Efficient Monte Carlo Methods for Conditional Logistic Regression

By Cyrus R. Mehta, Nitin R. Patel, Pralay Senchaudhuri. 2000

116 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6c3fab0e26d8a2945dedbdbefbd2eca05e600012

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jonathan E. Taylor
2. William Fithian
3. Robert Tibshirani
4. Jun Sakuma
5. Shohei Kawasaki
6. Yoshiji Yamada
7. David duVerle
8. Koji Tsuda

In Statistics and Probability

1. Jonathan E. Taylor
2. William Fithian
3. Robert Tibshirani
4. Dennis L. Sun
5. Jun Sakuma
6. Shohei Kawasaki
7. Yoshiji Yamada
8. David duVerle

Citations in the corpus

• Optimal Inference After Model Selection (2014, background): “For further references on Monte Carlo inference see Besag and Clifford (1989); Forster et al. (1996); Mehta et al. (2000).”
• Privacy-Preserving Statistical Analysis by Exact Logistic Regression (2015, methodology): “Nevertheless, it can be achieved using Markov chain Monte Carlo methods [16], [15], [17].”