Johnathan M. Bardsley

Statistics and Probability · 2013

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Johnathan M. Bardsley trusts overall

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

  1. Gareth O. Roberts
  2. Omiros Papaspiliopoulos
  3. Yaming Yu
  4. Maurizio Filippone
  5. Andrew M. Stuart
  6. Simon L. Cotter
  7. Yasuhiro Omori
  8. Jeffrey S. Rosenthal

Papers from Johnathan M. Bardsley's perspective

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

  1. Optimal scaling of discrete approximations to Langevin diffusions
  2. Non-Centered Parameterisations for Hierarchical Models and Data Augmentation
  3. Stability of the Gibbs sampler for Bayesian hierarchical models
  4. On inference for partially observed nonlinear diffusion models using the Metropolis–Hastings algorithm
  5. Inverse problems: A Bayesian perspective (Acta Numerica)
  6. Bayesian aspects of some nonparametric problems
  7. Weak convergence and optimal scaling of random walk Metropolis algorithms
  8. Markov Processes: Characterization and Convergence
  9. Non-centred parameterisations for hierarchical models and data augmentation.
  10. To Center or Not to Center: That Is Not the Question—An Ancillarity–Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Efficiency

Their papers