Exploratory methods, software and applications.

Software development and implementation. Innpar2D researchers develop and maintain R packages (https://cran.r-project.org/) including their current advances. In http://eio.usc.es/pub/innpar2d/index.php/en/software-e a description of the packages can be found.

Applications. Innpar2D is conceived with a relevant practical scope, with applications in actuarial sciences, recommending systems, epidemiology, environmental sciences, ecology, biomedicine, geolinguistics or proteomics.



Nonparametric inference, dependence, high dimension, directional data, incomplete data, set estimation. The advances in nonparametric inference on curves have provided answers to applied problems in medicine, biology, economics or environmental sciences, among other fields. In all these contexts, data recording mechanisms have evolved in such a way that the current scenario shows huge amounts of data (“Big data”). These data usually come from stochastic systems (DGS: data generating system) which may be described as complex, understading as “complex systems” those DGSs whose response or design is far from the classical inferential setting (real and independent observations, as the simplest case). We may distinguish DGSs which are complex because of the data nature: functional or high dimensional data, directional data, imcomplete data (missing, censored, truncated), images or sets. Or DGSs which are complex due to underlying structures and dynamics: spatial and/or temporal dependent data; DGSs which are modelled through “complex” regressión with random effects, structured or quantile models. Or in general, any combination of non-standard data (even from combined nature, such as directional and high dimensional, for instance) and complex dynamics.

Innpar2D is born with the aim of obtaining methodological advances which allow to describe and characterize the behaviour of complex DGSs. The project is structured in two blocks: (B1) nonparametric inference and (B2) exploratory methods, software and applications. Working methodology is focused on theoretical developments, validation through simulation studies, software and exploratory methods production (and their disposal for the scientific community) and the consideration of practical problems in fields such as medicine, environmental sciences, actuarial sciences and lingüistics.

The research group for Innpar2D has been designed with the goal of keeping the excelence levels reached in recent years, with an active dissemination of research results; training young researchers and strengthening the relation with bussinesses and industry, with new collaborations for technology transfer. Our scientific foregoing guarantees the success of this new proposal.

This proyect is a continuation from MTM2013-41383-P (Innpar), more details in http://eio.usc.es/pub/innpar/.



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