Literature DB >> 15690993

Survival models based on the Ornstein-Uhlenbeck process.

Odd O Aalen1, Håkon K Gjessing.   

Abstract

When modelling survival data it may be of interest to imagine an underlying process leading up to the event in question. The Ornstein-Uhlenbeck process is a natural model to consider in a biological context because it stabilizes around some equilibrium point. This corresponds to the homeostasis often observed in biology, and also to some extent in the social sciences. First, we study the first-passage time distribution of an Ornstein-Uhlenbeck process, focussing especially on what is termed quasi-stationarity and the various shapes of the hazard rate. Next, we consider a model where the individual hazard rate is a squared function of an Ornstein-Uhlenbeck process. We extend known results on this model. The results on quasi-stationarity are relevant for recent discussions about mortality plateaus. In addition, we point out a connection to models for short-term interest rates in financial modeling.

Mesh:

Year:  2004        PMID: 15690993     DOI: 10.1007/s10985-004-4775-9

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  2 in total

1.  Markov mortality models: implications of quasistationarity and varying initial distributions.

Authors:  David Steinsaltz; Steven N Evans
Journal:  Theor Popul Biol       Date:  2004-06       Impact factor: 1.570

2.  A random-walk model of human mortality and aging.

Authors:  M A Woodbury
Journal:  Theor Popul Biol       Date:  1977-02       Impact factor: 1.570

  2 in total
  7 in total

1.  Special issue dedicated to Odd O. Aalen.

Authors:  Ørnulf Borgan; Håkon K Gjessing
Journal:  Lifetime Data Anal       Date:  2019-08-28       Impact factor: 1.588

2.  Semiparametric Stochastic Modeling of the Rate Function in Longitudinal Studies.

Authors:  Bin Zhu; Jeremy M G Taylor; Peter X-K Song
Journal:  J Am Stat Assoc       Date:  2011-12-01       Impact factor: 5.033

3.  Some Dissimilarity Measures of Branching Processes and Optimal Decision Making in the Presence of Potential Pandemics.

Authors:  Niels B Kammerer; Wolfgang Stummer
Journal:  Entropy (Basel)       Date:  2020-08-08       Impact factor: 2.524

4.  Ornstein-Uhlenbeck threshold regression for time-to-event data with and without a cure fraction.

Authors:  Roger Erich; Michael L Pennell
Journal:  Lifetime Data Anal       Date:  2014-08-06       Impact factor: 1.588

Review 5.  Dynamics of biomarkers in relation to aging and mortality.

Authors:  Konstantin G Arbeev; Svetlana V Ukraintseva; Anatoliy I Yashin
Journal:  Mech Ageing Dev       Date:  2016-04-29       Impact factor: 5.432

6.  Steady-state EB cap size fluctuations are determined by stochastic microtubule growth and maturation.

Authors:  Jamie Rickman; Christian Duellberg; Nicholas I Cade; Lewis D Griffin; Thomas Surrey
Journal:  Proc Natl Acad Sci U S A       Date:  2017-03-09       Impact factor: 11.205

7.  A tutorial on frailty models.

Authors:  Theodor A Balan; Hein Putter
Journal:  Stat Methods Med Res       Date:  2020-05-28       Impact factor: 3.021

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.