World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
36
Citations
18399
World Ranking
2565
National Ranking
42

Genshiro Kitagawa 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 Genshiro Kitagawa 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: 160 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Genshiro Kitagawa 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 Genshiro Kitagawa 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

  • 2000 - Fellow of the American Statistical Association (ASA)

Overview

Genshiro Kitagawa is affiliated with the University of Tokyo in Japan. Their research spans across the fields of Computer Science and Economics, Econometrics and Finance, focusing on several subfields including Artificial Intelligence, Economics and Econometrics, Signal Processing, General Economics, Econometrics and Finance, and Management Science and Operations Research.

Their work covers a range of topics such as Complex Systems and Time Series Analysis, Time Series Analysis and Forecasting, Monetary Policy and Economic Impact, Market Dynamics and Volatility, Economic Theory and Policy, Stock Market Forecasting Methods, and Forecasting Techniques and Applications.

Kitagawa has contributed papers to various prominent publication venues. These include:

  • arXiv (Cornell University) with 8 publications
  • Journal of Business Cycle Research with 2 publications
  • Asian Journal of Management Science and Applications with 1 publication

Selected recent papers authored or co-authored by Kitagawa include:

  • "A Moving Linear Model Approach for Extracting Cyclical Variation from Time Series Data" (2023), published in the Journal of Business Cycle Research
  • "Co-movement of Cyclical Components Approach to Construct a Coincident Index of Business Cycles" (2022), published in the Journal of Business Cycle Research
  • "Hyper-trend method for seasonal adjustment and trend-cycle decomposition of time series containing long-period cycles" (2021), published in the Asian Journal of Management Science and Applications
  • "Pearson chi^2-divergence Approach to Gaussian Mixture Reduction and its Application to Gaussian-sum Filter and Smoother" (2020), published in arXiv (Cornell University)
  • "An implimentation of the Differential Filter for Computing Gradient and Hessian of the Log-likelihood of Nonstationary Time Series Models" (2022), published in arXiv (Cornell University)

Frequent co-authors include:

  • Koki Kyo
  • Hideo Noda
  • Yoko Tanokura
  • Seisho Sato

Throughout their career, Kitagawa has worked extensively on topics that integrate statistical and computational methods with economic data analysis, particularly focusing on time series models and forecasting techniques. The research contributions also explore the cyclical behavior of economic indicators and methods for improving seasonal adjustments and decomposition of time series data.

Recognition received by Kitagawa includes the designation as a Fellow of the American Statistical Association (ASA) awarded in 2000.

Best Publications

  • Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models

    Genshiro Kitagawa

  • Akaike Information Criterion Statistics

    Y. Sakamoto;G. Kitagawa

  • Akaike Information Criterion Statistics

    Dan Grove;Y. Sakamoto;M. Ishiguro;G. Kitagawa

  • Non-Gaussian State—Space Modeling of Nonstationary Time Series

    Genshiro Kitagawa

  • Information Criteria and Statistical Modeling

    Sadanori Konishi;Genshiro Kitagawa

  • Smoothness priors analysis of time series

    Genshiro Kitagawa;Will Gersch

  • Generalised information criteria in model selection

    Sadanori Konishi;Genshiro Kitagawa

  • A self-organizing state-space model

    Genshiro Kitagawa

  • A Smoothness Priors–State Space Modeling of Time Series with Trend and Seasonality

    Genshiro Kitagawa;Will Gersch

  • Selected papers of Hirotugu Akaike

    Emanuel Parzen;Kunio Tanabe;Genshiro Kitagawa

  • A smoothness priors time-varying AR coefficient modeling of nonstationary covariance time series

    G. Kitagawa;W. Gersch

  • A procedure for the modeling of non-stationary time series

    Genshiro Kitagawa;Hirotugu Akaike

  • Introduction to Time Series Modeling

    Genshiro Kitagawa

  • A NONSTATIONARY TIME SERIES MODEL AND ITS FITTING BY A RECURSIVE FILTER

    Genshiro Kitagawa

  • Theory and Methods

    Genshiro Kitagawa

  • Bootstrapping Log Likelihood and EIC, an Extension of AIC

    Makio Ishiguro;Yosiyuki Sakamoto;Genshiro Kitagawa

  • The two-filter formula for smoothing and an implementation of the Gaussian-sum smoother

    Genshiro Kitagawa

  • A new efficient procedure for the estimation of onset times of seismic waves.

    Tetsuo Takanami;Genshiro Kitagawa

  • The Prediction of Time Series With Trends and Seasonalities

    Will Gersch;Genshiro Kitagawa

  • ESTIMATION OF THE ARRIVAL TIMES OF SEISMIC WAVES BY MULTIVARIATE TIME SERIES MODEL

    Tetsuo Takanami;Genshiro Kitagawa

  • Non-Gaussian state-space modeling of nonstationary time series. Comment. Rejoinder

    G. Kitagawa;R. Kohn;C. F. Ansley;R. D. Martin

Frequent Co-Authors

Hirotugu Akaike
Hirotugu Akaike The Graduate University for Advanced Studies, SOKENDAI
Alan T. Linde
Alan T. Linde Carnegie Institution for Science
Dimitris A. Pados
Dimitris A. Pados Florida Atlantic University
Xiaohong Chen
Xiaohong Chen Central South University

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