Efficiency and Convergence Properties of Slice Samplers

By Antonietta Mira, L. Tierney. 2002

96 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1aec49e5724db19dd5b32fc8c78d4e33d1f818cd

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. Mark A. Girolami
2. Theodore Papamarkou
3. James M. Flegal
4. Antonietta Mira
5. Chris J. Oates
6. Galin L. Jones
7. Murali Haran
8. Gareth O. Roberts

In Statistics and Probability

1. Mark A. Girolami
2. Theodore Papamarkou
3. Galin L. Jones
4. James M. Flegal
5. Antonietta Mira
6. Chris J. Oates
7. Murali Haran
8. R. Neath

Citations in the corpus

• Zero variance Markov chain Monte Carlo for Bayesian estimators (2010, background): “These modifications have been achieved in many different ways, for example by trying to induce negative correlation along the chain path ([6,21,13,41,12]); by trying to avoid random walk behavior via successive over-relaxation ([1,36,7]); by hybrid Monte Carlo ([16,35,10,18,27]); by exploiting non r”
• Perfect slice samplers (2001, background): “Perfect product slice sampling The product slice sampler (Besag and Green, 1993; Damien and Walker, 1999; Edwards and Sokal, 1988; Mira and Tierney, 2001; Roberts and Rosenthal, 1999; Swendsen and Wang, 1987) is an extension of the simple slice sampler where more than one auxiliary variable is intro”
• Markov chain Monte Carlo: Can we trust the third significant figure? (2007, background): “Marchev and Hobert (2004), Mira and Tierney (2002) , Robert (1995), Roberts and”
• Zero Variance Differential Geometric Markov Chain Monte Carlo Algorithms (2014, methodology): “…Carlo (Duane et al. (1987), Fort et al. (2003)), use of Riemann sums (Philippe and Robert (2001)) or of auxiliary variables (Swendsen andWang (1987), Mira and Tierney (2002)), exploitation of non reversible Markov chains (Diaconis et al. (2000), Geyer and Mira (2000)) and data augmentation…”
• On the Markov chain central limit theorem (2004, background): “Also, M ira and Tierney (2002) and Robertsand Rosenthal(1999)worked with slice sam plers.”
• Fixed-Width Output Analysis for Markov Chain Monte Carlo (2006, background): “For example, Hobert and Geyer (1998), Hobert, Jones, Presnell, and Rosenthal (2002), Jones and Hobert (2004), Marchev and Hobert (2004), Mira and Tierney (2002), Robert (1995), Roberts and Polson (1994), Roberts and Rosenthal (1999), Rosenthal (1995, 1996), and Tierney (1994) examined Gibbs…”