World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
31
Citations
3974
World Ranking
3345
National Ranking
1314

Victor H. Lachos publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Victor H. Lachos sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 174 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Victor H. Lachos D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Victor H. Lachos sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 31 D-Index — 9th percentile

9% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

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
Francisco Louzada
Francisco Louzada Universidade de São Paulo
Ming-Hui Chen
Ming-Hui Chen University of Connecticut
Narayanaswamy Balakrishnan
Narayanaswamy Balakrishnan McMaster University

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