Andrea Riebler

Statistics and Probability · 2014–2018

A researcher in the Science corpus: 6 papers; trusts 47 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 95 citations into it; #8,870 of 12,932 by trust here, #5,481 by citations
• Artificial Intelligence — 51 citations into it; #11,943 of 35,345 by trust here, #14,718 by citations
• Economics and Econometrics — 32 citations into it
• Environmental Engineering — 30 citations into it
• Global and Planetary Change — 13 citations into it
• Management Science and Operations Research — 10 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Applied Mathematics — 8 citations into it

Whom Andrea Riebler trusts overall

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

1. Håvard Rue
2. Tilmann Gneiting
3. Daniel P. Simpson
4. Leonhard Held
5. David J. Spiegelhalter
6. Finn Lindgren
7. N. G. Best
8. Adrian E. Raftery
9. David J. Lunn
10. Paul Gustafson

Who trusts Andrea Riebler overall

1. Håvard Rue
2. H. Bakka
3. Daniel P. Simpson
4. Sigrunn Holbek Sørbye
5. Thomas Opitz
6. Finn Lindgren
7. Jonathan Koh
8. Geir-Arne Fuglstad
9. Sean Talts
10. J. Illian

Papers from Andrea Riebler's perspective

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

1. Spatial Interaction and the Statistical Analysis of Lattice Systems
2. Bayesian measures of model complexity and fit
3. Sampling-Based Approaches to Calculating Marginal Densities
4. Gaussian Markov Random Fields: Theory and Applications
5. Generalized Linear Models
6. Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
7. Bayesianly Justifiable and Relevant Frequency Calculations for the Applied Statistician
8. Hierarchical Modeling and Analysis for Spatial Data
9. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
10. Strictly Proper Scoring Rules, Prediction, and Estimation

Their papers

• Bayesian Computing with INLA: A Review (2016) — 746 citations
• An intuitive Bayesian spatial model for disease mapping that accounts for scaling (2016) — 496 citations
• Bayesian analysis of measurement error models using integrated nested Laplace approximations (2015) — 107 citations
• Spatial modelling with R-INLA: A review (2018) — 401 citations
• Projecting the future burden of cancer: Bayesian age–period–cohort analysis with integrated nested Laplace approximations (2017) — 510 citations
• Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors (2014) — 1,120 citations