Curriculum Vitae

Google Scholar Citation

Web of Science ResearcherID

Among the most popular articles published in the last three years (2021-2024) at JMVA: #116 and #137

Among the most cited articles published  in the last three years (2021-2024) at JCGS: #127

List of Publications (Updated: November 20th, 2024)

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: 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 (In progress).
  6. Diniz, C. and Lachos, V.H. (2024). Finite mixtures of matrix variate generalized asymmetric Laplace distribution for three-way data. (In progress).
  7. Lim, H., Lachos, E.V. and Lachos V.H. (2024). Bayesian analysis of flexible Heckman-selection models using Hamiltonian Monte Carlo. (In progress)
  8. Brisilda Nbreka, D. Dey and  Lachos, V.H. (2024). Quantifying homophily through skewed link functions in Bayesian network models: Estimating peer influence ( Submitted).
  9. Brisilda Nbreka, D. Dey and  Lachos, V.H. (2024). Bayesian Estimation of Contagion Effect: An Application of Friendship Networks and Alcohol Behavior (Submitted).
  10. Lachos, V.H.,  José Alejandro Ordoñez, Heeju Lim and Punzo, A. (2024). Heckman selection – contaminated normal model (Submitted).
  11.  Gil, Yessenia A., Garay, A.W. and Lachos, V.H. (2024). Likelihood-based inference for interval censored regression models under heavy-tailed distributions (Submitted).
  12. Carrasco, J.M., Castillo, L.F. , Dey,  D. and Lachos, V.H. (2024). Variable selection in high-dimensional generalized linear mixed models for correlated binary data (Submitted).