Andrew O. Finley

Environmental Engineering · 2007–2017

A researcher in the Science corpus: 7 papers; trusts 39 researchers and is trusted by 46 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 66 citations into it; #215 of 5,479 by trust here, #584 by citations
• Statistics and Probability — 38 citations into it; #3,487 of 12,932 by trust here, #3,255 by citations
• Economics and Econometrics — 33 citations into it; #5,650 of 23,481 by trust here, #7,434 by citations
• Nature and Landscape Conservation — 31 citations into it; #578 of 6,941 by trust here, #2,432 by citations
• Artificial Intelligence — 19 citations into it
• Ecology — 16 citations into it; #4,169 of 10,717 by trust here, #7,367 by citations
• Applied Mathematics — 11 citations into it
• Signal Processing — 10 citations into it; #1,273 of 7,572 by trust here, #3,784 by citations

Whom Andrew O. Finley trusts overall

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

1. Alan E. Gelfand
2. Michael L. Stein
3. Sudipto Banerjee
4. Noel Cressie
5. C. Chatfield
6. Hector Franco-Lopez
7. D. Higdon
8. Håvard Rue
9. Andy Liaw
10. A. R. Stage

Who trusts Andrew O. Finley overall

1. Hooman Latifi
2. Petteri Packalen
3. Johannes Breidenbach
4. Noel Cressie
5. Arne Nothdurft
6. Gérard Biau
7. Alexander Kowarik
8. Emily Lei Kang
9. Ronald E. McRoberts
10. Barbara Koch

Papers from Andrew O. Finley's perspective

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

1. Hierarchical Modeling and Analysis for Spatial Data
2. Interpolation of spatial data
3. Bayesian measures of model complexity and fit
4. Spatial modelling using a new class of nonstationary covariance functions (Environmetrics)
5. Gaussian Markov Random Fields: Theory and Applications
6. Covariance Tapering for Interpolation of Large Spatial Datasets
7. Non-Stationary Spatial Modeling
8. Smoothing Spline Anova Models
9. Fixed-domain asymptotic properties of tapered maximum likelihood estimators
10. Space and Space-Time Modeling using Process Convolutions

Their papers

• Gaussian predictive process models for large spatial data sets (2008) — 1,128 citations
• A Case Study Competition Among Methods for Analyzing Large Spatial Data (2017) — 458 citations
• Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations (2017) — 60 citations
• Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets (2014) — 749 citations
• Tropical tree growth is correlated with soil phosphorus, potassium, and calcium, though not for legumes (2012) — 172 citations
• yaImpute: An R Package for kNN Imputation (2008) — 399 citations
• Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery (2007) — 214 citations