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PUBLICATIONS

“The joy of discovery is certainly the liveliest that the mind of man can ever feel”

- Claude Bernard -

Journal Publications
(Updated: Jul, 17th, 2025)

30. Galarza, C.E., & Lachos, V.H. (2025). Truncated Moments. In: Lovric, M. (ed.) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. DOI:10.1007/978-3-662-69359-9_729.

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29. Tatari, M., Zeraati, H., Yaseri, M., Kasaeian, A., Yazdani, A., Mousavi, S.A., and Galarza, C.E. (2025). Skewed Slash Censored Quantile Regression. Sankhya: The Indian Journal of Statistics, 87-B(1), 292-318.

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28. Oliveira, M., Galarza, C.E., Prates, O.M. and Lachos, V. H. (2025).  Influence diagnostics in Heckman selection models based on EM algorithms. Journal of Applied Statistics. DOI: 10.1080/02664763.2025.2461715.

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27. Ordoñez, J., Galarza, C.E. and Lachos, V. H. (2024). CensSpatial: An R Package for Estimation and Diagnostics in Spatial Censored Regression Models. SoftwareX, Vol 27, 101762.

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26. Valeriano. K.L., Schumacher, F.L., Galarza, C.E. and Matos, L.A. (2024). Censored autoregressive regression models with Student-t innovations. The Canadian Journal of Statistics, 52: 804-828. 

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25. Valeriano, K.L.,  Galarza, C.E., Matos, L.A. and Lachos, V.H. (2023). Likelihood-based inference for multivariate skew-t censored regression with censored or missing responses. Journal of Multivariate Analysis, Vol. 196, 105174.

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24. Valeriano. K.L., Galarza, C.E. and Matos, L.A. (2023). Moments and random number generation for the truncated elliptical family of distributions. Statistics and Computing. DOI: 10.1007/s11222-022-10200-4.

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23. Galarza, C.E., Matos, L.A. and Lachos, V.H. (2022). An EM algorithm for estimating the parameters of the multivariate skew-normal distribution with censored responses. Metron, 80, 231–253. DOI: 10.1007/s40300-021-00227-4.

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22. Galarza, C.E., Lachos, V. H. and Matos, L. A. (2022). Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution. Journal of Multivariate Analysis, (189), 104944.

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21. Ordoñez, J., Galarza, C.E. and Lachos, V. H. (2022). An R package for censored spatial data analysis. Medwave. 22(S1): eCI54. DOI: 10.5867/Medwave.2022.S1.CI54.

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20. Galarza C.E., Matos L.A., Dey D.K. and Lachos V.H. (2022)  On moments of folded and doubly truncated multivariate extended skew-normal distributions. Journal of Computational and Graphical Statistics. DOI: 10.1080/10618600.2021.2000869.

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19. De Alencar F.H, Galarza, C.E.  Matos, L.A. and Lachos V.H. (2021). Finite mixture modeling of censored and missing data using the multivariate skew-normal distribution. Advances and Data Analysis and Classification.  DOI: 10.1007/s11634-021-00448-5.

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18. Galarza C.E., Lachos V.H. and Bourgingnon M. (2021) A skew-t quantile regression for censored and missing data.  STAT.  e379. DOI: 10.1002/sta4.379.

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17. Galarza C.E., Lachos V.H, Tsung-I, L. and Wan-Lun, W. (2021) On moments of folded and truncated multivariate Student-t distributions based on recurrence relations. Metrika, 84, 825–850. DOI: 10.1007/s00184-020-00802-1.

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16. Lemus, M.N., Lachos V.H., Galarza, C.E. and Matos L.A. (2021) Estimation and diagnostics for partially censored regression models based on heavy-tailed distributions. Statistics and Its Interface, 14(2), 165-182.

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15. Gallardo. D., Bourgingnon M., Galarza C.E., and Gómez H. (2020) A parametric quantile regression model for asymmetric response variables on the real line. Symmetry, (12), 1938. 

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14. Galarza C.E., Lachos V.H. and Panpan Z. (2020) Logistic quantile regression for bounded outcomes using a family of heavy-tailed distributions. Sankhya B. DOI: 10.1007/s13571-020-00231-0.

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13. Galarza, C.E., Castro, LM. Louzada, F. and V. H. Lachos (2018) Quantile Regression for Nonlinear Mixed Effects Models: A Likelihood Based Perspective. Statistical Papers. DOI: 10.1007/s00362-018-0988-y.

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12. Galarza, C.E., V. H. Lachos, Cabral, CRB. and Castro L.M. (2017) Robust Quantile Regression using a Generalized Class of Skewed Distributions. Stat. DOI: 10.1002/sta4.140.

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11. Galarza, C.E., Bandyopadhyay, D. and V. H. Lachos (2017) Quantile Regression for Linear Mixed Models: A Stochastic Approximation EM approach. Statistics and its interface. Volume 10(3): 471 – 482.

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10. Gonzalez-López, V.A., Galarza, C.E., Gholizadeh, R. (2016). E-Bayesian Estimation for System Reliability and Availability Analysis based on Exponential Distribution. Communications in Statistics: Simulation and Computation. DOI: 10.1080/03610918.2016.1202269.

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9. Galarza, C.E. and V. H. Lachos (2015) Classical Inference for Quantile Regression Nonlinear Mixed Effects Models. Estadistica (Inter-American Statistical Institute). Vol. 67 N188-189.

