Bayesian Survival Analysis.
نویسندگان
چکیده
منابع مشابه
Bayesian Analysis of Survival Data with Spatial Correlation
Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study. One of the most important issues in the analysis of survival data with spatial dependence, is estimation of the parameters and prediction of the unknown values in known sites based on observations vector. In this paper to analyze this type of survival, Cox...
متن کاملA neural-Bayesian approach to survival analysis
Standard survival analysis can be given a neural interpretation in terms of a multi-layered perceptron (MLP) with exponential transfer functions. More hidden units accommodate more complex relationships. The neural interpretation suggests a Bayesian analysis, which allows one to introduce sensible priors and to sample from the posterior. We also propose a method for computing p-values from the ...
متن کاملAnalysis of Survival Times Using Bayesian Networks
In this paper we construct a Bayesian network to analyze survival times of mechanical equipment based on a set of covariates e g environmental data maintenance philosophy etc Both the predictive ability and the data exploratory features are investigated and compared to the results obtained by standard methods The methods are tested using a real life dataset from the OREDA
متن کاملSurvival Analysis: A Neural-Bayesian Approach
In this article we show that traditional Cox survival analysis can be improved upon when written in terms of a multi-layered perceptron and analyzed in the context of the Bayesian evidence framework. The obtained posterior distribution of network parameters is approximated both by Hybrid Markov Chain Monte Carlo sampling and by variational methods. We discuss the merits of both approaches. We a...
متن کاملSemiparametric Bayesian Analysis of Survival Data
This review paper investigates the potential of the semiparametric Bayes methods for the analysis of survival data. The nonparametric part of every semiparametric model is assumed to be a realization of a stochastic process. The parametric part, which may include a regression parameter or a parameter quantifying the heterogeneity of a population, is assumed to have a prior distribution with pos...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Epidemiology
سال: 2002
ISSN: 1464-3685,0300-5771
DOI: 10.1093/intjepid/31.2.505