John W. Staudenmayer

Statistics and Probability · 2004–2011

A researcher in the Science corpus: 6 papers; trusts 16 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

Whom John W. Staudenmayer trusts overall

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

  1. David Ruppert
  2. Aurore Delaigle
  3. Robert Fildes
  4. Frank Hampel
  5. Jonathan Lester
  6. A. Meister
  7. Matt P. Wand
  8. Scott M. Berry
  9. William S. Cleveland
  10. Raymond J. Carroll

Who trusts John W. Staudenmayer overall

  1. Anthony R. Ives
  2. J. Hadfield
  3. Vasilis Dakos
  4. David Ruppert
  5. Matt P. Wand
  6. Emily Lei Kang
  7. John P. Buonaccorsi
  8. Tim Bollerslev

Papers from John W. Staudenmayer's perspective

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

  1. Spline Models for Observational Data
  2. Nonparametric regression with errors in variables
  3. Bayesian Smoothing and Regression Splines for Measurement Error Problems
  4. Kernel Smoothing
  5. Inference from Iterative Simulation Using Multiple Sequences
  6. Local polynomial modelling and its applications
  7. Estimation of integrated squared density derivatives from a contaminated sample
  8. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
  9. A Hybrid Discriminative/Generative Approach for Modeling Human Activities (International Joint Conference on Artificial Intelligence)
  10. Robust Locally Weighted Regression and Smoothing Scatterplots

Their papers