Arbeitspapier
Efficient Bayesian nonparametric hazard regression
We model the log-cumulative baseline hazard for the Cox model via Bayesian, monotonic P-splines. This approach permits fast computation, accounting for arbitrary censorship and the inclusion of nonparametric effects. We leverage the computational efficiency to simplify effect interpretation for metric and non-metric variables by combining the restricted mean survival time approach with partial dependence plots. This allows effect interpretation in terms of survival times. Monte Carlo simulations indicate that the proposed methods work well. We illustrate our approach using a large data set of real estate data advertisements.
- ISBN
-
978-3-86788-985-8
- Sprache
-
Englisch
- Erschienen in
-
Series: Ruhr Economic Papers ; No. 850
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Semiparametric and Nonparametric Methods: General
Duration Analysis; Optimal Timing Strategies
- Thema
-
Bayesian survival analysis
nonparametric modeling
penalized spline: restricted mean survival time
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Kaeding, Matthias
- Ereignis
-
Veröffentlichung
- (wer)
-
RWI - Leibniz-Institut für Wirtschaftsforschung
- (wo)
-
Essen
- (wann)
-
2020
- DOI
-
doi:10.4419/86788985
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Kaeding, Matthias
- RWI - Leibniz-Institut für Wirtschaftsforschung
Entstanden
- 2020
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