Curriculum Vitae.pdf

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Among the most popular articles published in the last three years (2022-2025) at JMVA:  #137

Among the most cited articles published  in the last three years (2022-2024) at JCGS: #127

List of Publications (Updated: March 31th, 2025)

Packages for R

  1. mixsmsn: Fitting finite mixture of scale mixture of skew-normal distributions (2010)
  2. tlmec: Linear Student-t Mixed-Effects Models with Censored Data (2011)
  3. nlsmsn: Fitting univariate non-linear scale mixture of skew-normal regression models. (2012)
  4. CensRegMod: Fitting Normal and Student-t censored regression models. (2012)
  5. SMNCensReg: Fitting univariate censored regression model under the scale mixture of normal distributions. (2013)
  6. ALDqr: Quantile Regression Using Asymmetric Laplace Distribution. (2013)
  7. BayesCR: Bayesian analysis of censored linear regression models with scale mixtures of normal (SMN) distributions (2013)
  8. qrLMM: Quantile Regression for Linear Mixed-Effects Models (2015)
  9. ald: The Asymmetric Laplace Distribution (2015)
  10. CensMixReg.pdf: Censored Linear Mixture Regression Models (2015)
  11. lqr: Robust Linear Quantile Regression (2016)
  12. FMsmsnReg: Regression Models with Finite Mixtures of Skew Heavy-Tailed Errors (2016)
  13. ARCensReg: Fitting Univariate Censored Linear Regression Model with Autoregressive Errors (2016)
  14. CensSpatial: Censored Spatial Models (2016)
  15. MomTrunc: Moments of Folded and Doubly Truncated Multivariate Distributions (2018)
  16. PartCensReg: Partially Censored Regression Models Based on Heavy-Tailed Distributions (2018)
  17. StempCens: Spatio-Temporal Estimation and Prediction for Censored/Missing Responses (2019)
  18. CensMFM: Finite Mixture of Multivariate Censored/Missing Data (2019)
  19. skewlmm: Scale Mixture of Skew-Normal Linear Mixed Models (2020)
  20. OBASpatial: Objective Bayesian Analysis for Spatial Regression Models (2020)

Submitted/in Progress

  1. R. Retnam, S. Srivastava, D. Bandyopadhyay, and V.H. Lachos (2024). A divide-and-conquer EM algorithm for large non-Gaussian longitudinal data with irregular follow-ups (In Progress).
  2. Fusheng Yang and V.H. Lachos (2024). Comparison of Zero-Inflated and Hurdle INAR(1) Processes for Modeling Count Data (In progress).
  3. Galarza, C. and Lachos, V.H. (2024). Finite mixture modeling of censored and missing data using the multivariate skew-t distribution (In progress).
  4. D.C.R. Oliveira, D. Liu & V.H. Lachos (2024). The use of the EM algorithm for regularization problems in high-dimensional censored linear mixed-effects models (In progress).
  5. Fabio, L., Carrasco, J., Lachos, V.H. and Chen, M-H (2024). Likelihood-based inference for joint modeling of correlated count and binary outcomes with extra variability and zeros (Submitted).
  6. Lachos, V.H. (2025). Multivariate Contaminated Skew-Normal Censored Model: Properties and Maximum Likelihood Inference (In progress).
  7. Diniz, C. and Lachos, V.H. (2025). Finite mixtures of matrix variate generalized asymmetric Laplace distribution for three-way data. (Submitted).
  8. Diniz, C. Jogwoo Choi and Lachos, V.H. (2025). An EM algorithm for fitting matrix-variate Student’s-t distributions on interval-censored and missing data. (Submitted).
  9. Lim, H., Lachos, E.V. and Lachos V.H. (2025). Bayesian analysis of flexible Heckman-selection models using Hamiltonian Monte Carlo. (Submitted)
  10. Brisilda Nbreka, D. Dey and  Lachos, V.H. (2025). Quantifying homophily through skewed link functions in Bayesian network models: Estimating peer influence ( Submitted).
  11. Brisilda Nbreka, D. Dey and  Lachos, V.H. (2025). Bayesian Estimation of Contagion Effect: An Application of Friendship Networks and Alcohol Behavior (Submitted).