Noel Cressie

Statistics and Probability · 1990–2021

A researcher in the Science corpus: 21 papers; trusts 77 researchers and is trusted by 49 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 54 citations into it; #1,458 of 12,932 by trust here, #2,919 by citations
• Environmental Engineering — 46 citations into it; #178 of 5,479 by trust here, #560 by citations
• Economics and Econometrics — 35 citations into it; #4,423 of 23,481 by trust here, #8,678 by citations
• Artificial Intelligence — 30 citations into it; #28,218 of 35,345 by trust here, #30,347 by citations
• Global and Planetary Change — 25 citations into it
• Probabilistic & Bayesian Methods — 21 citations into it
• Ecology — 16 citations into it; #7,247 of 10,717 by trust here, #10,333 by citations
• Management Science and Operations Research — 11 citations into it

Whom Noel Cressie trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alan E. Gelfand
2. Montserrat Fuentes
3. Sudipto Banerjee
4. Finn Lindgren
5. Håvard Rue
6. Christopher K. Wikle
7. D. Nychka
8. Emily Lei Kang
9. James S. Clark
10. Jay M. Ver Hoef

Who trusts Noel Cressie overall

1. Tomislav Hengl
2. Emily Lei Kang
3. Vladimir G Vovk
4. Aritra Sengupta
5. Finn Lindgren
6. Francky Fouedjio
7. Christopher K. Wikle
8. Tengyuan Liang
9. Han-Lim Choi
10. Jonathan R. Bradley

Papers from Noel Cressie's perspective

Ordered by how strongly the researchers Noel Cressie trusts endorse each paper. Same corpus, a different order for every researcher.

1. Hierarchical Modeling and Analysis for Spatial Data
2. Sampling-Based Approaches to Calculating Marginal Densities
3. Bayesian measures of model complexity and fit
4. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
5. Spatial Interaction and the Statistical Analysis of Lattice Systems
6. Estimating the Dimension of a Model
7. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
8. Gaussian predictive process models for large spatial data sets (Journal of The Royal Statistical Society Series B-statistical Methodology)
9. Gaussian Markov Random Fields: Theory and Applications
10. Interpolation of spatial data

Their papers

• Fixed rank kriging for very large spatial data sets (2008) — 1,099 citations
• Flexible Spatial Models for Kriging and Cokriging Using Moving Averages and the Fast Fourier Transform (FFT) (2004) — 105 citations
• On asymptotic distribution and asymptotic efficiency of least squares estimators of spatial variogram parameters (2002) — 84 citations
• Smoothing regional maps using empirical Bayes predictors (2010) — 48 citations
• The Construction of Multivariate Distributions from Markov Random Fields (2000) — 91 citations
• Bayesian Inference for the Spatial Random Effects Model (2011) — 105 citations
• Using temporal variability to improve spatial mapping with application to satellite data (2010) — 82 citations
• Hierarchical statistical modeling of big spatial datasets using the exponential family of distributions (2013) — 54 citations
• Beyond Moran's I: Testing for Spatial Dependence Based on the Spatial Autoregressive Model (2007) — 509 citations
• Basis-Function Models in Spatial Statistics (2021) — 57 citations
• Correction factors for unbiased, efficient estimation and prediction of biomass from log-log allometric models (2013) — 67 citations
• Statistics for Spatio-Temporal Data (2011) — 825 citations
• Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. (2009) — 569 citations
• Some topics in convolution-based spatial modeling (2007) — 42 citations
• Block Kriging for Lognormal Spatial Processes (2006) — 72 citations
• Size and power considerations for testing loglinear models using divergence test statistics (2003) — 53 citations
• Spatial statistics: Analysis of field experiments (2001) — 47 citations
• Hierarchical Bayesian space-time models (1998)
• Universal cokriging under intrinsic coregionalization (1994)
• 5. Statistics for Spatial Data (1993)