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Mathematics

D-Index
31
Citations
3974
World Ranking
3344
National Ranking
1314

Overview

Victor H. Lachos is affiliated with the University of Connecticut in the United States. Their research primarily focuses on the field of Mathematics, with a significant emphasis on Statistics and Probability. Their scholarly work extends into subfields such as Artificial Intelligence, Statistics, Probability and Uncertainty, Global and Planetary Change, and Economics and Econometrics.

The research topics explored by Victor H. Lachos include:

  • Statistical Methods and Bayesian Inference
  • Statistical Distribution Estimation and Applications
  • Bayesian Methods and Mixture Models
  • Statistical Methods and Inference
  • Probabilistic and Robust Engineering Design
  • Hydrology and Drought Analysis
  • Advanced Statistical Methods and Models

Victor H. Lachos has contributed to various publication venues, with frequent appearances in the following journals and platforms:

  • arXiv (Cornell University)
  • Statistics in Medicine
  • Journal of Multivariate Analysis
  • Brazilian Journal of Probability and Statistics
  • Journal of Applied Statistics

Some of their recent research papers are:

  • "Skew-normal Linear Mixed Models," 2021, Journal of Data Science
  • "On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions," 2021, Journal of Computational and Graphical Statistics
  • "Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution," 2021, Journal of Multivariate Analysis
  • "Logistic Quantile Regression for Bounded Outcomes Using a Family of Heavy-Tailed Distributions," 2020, Sankhya B
  • "On moments of folded and truncated multivariate Student-t distributions based on recurrence relations," 2021, Metrika

Their frequent coauthors include:

  • Larissa A. Matos
  • Christian E. Galarza
  • Marcos O. Prates
  • Dipak K. Dey
  • Luis M. Castro

Best Publications

  • Skew-normal Linear Mixed Models

    R. B. Arellano-Valle;H. Bolfarine;V. H. Lachos

  • LIKELIHOOD BASED INFERENCE FOR SKEW-NORMAL INDEPENDENT LINEAR MIXED MODELS

    Victor H. Lachos;Pulak Ghosh;Reinaldo B. Arellano-Valle

  • Multivariate mixture modeling using skew-normal independent distributions

    Celso RôMulo Barbosa Cabral;VíCtor Hugo Lachos;Marcos O. Prates

  • Robust mixture modeling based on scale mixtures of skew-normal distributions

    Rodrigo M. Basso;Víctor H. Lachos;Celso Rômulo Barbosa Cabral;Pulak Ghosh

  • On estimation and influence diagnostics for zero-inflated negative binomial regression models

    Aldo M. Garay;Elizabeth M. Hashimoto;Edwin M. M. Ortega;Víctor H. Lachos

  • Bayesian Inference for Skew-normal Linear Mixed Models

    R.B. Arellano-Valle;H. Bolfarine;V.H. Lachos

  • mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions

    Marcos Oliveira Prates;Victor Hugo Lachos;Celso Rômulo Barbosa Cabral

  • Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

    C. A. Abanto-Valle;D. Bandyopadhyay;V. H. Lachos;I. Enriquez

  • Linear and Nonlinear Mixed-Effects Models for Censored HIV Viral Loads Using Normal/Independent Distributions

    Victor H. Lachos;Dipankar Bandyopadhyay;Dipak K. Dey

  • A nonlinear regression model with skew-normal errors

    Vicente G. Cancho;Víctor H. Lachos;Edwin M. M. Ortega

  • Skew scale mixtures of normal distributions: Properties and estimation

    Clécio da Silva Ferreira;Heleno Bolfarine;Víctor H. Lachos

  • Skew normal measurement error models

    R. B. Arellano-Valle;S. Ozan;H. Bolfarine;V. H. Lachos

  • Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

    Victor H. Lachos;Dipak K. Dey;Vicente G. Cancho

  • Likelihood-Based Inference for Multivariate Skew-Normal Regression Models

    Víctor H. Lachos;Heleno Bolfarine;Reinaldo B. Arellano-Valle;Lourdes C. Montenegro

  • Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

    Vicente G. Cancho;Dipak K. Dey;Victor H. Lachos;Marinho G. Andrade

  • Augmented mixed beta regression models for periodontal proportion data

    Diana M. Galvis;Dipankar Bandyopadhyay;Victor H. Lachos

  • Likelihood-based Inference For Mixed-effects Models With Censored Response Using The Multivariate-t Distribution

    Larissa A. Matos;Marcos O. Prates;Ming-Hui Chen;Victor H. Lachos

  • Robust mixture regression modeling based on scale mixtures of skew-normal distributions

    Camila B. Zeller;Celso R. B. Cabral;Victor Hugo Lachos

  • Linear censored regression models with scale mixtures of normal distributions

    Aldo M. Garay;Victor H. Lachos;Heleno Bolfarine;Celso R. B. Cabral

  • Bayesian analysis of skew-normal independent linear mixed models with heterogeneity in the random-effects population

    Celso Rômulo Barbosa Cabral;Víctor Hugo Lachos;Maria Regina Madruga

  • Heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions.

    Victor H. Lachos;Dipankar Bandyopadhyay;Aldo M. Garay

  • mixsmsn: Fitting Finite Mixture of Scale Mixture of Skew-Normal Distributions

    MO Prates;Crb Cabral;VH Lachos

Frequent Co-Authors

Heleno Bolfarine
Heleno Bolfarine Universidade de São Paulo
Dipak K. Dey
Dipak K. Dey University of Connecticut
Edwin M. M. Ortega
Edwin M. M. Ortega Universidade de São Paulo
Ming-Hui Chen
Ming-Hui Chen University of Connecticut
Narayanaswamy Balakrishnan
Narayanaswamy Balakrishnan McMaster University

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