Institutos Universitarios

Nirian Martín Apaolaza

Titular de Universidad (Associate Professor)
Department of Financial and Actuarial Economics & Statistics
Faculty of Commerce and Tourism
Complutense University of Madrid
Procedimientos Inferenciales basados en Divergencias

 

 

 

Bio

Associate Professor (Profesora Titular de Universidad) 2019 - Present. Complutense University of Madrid - UCM Madrid, Spain. Department of Financial and Actuarial Economics & Statistics, Faculty of Commerce and Tourism.

Visiting Professor 2019, 6 months. McMaster University Hamilton (ON), Canada. Department of Mathematics & Statistics, Faculty of Science.

Associate Professor (Profesora Contratada Doctora) 2018 - 2019. Complutense University of Madrid - UCM Madrid, Spain. Department of Financial and Actuarial Economics & Statistics, Faculty of Commerce and Tourism.

Associate Professor (Profesora Contratada Doctora) 2015 - 2018. Complutense University of Madrid - UCM Madrid, Spain. Department of Statistics and Operations Research II (Decision Methods), Faculty of Commerce and Tourism.

Guest Researcher 2011, 2 months. McMaster University Hamilton (ON), Canada. Department of Mathematics & Statistics, Faculty of Science.

Assistant Professor (Profesora Visitante) 2009 - 2015. Carlos III University of Madrid - UC3M Getafe (Madrid), Spain. Department of Statistics, Faculty of Social Sciences and Law.

Visiting Scientist 2008-2009, 11 months. Harvard University and Dana Farber Cancer Institute Boston (MA), United States. Departments of Biostatistics and Biostatistics & Computational Biology, Harvard School of Public Health and Dana Farber Cancer Institute.

Teaching Assistant (Profesora Ayudante) 2005-2009. Complutense University of Madrid - UCM Madrid, Spain. Department of Statistics and Operations Research III, School of Statistics.

Predoctoral Fellow of the Basque Government 2003-2005. Complutense University of Madrid - UCM Madrid, Spain. Department of Statistics and Operations Research I, Faculty of Mathematics.

 

Research interests

Categorical Data Analysis, Generalized Linear Models, Change Points, Empirical Likelihood, High Dimensional Data, Order Restricted Statistical Inference, Overdispersion Models, Regression Diagnostics, Robust Statistics.

 

Latest Publications

  • Á. Felipe, P. Miranda, N. Martín. Phi-divergence Test Statistics Applied to Latent Class Models for Binary Data. In Trends in Mathematical, Information and Data Sciences, 2023, 445, pp. 223–231. https://doi.org/10.1007/978-3-031-04137-2_20
  • N. Balakrishnan, E. CastillaN. MartinL. Pardo. Power divergence approach for one-shot device testing under competing risks. Journal of Computational and Applied Mathematics, 2023, 419. https://doi.org/10.1016/j.cam.2022.114676
  • N. Martín Apaolaza, El quincunx, un juego de azar de museoBoletín del IMINº45 (21 de abril de 2022), Sección "1+400. Divulgación con 1 imagen y 400 palabras". Link
  • E. Castilla, N. Martín, L. Pardo. Testing linear hypotheses in logistic regression analysis with complex sample survey data based on phi-divergence measures. Communications in Statistics - Theory and Methods. 2021, 50, 22, 5228-5247. https://doi.org/10.1080/03610926.2020.1746342
  • E. Castilla, A. Ghosh, N. Martín, L. Pardo. Robust semiparametric inference for polytomous logistic regression with complex survey design. Advances in Data Analysis and Classification. 2021, 15, 701 – 734. https://doi.org/10.1007/s11634-020-00430-7
  • L. Pardo, N. Martín. Robust Procedures for Estimating and Testing in the Framework of Divergence Measures. Entropy. 2021, 23(4):430. https://doi.org/10.3390/e23040430
  • A. Basu, A. Ghosh, N. Martín, L. Pardo. A Robust Generalization of the Rao Test. Journal of Business and Economic Statistics. 2021. https://doi.org/10.1080/07350015.2021.1876711
  • A. Calviño, N. Martín, L. Pardo. Robustness of Minimum Density Power Divergence Estimators and Wald-type test statistics in loglinear models with multinomial sampling. Journal of Computational and Applied Mathematics. 2021, 386, Article number 113214. https://doi.org/10.1016/j.cam.2020.113214
  • N. Balakrishnan, E. Castilla, N. Martin, L. Pardo. Divergence-Based Robust Inference Under Proportional Hazards Model for One-Shot Device Life-Test. IEEE Transactions on Reliability. 2021, 70, 4, 1355-1367https://doi.org/10.1109/TR.2021.3062289
  • E. Castilla, N. Martín, L. Pardo, K. Zografos. Model Selection in a Composite Likelihood Framework Based on Density Power Divergence. Entropy. 2020, 22(3), 270. https://doi.org/10.3390/e22030270
  • A. Basu, A. Ghosh, A. Mandal, N. Martin, L. Pardo. Robust Wald-type tests in GLM with random design based on minimum density power divergence estimators. Statistical Methods & Applications. 2020. https://doi.org/10.1007/s10260-020-00544-4
  • J. M. Alonso-Revenga, N. Martín, L. Pardo. New statistics to test log-linear modeling hypothesis with no distributional specifications and clusters with homogeneous correlation. Journal of Computational and Applied Mathematics. 374, 112757. https://doi.org/10.1016/j.cam.2020.112757
  • E. Castilla, N. Martın, L. Pardo. Testing linear hypotheses in logistic regression analysis with complex sample survey data based on phi-divergence measures. Communications in Statistics - Theory and Methods. 2020. https://doi.org/10.1080/03610926.2020.1746342
  • N. Balakrishnan, E. Castilla, N. Martín, L. Pardo. Robust Inference for One-Shot Device Testing Data Under Weibull Lifetime Model. IEEE TRANSACTIONS ON RELIABILITY. 2020, 
  • E. Castilla, N. Martín, S. Muñoz, L. Pardo. Robust Wald-type tests based on minimum Rényi pseudodistance estimators for the multiple linear regression model. Journal of Statistical Computation and Simulation. 2020, 90, 14. https://doi.org/10.1080/00949655.2020.1787410
  • N. Balakrishnan, E. Castilla, N. Martín, L. Pardo. Robust inference for one-shot device testing data under
    exponential lifetime model with multiple stresses. Qual Reliab Engng Int. 2020, 1–15. https://doi.org/10.1002/qre.2665