Prasenjit Ghosh

Statistics and Probability · 2013

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Prasenjit Ghosh trusts overall

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

  1. James G. Scott
  2. John D. Storey
  3. Artin Armagan
  4. Chris Hans
  5. Michael A. Newton
  6. Malgorzata Bogdan
  7. Nicholas G. Polson
  8. Yoav Benjamini
  9. Tommaso Cai
  10. Jayanta Kumar Ghosh

Papers from Prasenjit Ghosh's perspective

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

  1. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  2. Bayesian lasso regression
  3. The Bayesian Lasso
  4. Computational approaches to motor learning by imitation.
  5. Sparse Bayesian Learning and the Relevan e Ve tor Ma hine
  6. Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction
  7. Regression Shrinkage and Selection via the Lasso
  8. Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses
  9. An exploration of aspects of Bayesian multiple testing
  10. Conservative prior distributions for variance parameters in hierarchical models

Their papers