Edited Image 2016-05-05 05-51-34_edited_
Collaboratory

8. Morales, N., Valdés-Muñoz, E., González, J., Valenzuela-Hormazábal, P., Palma, J.M., Galarza, C.E., Catagua-González, Á., Yáñez, O., Pereira, A., & Bustos, D. (2024). Machine Learning-Driven Classification of Urease Inhibitors Leveraging Physicochemical Properties as Effective Filter Criteria. International Journal of Molecular Sciences, 25(8), 4303.

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7. Valenzuela-Hormazabal, P., Galarza, C.E., Morales, N., Leddermann, V., Bustos, D., et.al. (2024). Unveiling Novel Urease Inhibitors for Helicobacter pylori: A Multi-Methodological Approach from Virtual Screening and ADME to Molecular Dynamics Simulations. International Journal of Molecular Sciences, 25(4), 1968.

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6. Velastegui, A., Guerrero, G., Marquez, J. O., El Imanni, H. S., Galarza, C.E., and Hidalgo, J. (2023). Geospatial Analysis of Guayaquil’s Sound Landscape After the Covid-19 Isolation Period. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 2504-2507). IEEE.

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5. Yáñez O., Alegría M., Suardiaz R., Morales L., Castro R.I., Palma J.M., Galarza C.E., Catagua A., Rojas V., Urra G., et al. (2023). Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach. Polymers; 15(14):3020.

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4. Bustos, D., Galarza, C.E., Ordoñez, W., Brauchi, S. and Benso, B. (2023). Cost-effective pipeline for a rational design and selection of capsaicin analogs targeting TRPV1 channels. American Chemical Society (ACS) Omega 8, 13, 11736–11749.

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3. Galarza, C.E., Palma, J.M., Morais, C.F., Utria J. and Carvalho, L.P. (2021) A Novel Probabilistic Model for Opportunistic Routing and Applications with Computation of Energy Consumption in WSN. Sensors 21 (23), 8058.

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2. Palma, J.O., De Paula, C.L., Gonçalves, A.C., Galarza, C.E. and De Oliveira, A.M. (2016) Network Control System Application: Minimization of global number of interactions, transmissions and receptions in a Multi-Hop network using Discrete-Time Markovian Jump Linear Systems. IEEE Latin American Transactions 14(6): 2675-2680. DOI: 10.1109/TLA.2016.7555237

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1. Palma, J.O., De Paula, C.L., Gonçalves, A.C., Galarza, C.E. and De Oliveira, A.M. (2015) Application of Control Theory Markov Systems to Minimize the Number of Transmissions in a Multi-hop Network. IEEE Computer Aided System Engineering (APCASE), 2015 Asia-Pacific Conference on. DOI: 10.1109/APCASE.2015.59.

R software packages

  1. HeckmanEM: Fit Normal or Student-t Heckman Selection Models (2023). Prates M., Lachos V.H., Dipak D,  Oliveira M., Galarza, C.M., and Loor, K.
     

  2. RcppCensSpatial: Spatial Estimation and Prediction for Censored/Missing Responses (2021). Loor, K., Ordoñez, A., Galarza, C.M., and Matos, L.A.
     

  3. relliptical: The Truncated Elliptical Family of Distributions (2021). Loor, K., Galarza, C.M., and Matos, L.A.
     

  4. CensMFM: Finite Mixture of Multivariate Censored/Missing Data (2019). De Alencar, H.F., Avila, L., Galarza, C.M. and V. H. Lachos.​
     

  5. MomTrunc: Moments of Folded and Doubly Truncated Multivariate Distributions (2019). Galarza, C.M. and V. H. Lachos.
     

  6. PartCensReg: Partially Censored Regression Models Based on Heavy-Tailed Distributions (2018).  Lemus M.N, Galarza, C.M., Matos, L.A. and V. H. Lachos.
     

  7. Opportunistic: Routing Distribution, Broadcasts, Transmissions and Receptions in an Opportunistic Network (2017).  Galarza, C.M. and Palma, J.O.​
     

  8. CensSpatial: Censored Spatial Models (2016). Ordoñez, A., Galarza, C.M., and V. H. Lachos.​
     

  9. endtoend: Transmissions and Receptions in a End to End  Network (2016). Galarza, C.M. and Palma, J.O.​
     

  10. ARCensReg: Fitting Univariate Censored Linear Regression Model with Autoregressive Errors (2016). Schumacher L. F., Galarza, C.M., and V. H. Lachos.
     

  11. lqr: Robust Linear Quantile Regression (2016). Galarza, C.M., Benites, L. and V. H. Lachos.​
     

  12. hopbyhop: Transmissions and Receptions in a Hop by Hop Network (2016). Galarza, C.M. and Palma, J.O.
     

  13. ald: The Asymmetric Laplace Distribution (2015). Galarza, C.M., and V. H. Lachos.​
     

  14. qrNLMM: Quantile Regression for Nonlinear Mixed-Effects Models (2015). Galarza, C.M., and V. H. Lachos.
     

  15. qrLMM:  Quantile Regression for Linear Mixed-Effects Models (2015). Galarza, C.M., and V. H. Lachos.​
     

  16. ALDqr: Quantile Regression Using Asymmetric Laplace Distribution (2015). Benites, L., Galarza, C.M. and V. H. Lachos

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