Emily Lei Kang

Statistics and Probability · 2010–2011

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 13 citations into it
• Environmental Engineering — 8 citations into it; #1,622 of 5,479 by trust here, #4,337 by citations
• Economics and Econometrics — 7 citations into it; #9,048 of 23,481 by trust here, #19,308 by citations
• Artificial Intelligence — 6 citations into it
• Global and Planetary Change — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Emily Lei Kang trusts overall

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

1. Noel Cressie
2. Alan E. Gelfand
3. Sudipto Banerjee
4. Andrew Gelman
5. Alexander Shapiro
6. David J. Spiegelhalter
7. G. Jóhannesson
8. Paul Gustafson
9. Hedibert Freitas Lopes
10. Reinhard Furrer

Who trusts Emily Lei Kang overall

1. Aritra Sengupta
2. Noel Cressie
3. Jonathan R. Bradley
4. Scott H. Holan
5. Christopher K. Wikle

Papers from Emily Lei Kang's perspective

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

1. Sampling-Based Approaches to Calculating Marginal Densities
2. Bayesian measures of model complexity and fit
3. Hierarchical Modeling and Analysis for Spatial Data
4. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
5. Spatial dynamic factor analysis
6. Fixed rank kriging for very large spatial data sets
7. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
8. Monte Carlo Sampling Methods Using Markov Chains and Their Applications
9. Conservative prior distributions for variance parameters in hierarchical models
10. Gaussian predictive process models for large spatial data sets (Journal of The Royal Statistical Society Series B-statistical Methodology)

Their papers

• 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