Jonathan R. Bradley
Statistics and Probability · 2017
A researcher in the Science corpus: 1 paper; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 19 citations into it; #10,319 of 12,932 by trust here, #12,077 by citations
- Artificial Intelligence — 7 citations into it; #28,215 of 35,345 by trust here, #34,213 by citations
- Environmental Engineering — 7 citations into it
- Economics and Econometrics — 5 citations into it
Whom Jonathan R. Bradley trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eric R. Ziegel
- Noel Cressie
- Andrew Gelman
- Sudipto Banerjee
- D. Nychka
- Stu Daultrey
- Emily Lei Kang
- David L. Donoho
- Persi Diaconis
- Ming-Hui Chen
Who trusts Jonathan R. Bradley overall
Papers from Jonathan R. Bradley's perspective
Ordered by how strongly the researchers Jonathan R. Bradley trusts endorse each paper. Same corpus, a different order for every researcher.
- Spline Models for Observational Data
- Hierarchical Modeling and Analysis for Spatial Data
- Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
- Gaussian predictive process models for large spatial data sets (Journal of The Royal Statistical Society Series B-statistical Methodology)
- Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
- Model‐based geostatistics
- Sampling-Based Approaches to Calculating Marginal Densities
- The Elements of Statistical Learning
- Bayesian measures of model complexity and fit
- Statistics for Spatio-Temporal Data