Griffin, JE;
Latuszynski, KG;
Steel, MFJ;
(2021)
In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p.
BIOMETRIKA
, 108
(1)
pp. 53-69.
10.1093/biomet/asaa055.
Preview |
Text
Griffin_asaa055.pdf - Published Version Download (593kB) | Preview |
| Type: | Article |
|---|---|
| Title: | In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/biomet/asaa055 |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Physical Sciences, Biology, Mathematical & Computational Biology, Statistics & Probability, Life Sciences & Biomedicine - Other Topics, Mathematics, Expected squared jumping distance, High-dimensional data, Large-p, small-n problem, Linear regression, Optimal scaling, Spike-and-slab prior, Variable selection |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10125140 |
Downloads since deposit
40Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months
Archive Staff Only
 |
View Item |
