TY - GEN
T1 - Nonparametric Bayesian Analysis of Hazard Rate Functions using the Gamma Process Prior
AU - Arnold, Richard
AU - Chukova, Stefanka
AU - Hayakawa, Yu
N1 - Funding Information:
This work was supported by: Waseda University, Grant for Special Research Projects (2018K-383); JSPS KAKENHI Grant-in-Aid for Scientific Research (C) Grant Number 18K04621; Waseda Institute for Advanced Study Visiting Scholars 2018; FY2018 Grant Program for Promotion of International Joint Research, Waseda University. Fulbright New Zealand: Fulbright Scholar Award 2018.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - When failure time data are modelled using an inhomogeneous Poisson process, it is necessary to model the underlying hazard rate function λ(t). The most common approaches to the problem either select some parametric form for λ(t), or alternatively-conditional on some collected data set- A pproximate it using the non-parametric Kaplan-Meier estimator. In this paper we present simulation and inference for a non-parametric hazard rate function drawn from a Gamma Process Prior. We use a gamma-scaled Dirichlet Process prior to implement the Gamma Process prior, and construct a Markov Chain Monte Carlo sampler to carry out inference. We demon-strate the methodology with the simulation of a process with an increasing failure rate.
AB - When failure time data are modelled using an inhomogeneous Poisson process, it is necessary to model the underlying hazard rate function λ(t). The most common approaches to the problem either select some parametric form for λ(t), or alternatively-conditional on some collected data set- A pproximate it using the non-parametric Kaplan-Meier estimator. In this paper we present simulation and inference for a non-parametric hazard rate function drawn from a Gamma Process Prior. We use a gamma-scaled Dirichlet Process prior to implement the Gamma Process prior, and construct a Markov Chain Monte Carlo sampler to carry out inference. We demon-strate the methodology with the simulation of a process with an increasing failure rate.
KW - Bayesian non-parametrics
KW - Gamma Process
KW - Hazard rate function.
KW - Reliability
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U2 - 10.1109/APARM49247.2020.9209405
DO - 10.1109/APARM49247.2020.9209405
M3 - Conference contribution
AN - SCOPUS:85093965085
T3 - 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
BT - 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, APARM 2020
Y2 - 20 August 2020 through 23 August 2020
ER -