Mark J. Schervish

Statistics and Probability · 1999–2008

A researcher in the Science corpus: 6 papers; trusts 18 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 29 citations into it; #2,127 of 12,932 by trust here, #3,609 by citations
• Artificial Intelligence — 19 citations into it; #5,013 of 35,345 by trust here, #15,004 by citations
• Environmental Engineering — 16 citations into it; #168 of 5,479 by trust here, #1,223 by citations
• Applied Mathematics — 7 citations into it
• Management Science and Operations Research — 6 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Mark J. Schervish trusts overall

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

1. Simon N. Wood
2. Hao Zhang
3. Christopher C. Holmes
4. C. Biller
5. Reinhard Furrer
6. Tilmann Gneiting
7. Christopher J. Paciorek
8. Robert M. Gray
9. D. Higdon
10. Alexandra M. Schmidt

Who trusts Mark J. Schervish overall

1. Mikyoung Jun
2. Taeryon Choi
3. Phillip Boyle
4. Michael L. Stein
5. Huiyan Sang
6. Jaehong Jeong
7. Stephen G. Walker
8. R. Ingebrigtsen
9. Francky Fouedjio
10. Subhashis Ghosal

Papers from Mark J. Schervish's perspective

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

1. Hierarchical Modeling and Analysis for Spatial Data
2. Applied Regression Including Computing and Graphics
3. Nonparametric regression and generalized linear models
4. Compactly Supported Correlation Functions
5. Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
6. Modelling and smoothing parameter estimation with multiple quadratic penalties
7. Bayesian regression with multivariate linear splines
8. Bayesian curve-fitting with free-knot splines
9. Covariance Tapering for Interpolation of Large Spatial Datasets
10. Adaptive Bayesian Regression Splines in Semiparametric Generalized Linear Models

Their papers

• On posterior consistency in nonparametric regression problems (2007) — 136 citations
• Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets (2008) — 528 citations
• Spatial modelling using a new class of nonstationary covariance functions (2006) — 533 citations
• Nonstationary Covariance Functions for Gaussian Process Regression (2003) — 433 citations
• Improper regular conditional distributions (2001) — 78 citations
• The consistency of posterior distributions in nonparametric problems (1999)