World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
46
Citations
16751
World Ranking
1314
National Ranking
587

Research.com Recognitions

  • 1999 - Fellow of the American Statistical Association (ASA)

Overview

Michael L. Stein is affiliated with Rutgers, The State University of New Jersey in the United States. Their research primarily focuses on environmental science, with notable contributions to global and planetary change, environmental engineering, and atmospheric science. They have also worked in finance and artificial intelligence as applied to environmental contexts.

The scientist has explored major topics including climate variability and models, hydrology and drought analysis, soil geostatistics and mapping, Gaussian processes and Bayesian inference, financial risk and volatility modeling, meteorological phenomena and simulations, and atmospheric and environmental gas dynamics.

Recent papers by Michael L. Stein and collaborators provide insight into their research scope. Titles include:

  • Neural networks for parameter estimation in intractable models (2023, Computational Statistics & Data Analysis)
  • A parametric model for distributions with flexible behavior in both tails (2020, Environmetrics)
  • The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate (2020, Journal of Geophysical Research Atmospheres)
  • Parametric models for distributions when interest is in extremes with an application to daily temperature (2020, Extremes)
  • Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails (2022, Weather and Climate Extremes)

Frequent co-authors of Michael L. Stein include:

  • Christopher J. Geoga
  • Julie Bessac
  • Mitchell Krock
  • Adam H. Monahan
  • Mihai Anitescu

Publishing venues where Michael L. Stein regularly contributes include:

  • arXiv (Cornell University)
  • Environmetrics
  • Extremes
  • Journal of the American Statistical Association
  • Statistics and Computing

Michael L. Stein was recognized as a Fellow of the American Statistical Association in 1999. This distinction is a formal acknowledgment within the statistical community.

Best Publications

  • Interpolation of Spatial Data: Some Theory for Kriging

    Michael Leonard Stein

  • Interpolation of Spatial Data

    Michael L. Stein

  • Large sample properties of simulations using latin hypercube sampling

    Michael Stein

  • A Bayesian analysis of kriging

    Mark S. Handcock;Michael L. Stein

  • Space–Time Covariance Functions

    Michael L Stein

  • Approximating likelihoods for large spatial data sets

    Michael L. Stein;Zhiyi Chi;Leah J. Welty

  • Spatial sampling design for prediction with estimated parameters

    Zhengyuan Zhu;Michael L. Stein

  • Limitations on low rank approximations for covariance matrices of spatial data

    Michael L. Stein

  • Asymptotically Efficient Prediction of a Random Field with a Misspecified Covariance Function

    Michael L. Stein

  • A general method for validating statistical downscaling methods under future climate change

    M. Vrac;M. L. Stein;K. Hayhoe;K. Hayhoe;X.-Z. Liang

  • Nonstationary covariance models for global data

    Mikyoung Jun;Michael L. Stein

  • Estimating and choosing

    Michael Stein

  • Statistical emulation of climate model projections based on precomputed GCM runs

    Stefano Castruccio;David J. McInerney;Michael L. Stein;Feifei Liu Crouch

  • Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing

    M. Vrac;M. Stein;K. Hayhoe

  • An Approach to Producing Space–Time Covariance Functions on Spheres

    Mikyoung Jun;Michael L Stein

  • Fast and Exact Simulation of Fractional Brownian Surfaces

    Michael L Stein

  • A modeling approach for large spatial datasets

    Michael L. Stein

  • Spatial variation of total column ozone on a global scale

    Michael L. Stein

  • Spatial sampling design for parameter estimation of the covariance function

    Zhengyuan Zhu;Michael L. Stein

  • Uniform Asymptotic Optimality of Linear Predictions of a Random Field Using an Incorrect Second-Order Structure

    Michael Stein

  • The screening effect in Kriging

    Michael L. Stein

  • The Analysis of Directional Time Series: Applications to Wind Speed and Direction

    Michael Stein

Frequent Co-Authors

Mihai Anitescu
Mihai Anitescu Argonne National Laboratory
David J. Schwab
David J. Schwab Michigan Technological University
Dmitry Beletsky
Dmitry Beletsky University of Michigan–Ann Arbor
Donald J. Wuebbles
Donald J. Wuebbles University of Illinois at Urbana-Champaign
Ying Sun
Ying Sun King Abdullah University of Science and Technology
Mark S. Handcock
Mark S. Handcock University of California, Los Angeles
Jon Brinkmann
Jon Brinkmann New Mexico State University
Donald G. York
Donald G. York University of Chicago
Edward B. Jenkins
Edward B. Jenkins Princeton University
Brian Yanny
Brian Yanny Fermilab

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