World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
49
Citations
13833
World Ranking
1121
National Ranking
514

Environmental Sciences

D-Index
45
Citations
11219
World Ranking
6272
National Ranking
2261

Research.com Recognitions

  • 2002 - Fellow of the American Statistical Association (ASA)

Overview

Douglas Nychka is affiliated with the Colorado School of Mines in the United States. Their research primarily focuses on Environmental Science, with significant contributions in Environmental Engineering, Global and Planetary Change, Artificial Intelligence, Economics and Econometrics, and Atmospheric Science.

The central topics in Nychka's work include:

  • Soil Geostatistics and Mapping
  • Remote Sensing and LiDAR Applications
  • Climate Variability and Models
  • Spatial and Panel Data Analysis
  • Meteorological Phenomena and Simulations
  • Atmospheric and Environmental Gas Dynamics
  • Geochemistry and Geologic Mapping

Recent publications by Nychka cover a range of themes and methodologies applied to environmental and statistical modeling. Notable papers include:

  • "30 Years of space-time covariance functions", 2020, Wiley Interdisciplinary Reviews Computational Statistics
  • "Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation", 2020, Environmetrics
  • "Fast parameter estimation of generalized extreme value distribution using neural networks", 2024, Environmetrics
  • "Functional forecasting of dissolved oxygen in high-frequency vertical lake profiles", 2022, Environmetrics
  • "A Gaussian Process Model for Insulin Secretion Reconstruction with Uncertainty Quantification: Applications in Cystic Fibrosis", 2023, SIAM Journal on Applied Mathematics

The scientist frequently collaborates with other researchers, including:

  • Soutir Bandyopadhyay
  • Maggie D. Bailey
  • Manajit Sengupta
  • Ashton Wiens
  • William Kleiber

Douglas Nychka's work is often published in several key venues, including:

  • arXiv (Cornell University)
  • Stat
  • Environmetrics
  • Solar Energy
  • Wiley Interdisciplinary Reviews Computational Statistics

In recognition of contributions to the field, Nychka was named a Fellow of the American Statistical Association (ASA) in 2002.

Best Publications

  • Semi-nonparametric maximum likelihood estimation

    A. Ronald Gallant;Douglas W. Nychka

  • Covariance Tapering for Interpolation of Large Spatial Datasets

    Reinhard Furrer;Marc G Genton;Douglas Nychka

  • Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles

    Claudia Tebaldi;Richard L. Smith;Doug Nychka;Linda O. Mearns

  • Statistical significance of trends and trend differences in layer-average atmospheric temperature time series

    B. D. Santer;T. M. L. Wigley;J. S. Boyle;D. J. Gaffen

  • Bayesian Spatial Modeling of Extreme Precipitation Return Levels

    Daniel Cooley;Douglas Nychka;Philippe Naveau

  • Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets

    Cari G. Kaufman;Mark J. Schervish;Douglas W. Nychka

  • Fitting The Term Structure of Interest Rates With Smoothing Splines

    Mark Fisher;Douglas W. Nychka;David Zervos

  • Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds

    Christopher K Wikle;Ralph F Milliff;Doug Nychka;L Mark Berliner

  • Finding chaos in noisy systems

    Douglas Nychka;Stephen Ellner;A. Ronald Gallant;Daniel McCaffrey

  • Bayesian Confidence Intervals for Smoothing Splines

    Douglas Nychka

  • A Case Study Competition Among Methods for Analyzing Large Spatial Data

    Matthew J. Heaton;Abhirup Datta;Andrew O. Finley;Reinhard Furrer

  • Consistency of modelled and observed temperature trends in the tropical troposphere

    B. D. Santer;P. W. Thorne;L. Haimberger;K. E. Taylor

  • A Multi-resolution Gaussian process model for the analysis of large spatial data sets

    Douglas Nychka;Soutir Bandyopadhyay;Dorit Hammerling;Finn Lindgren

  • A smoothed EM approach to indirect estimation problems, with particular reference to stereology and emission tomography

    B. W. Silverman;M. C. Jones;J. D. Wilson;D. W. Nychka

  • Exploring fitness surfaces

    Dolph Schluter;Douglas Nychka

  • Bayesian Modeling of Uncertainty in Ensembles of Climate Models

    Richard L. Smith;Claudia Tebaldi;Doug Nychka;Linda O. Mearns

  • Multiresolution models for nonstationary spatial covariance functions

    Douglas Nychka;Christopher Wikle;J Andrew Royle

  • Regional probabilities of precipitation change: A Bayesian analysis of multimodel simulations

    C. Tebaldi;L. O. Mearns;D. Nychka;R. L. Smith

  • Spatial analysis to quantify numerical model bias and dependence: How many climate models are there?

    Mikyoung Jun;Reto Knutti;Douglas W Nychka

  • Climate spectra and detecting climate change

    Peter Bloomfield;Douglas Nychka

  • Estimating the Lyapunov Exponent of a Chaotic System with Nonparametric Regression

    Daniel F. McCaffrey;Stephen Ellner;A. Ronald Gallant;Douglas W. Nychka

  • Reliable stereological method for estimating the number of microscopic hepatocellular foci from their transections.

    Thomas D. Pugh;James H. King;Hirofumi Koen;Douglas Nychka

  • The Value of Multiproxy Reconstruction of Past Climate

    Bo Li;Douglas W. Nychka;Caspar M. Ammann

  • Spatial‐Process Estimates as Smoothers

    Douglas W. Nychka

Frequent Co-Authors

Stephen P. Ellner
Stephen P. Ellner Cornell University
A. Ronald Gallant
A. Ronald Gallant Pennsylvania State University
Grace Wahba
Grace Wahba University of Wisconsin–Madison
V. Kerry Smith
V. Kerry Smith Arizona State University
Christopher K. Wikle
Christopher K. Wikle University of Missouri
Bryan T. Grenfell
Bryan T. Grenfell Princeton University
Caspar M. Ammann
Caspar M. Ammann National Center for Atmospheric Research
Gordon B. Bonan
Gordon B. Bonan National Center for Atmospheric Research
Reto Knutti
Reto Knutti ETH Zurich
Gerald A. Meehl
Gerald A. Meehl National Center for Atmospheric Research

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