Book

• Vallejos, R., Osorio, F., Bevilacqua, M. (2020). Spatial Relationships Between Two Georeferenced Variables: With Applications in R . Springer, Cham.
     

Publications

19. Ogueda, A., Osorio, F. (2025). Influence diagnostics for ridge regression using the Kullback-Leibler divergence. Statistical Papers 66, 85.
       
18. Acosta, J., Vallejos, R., Ellison, A. M., Osorio, F., de Castro, M. (2024). Comparing two spatial variables with the probability of agreement. Biometrics 80 (1), ujae009.
         
17. Osorio, F., Gárate, Á., Russo, C.M. (2024). The gradient test statistic for outlier detection in generalized estimating equations. Statistics & Probability Letters 209, 110087.
         
16. Osorio, F., Galea, M., Henríquez, C., Arellano-Valle, R. (2023). Addressing non-normality in multivariate analysis using the t-distribution. AStA Advances in Statistical Analysis 107, 785-813.
         
15. Osorio, F., Vallejos, R., Barraza, W., Ojeda, S.M., Landi, M.A. (2022). Statistical estimation of the structural similarity index for image quality assessment. Signal, Image and Video Processing 16, 1035-1042.
           
14. Vidal, G., Yuz, J., Vallejos, R., Osorio, F. (2022). Point-process modeling and divergence measures applied to the characterization of passenger flow patterns of a metro system. IEEE Access 10, 26529-26540.
     
13. Acosta, J., Alegría, A., Osorio, F., Vallejos, R. (2021). Assessing the effective sample size for large spatial datasets: A block likelihood approach. Computational Statistics & Data Analysis 162, 107282.
     
12. Crudu, F., Osorio, F. (2020). Bilinear form test statistics for extremum estimation Economics Letters 187, 108885.
         
11. Leal, C., Galea, M., Osorio, F. (2019). Assessment of local influence for the analysis of agreement. Biometrical Journal 61 (4), 955-972.
         
10. Acevedo, C., Tomic, G., Santander, R., Creixell, W., Osorio, F., Sánchez, E. (2016). A Chemometrics approach to analysis volatile molecules released by post-mortem bovine fast-twitch muscles. CyTA - Journal of Food 14 (3), 399-404.
    
9. Acosta, J., Osorio, F., Vallejos, R. (2016). Effective sample size for line transect sampling models with an application to marine macroalgae. Journal of Agricultural, Biological, and Environmental Statistics 21 (3), 407-425.
    
8. Osorio, F. (2016). Influence diagnostics for robust P-splines using scale mixture of normal distributions. Annals of the Institute of Statistical Mathematics 68 (3), 589-619.
      
7. Vallejos, R., Osorio, F., Mancilla, D. (2015). The codispersion map: a graphical tool to visualize the association between two spatial variables. Statistica Neerlandica 69 (3), 298-314.
    
6. Vallejos, R., Osorio, F. (2014). Effective sample size of spatial process models. Spatial Statistics 9, 66-92.
      
5. Meza, C., Osorio, F., De la Cruz, R. (2012). Estimation in nonlinear mixed-effects models using heavy-tailed distributions. Statistics and Computing 22 (1), 121-139.
    
4. Osorio, F., Paula, G.A., Galea, M. (2009). On estimation and influence diagnostics for the Grubbs' model under heavy-tailed distributions. Computational Statistics & Data Analysis 53 (4), 1249-1263.
    
3. Cademartori, D., Navia, R., Galea, M., Osorio, F. (2008). Prediction of the economic activity from the short and long-term interest rate differential: New evidences in Chile and the United States of America cases. Applied Economics Letters 15 (9), 707-712.
   
2. Osorio, F., Paula, G.A., Galea, M. (2007). Assessment of local influence in elliptical linear models with longitudinal structure. Computational Statistics & Data Analysis 51 (9), 4354-4368.
    
1. Osorio, F., Galea, M. (2006). Detection of a change-point in Student-t linear regression models. Statistical Papers 47 (1), 31-38.
    

Submitted Papers

• Gárate, Á., Osorio, F., Crudu, F. An invariant modification of the bilinear form test.
• Jaques, A., Schwarzenberg, C., Osorio, F., Kohnenkamp, E., Veliz, M., Aracena, A. Best practices in kinetic parameter estimation via regression in ore leaching processes.
• Vallejos, R., Osorio, F., Ferrer, C. A new coefficient to measure agreement between continuous variables.
  
• Vallejos, R., Osorio, F., Vidal, S., Britos, G. Optimized imaging prefiltering for enhanced image segmentation.
  

Work in Preparation

• Avello, P., Tapia, A., Osorio, F., Galea, M. Local influence in ordinary differential equation models.
• Bazurto, Z., Osorio, F., Galarza, C., Galea, M. Assessing influence in generalized linear models based on maximum Lq-likelihood estimation.
• Osorio, F., Galea, M., Giménez, P. A robust approach for generalized linear models based on maximum Lq-likelihood procedure.
  
• Osorio, F., Galea, M., Palacios, F. Agreement assessment between two measurement systems using robust P-splines.
• Osorio, F., Tapia, A. An EM-based approach for influence diagnostics in LAD regression.
• Osorio, F., Tapia, A., Liu, S. Assessment of local influence in LAD regression.
• Tapia, A., Giampaoli, V., Osorio, F., Morales, B., Mendez-Bustos, P. Novel approaches for validating ordinal regression models and their applications to the study of suicidal behavior.

arXiv Preprint

• Osorio, F., Vallejos, R., Cuevas, F. (2016). SpatialPack: Computing the association between two spatial processes.
   

Conference Proceedings

2. Osorio, F. (2011). Smoothing parameter selection and outliers accommodation for smoothing splines. In Proceedings of the 58th World Statistics Congress of the International Statistical Institute, Dublin, Ireland. Session CPS008, 6037-6042.
1. De la Cruz, R., Eyheramendy, S., Meza, C., Osorio, F. (2010). Exact estimation procedures in a spatial mixed-effects probit model with binary outcomes. In JSM Proceedings , Statistical Computing Section. Alexandria, VA: American Statistical Association. 3629-3637.

Theses

• Osorio, F. (2006). Influence Diagnostics in Elliptical Mixed-Effects Models. (in Portuguese) Unpublished Doctoral Thesis. Department of Statistics, University of São Paulo, Brazil.
   
• Osorio, F. (2000). Change-point detection in linear regression models with t-independent errors. (in Spanish) Statistical Engineering degree. Department of Statistics, Universidad de Valparaíso, Chile.

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