Semiparametric Bayesian analysis of high-dimensional censored outcome data
The Surveillance, Epidemiology and End Results (SEER) cancer database contains survival data for US individuals diagnosed with cancer. Semiparametric Bayesian methods are computationally expensive to fit for such large data-sets. This paper develops a cost-effective Markov chain Monte Carlo strategy...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Taylor & Francis Group
2017-07-01
|
| Schriftenreihe: | Statistical Theory and Related Fields |
| Schlagworte: | |
| Online-Zugang: | http://dx.doi.org/10.1080/24754269.2017.1396436 |
| Tags: |
Keine Tags, Fügen Sie das erste Tag hinzu!
|