2026 Christopher K. Wikle: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	51	1007	859	466	372	198	12798
Engineering and Technology	52	3562	3410	1047	958	180	12742

Christopher K. Wikle 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 Christopher K. Wikle sits on this spectrum.

42 publications 537+

This scientist: 198 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Christopher K. Wikle 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 Christopher K. Wikle sits on this spectrum.

30 D-Index 86+

This scientist: 51 D-Index — 73rd percentile

73% 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

2004 - Fellow of the American Statistical Association (ASA)

Overview

Christopher K. Wikle is a researcher affiliated with the University of Missouri in the United States. Their work spans a range of topics primarily in environmental science and computer science, focusing on the intersection of statistical methods and complex spatial and spatiotemporal data.

The scientist has contributed significantly to the fields of environmental science, with 53 publications, and computer science, with 49 publications. Their research incorporates several subfields, including artificial intelligence, global and planetary change, environmental engineering, economics and econometrics, and ecology.

Their main research topics include:

Gaussian Processes and Bayesian Inference
Neural Networks and Applications
Model Reduction and Neural Networks
Atmospheric and Environmental Gas Dynamics
Demographic Modeling and Climate Adaptation
Time Series Analysis and Forecasting
Meteorological Phenomena and Simulations

Christopher K. Wikle has published several recent papers, including:

"Statistical Deep Learning for Spatial and Spatiotemporal Data," 2023, Annual Review of Statistics and Its Application
"An Illustration of Model Agnostic Explainability Methods Applied to Environmental Data," 2022, Environmetrics

Other influential papers among their recent works, although authored by different leading researchers in the field, are frequently referenced along with their own, reflecting the broader scientific context they operate within. These include:

"The ASA President's Task Force Statement on Statistical Significance and Replicability," 2021, The Annals of Applied Statistics
"Statistical Implementations of Agent-Based Demographic Models," 2020, International Statistical Review
"Ecological Dynamics: Integrating Empirical, Statistical, and Analytical Methods," 2020, Trends in Ecology & Evolution

Their frequent publication venues are diverse, with a high number of publications in:

arXiv (Cornell University)
Environmetrics
Spatial Statistics
The Annals of Applied Statistics
Journal of Agricultural Biological and Environmental Statistics

Christopher K. Wikle has collaborated extensively with a number of researchers, notably including Erin M. Schliep, Scott H. Holan, Joshua S. North, Ranadeep Daw, and Jonathan R. Bradley.

In recognition of their contributions in statistics, they were named a Fellow of the American Statistical Association in 2004.

Best Publications

Statistics for Spatio-Temporal Data

Noel A. C. Cressie;Christopher K. Wikle

2551
Citations
Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Noel Cressie;Catherine A. Calder;James S. Clark;Jay M. Ver Hoef

672
Citations
A dimension-reduced approach to space-time Kalman filtering

Christopher Wikle;Noel A Cressie

578
Citations
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes

Christopher K. Wikle

576
Citations
A Bayesian tutorial for data assimilation

Christopher K. Wikle;L. Mark Berliner

572
Citations
Hierarchical Bayesian space-time models

Christopher Wikle;L M Berliner;Noel A Cressie

553
Citations
Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds

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

464
Citations
Spatio-Temporal Statistics with R

Christopher K. Wikle;Andrew Zammit-Mangion;Noel Cressie

338
Citations
Hierarchical Models in Environmental Science

Christopher K. Wikle

321
Citations
Multiresolution models for nonstationary spatial covariance functions

Douglas Nychka;Christopher Wikle;J Andrew Royle

280
Citations
Understanding the Ensemble Kalman Filter

Matthias Katzfuss;Jonathan R. Stroud;Christopher K. Wikle

252
Citations
A general science-based framework for dynamical spatio-temporal models

Christopher K. Wikle;Mevin B. Hooten

238
Citations
Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling

L. Mark Berliner;Christopher K. Wikle;Noel Cressie

218
Citations
A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

Mevin B. Hooten;Christopher K. Wikle

171
Citations
Low-Rank Representations for Spatial Processes

Christopher K. Wikle

171
Citations
A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities

Ke Xu;Christopher K Wikle;Neil I Fox

131
Citations
A kernel-based spectral model for non-Gaussian spatio-temporal processes:

Christopher K Wikle

128
Citations
Space-time Kalman filter

Noel A Cressie;Christopher K Wikle

121
Citations
Population Influences on Tornado Reports in the United States

Christopher J. Anderson;Christopher K. Wikle;Qin Zhou;J. Andrew Royle

121
Citations
Combining Information Across Spatial Scales

Christopher K Wikle;L. Mark Berliner

120
Citations
Modeling Hydrologic Change: Statistical Methods

Christopher K Wikle

17
Citations

Frequent Co-Authors

Noel A Cressie University of Wollongong

Mevin B. Hooten The University of Texas at Austin

J. Andrew Royle United States Geological Survey

Joshua J. Millspaugh University of Montana

Douglas Nychka Colorado School of Mines

Håvard Rue King Abdullah University of Science and Technology

Nadia Pinardi University of Bologna

Tsing-Chang Chen Iowa State University

Andrew M. Moore University of California, Santa Cruz

Thomas M. Powell University of California, Berkeley

External Links

Personal website of Christopher K. Wikle

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