Bayesian Inference in a Parametric Counting Process Model

We are in this paper concerned with Bayesian inference in a counting process model where the intensities depend on an unknown parameter. In particular, the model gives a unified approach to Bayesian inference for a large number of parametric failure time models with censoring. Asymptotic properties...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Scandinavian Journal of Statistics. - Blackwell Publishers, 1974. - 13(1986), 2, Seite 87-97
1. Verfasser: Aven, Terje (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1986
Zugriff auf das übergeordnete Werk:Scandinavian Journal of Statistics
Schlagworte:counting processes intensities martingales Bayesian inference survival analysis life testing censoring asymptotic theory Behavioral sciences Information science mehr... Mathematics Social sciences Philosophy
LEADER 01000caa a22002652 4500
001 JST077789733
003 DE-627
005 20240623113031.0
007 cr uuu---uuuuu
008 150325s1986 xx |||||o 00| ||eng c
035 |a (DE-627)JST077789733 
035 |a (JST)4616015 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Aven, Terje  |e verfasserin  |4 aut 
245 1 0 |a Bayesian Inference in a Parametric Counting Process Model 
264 1 |c 1986 
336 |a Text  |b txt  |2 rdacontent 
337 |a Computermedien  |b c  |2 rdamedia 
338 |a Online-Ressource  |b cr  |2 rdacarrier 
520 |a We are in this paper concerned with Bayesian inference in a counting process model where the intensities depend on an unknown parameter. In particular, the model gives a unified approach to Bayesian inference for a large number of parametric failure time models with censoring. Asymptotic properties of the Bayes estimator (w.r.t. quadratic loss function) are studied. 
540 |a Copyright The Almqvist & Wiksell Periodical Company 
650 4 |a counting processes 
650 4 |a intensities 
650 4 |a martingales 
650 4 |a Bayesian inference 
650 4 |a survival analysis 
650 4 |a life testing 
650 4 |a censoring 
650 4 |a asymptotic theory 
650 4 |a Behavioral sciences  |x Psychology  |x Cognitive psychology  |x Cognitive processes  |x Decision making  |x Bayesian theories  |x Bayes estimators 
650 4 |a Information science  |x Information management  |x Information classification  |x Cladistics  |x Bayesian inference 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Statistical models  |x Parametric models 
650 4 |a Mathematics  |x Pure mathematics  |x Probability theory  |x Random variables  |x Stochastic processes  |x Martingales 
650 4 |a Mathematics  |x Pure mathematics  |x Probability theory  |x Probabilities 
650 4 |a Social sciences  |x Communications  |x Censorship 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Statistical theories 
650 4 |a Mathematics  |x Pure mathematics  |x Geometry  |x Geometric shapes  |x Curves  |x Asymptotes  |x Asymptotic properties 
650 4 |a Philosophy  |x Metaphysics  |x Etiology  |x Determinism 
650 4 |a Mathematics  |x Applied mathematics  |x Analytics  |x Analytical estimating  |x Maximum likelihood estimation 
655 4 |a research-article 
773 0 8 |i Enthalten in  |t Scandinavian Journal of Statistics  |d Blackwell Publishers, 1974  |g 13(1986), 2, Seite 87-97  |w (DE-627)266018297  |w (DE-600)1466951-1  |x 14679469  |7 nnns 
773 1 8 |g volume:13  |g year:1986  |g number:2  |g pages:87-97 
856 4 0 |u https://www.jstor.org/stable/4616015  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_JST 
912 |a GBV_ILN_11 
912 |a GBV_ILN_20 
912 |a GBV_ILN_22 
912 |a GBV_ILN_24 
912 |a GBV_ILN_31 
912 |a GBV_ILN_39 
912 |a GBV_ILN_40 
912 |a GBV_ILN_60 
912 |a GBV_ILN_62 
912 |a GBV_ILN_63 
912 |a GBV_ILN_65 
912 |a GBV_ILN_69 
912 |a GBV_ILN_70 
912 |a GBV_ILN_90 
912 |a GBV_ILN_100 
912 |a GBV_ILN_101 
912 |a GBV_ILN_110 
912 |a GBV_ILN_120 
912 |a GBV_ILN_285 
912 |a GBV_ILN_374 
912 |a GBV_ILN_702 
912 |a GBV_ILN_2001 
912 |a GBV_ILN_2003 
912 |a GBV_ILN_2005 
912 |a GBV_ILN_2006 
912 |a GBV_ILN_2007 
912 |a GBV_ILN_2008 
912 |a GBV_ILN_2009 
912 |a GBV_ILN_2010 
912 |a GBV_ILN_2011 
912 |a GBV_ILN_2014 
912 |a GBV_ILN_2015 
912 |a GBV_ILN_2018 
912 |a GBV_ILN_2020 
912 |a GBV_ILN_2021 
912 |a GBV_ILN_2026 
912 |a GBV_ILN_2027 
912 |a GBV_ILN_2044 
912 |a GBV_ILN_2050 
912 |a GBV_ILN_2056 
912 |a GBV_ILN_2057 
912 |a GBV_ILN_2061 
912 |a GBV_ILN_2088 
912 |a GBV_ILN_2107 
912 |a GBV_ILN_2110 
912 |a GBV_ILN_2190 
912 |a GBV_ILN_2938 
912 |a GBV_ILN_2947 
912 |a GBV_ILN_2949 
912 |a GBV_ILN_2950 
912 |a GBV_ILN_4012 
912 |a GBV_ILN_4035 
912 |a GBV_ILN_4037 
912 |a GBV_ILN_4046 
912 |a GBV_ILN_4112 
912 |a GBV_ILN_4126 
912 |a GBV_ILN_4242 
912 |a GBV_ILN_4251 
912 |a GBV_ILN_4305 
912 |a GBV_ILN_4306 
912 |a GBV_ILN_4307 
912 |a GBV_ILN_4313 
912 |a GBV_ILN_4322 
912 |a GBV_ILN_4323 
912 |a GBV_ILN_4325 
912 |a GBV_ILN_4335 
912 |a GBV_ILN_4346 
912 |a GBV_ILN_4392 
912 |a GBV_ILN_4393 
912 |a GBV_ILN_4700 
951 |a AR 
952 |d 13  |j 1986  |e 2  |h 87-97