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D-Index & Metrics

Mathematics

D-Index
36
Citations
5401
World Ranking
2646
National Ranking
1090

Hira L. Koul 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 Hira L. Koul 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: 150 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Hira L. Koul 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 Hira L. Koul 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: 36 D-Index — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2003 - Fellow of the American Statistical Association (ASA)

Overview

Hira L. Koul is affiliated with Michigan State University in the United States. Their research primarily focuses on the field of Mathematics, with a particular emphasis on Statistics and Probability. Koul's work spans various subfields including Finance, Artificial Intelligence, Statistics, Probability and Uncertainty, as well as Management Science and Operations Research.

Their research topics cover a breadth of statistical methods and inference techniques, advanced statistical models, Bayesian inference, financial risk and volatility modeling, statistical distribution estimation and applications, mixture models, and advanced statistical process monitoring.

Frequent publication venues for Koul's research include:

  • Journal of Time Series Analysis
  • Journal of the Indian Society for Probability and Statistics
  • Journal of Statistical Theory and Practice
  • Journal of Statistical Planning and Inference
  • Metrika

Koul has contributed to several recent papers, which highlight the range of their statistical research:

  • A Minimum Distance Lack-of-Fit Test in a Markovian Multiplicative Error Model (2021, Journal of Statistical Theory and Practice)
  • Weighted empirical minimum distance estimators in linear errors-in-variables regression models (2021, Journal of Statistical Planning and Inference)
  • An R-Estimator in the Errors in Variables Linear Regression Model (2022, Journal of the Indian Society for Probability and Statistics)
  • An analog of Bickel-Rosenblatt test for fitting an error density in the two phase linear regression model (2022, Metrika)
  • Lack-of-fit of a parametric measurement error AR(1) model (2020, Statistics & Probability Letters)

Koul frequently collaborates with several co-authors in their research projects, including:

  • Jiwoong Kim
  • Indeewara Perera
  • Pei Geng
  • N. Balakrishna
  • Fuxia Cheng

In recognition of their contributions to the field, Hira L. Koul was named Fellow of the American Statistical Association (ASA) in 2003.

Best Publications

  • Regression Analysis with Randomly Right-Censored Data

    H. Koul;V. Susarla;J. Van Ryzin

  • Large Sample Inference for Long Memory Processes

    Liudas Giraitis;Hira L. Koul;Donatas Surgailis

  • Weighted Empirical Processes in Dynamic Nonlinear Models

    Hira L. Koul

  • Nonparametric model checks for time series

    Hira L. Koul;Winfried Stute

  • Asymptotic Expansion of the Empirical Process of Long Memory Moving Averages

    Hira L. Koul;Donatas Surgailis

  • Weighted empiricals and linear models

    H. L. Koul

  • Martingale transforms goodness-of-fit tests in regression models

    Estate V. Khmaladze;Hira L. Koul

  • An Estimator of the Scale Parameter for the Rank Analysis of Linear Models under General Score Functions

    H. L. Koul;G. L. Sievers;J. Mckean

  • Asymptotic normality of regression estimators with long memory errors

    Liudas Giraitis;Hira L Koul;Donatas Surgailis

  • Efficient estimation in nonlinear autoregressive time-series models

    Hira L. Koul;Anton Schick

  • Autoregression Quantiles and Related Rank-Scores Processes

    Hira L. Koul;A. K. Md. E. Saleh

  • Weak Convergence of Randomly Weighted Dependent Residual Empiricals with Applications to Autoregression

    Hira L. Koul;Mina Ossiander

  • Asymptotic Behavior of Wilcoxon Type Confidence Regions in Multiple Linear Regression

    Hira Lal Koul

  • A test for new better than used

    Hira L. Koul

  • Asymptotics of R-, MD- and LAD-estimators in linear regression models with long range dependent errors

    Hira L. Koul;Kanchan Mukherjee

  • Minimum distance regression model checking

    Hira L. Koul;Pingping Ni

  • Fitting an Error Distribution in Some Heteroscedastic Time Series Models

    Hira L. Koul;Shiqing Ling

  • Asymptotics of some estimators and sequential residual empiricals in nonlinear time series

    Hira L. Koul

  • M-estimators in linear models with long range dependent errors

    Hira L. Koul

  • Asymptotic expansion of M-estimators with long-memory errors

    Hira L. Koul;Donatas Surgailis

Frequent Co-Authors

Donatas Surgailis
Donatas Surgailis Vilnius University
Liudas Giraitis
Liudas Giraitis Queen Mary University of London
Winfried Stute
Winfried Stute University of Giessen
Pranab Kumar Sen
Pranab Kumar Sen University of North Carolina at Chapel Hill
Lixing Zhu
Lixing Zhu Beijing Normal University
Richard T. Baillie
Richard T. Baillie King's College London
Marc G. Genton
Marc G. Genton King Abdullah University of Science and Technology
Marc Hallin
Marc Hallin Université Libre de Bruxelles
Jianqing Fan
Jianqing Fan Princeton University
Roger Koenker
Roger Koenker University College London

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