Mallick B K, Denison D G, Smith A F
Department of Statistics, Texas A&M University, College Station 77843-3143, USA.
Biometrics. 1999 Dec;55(4):1071-7. doi: 10.1111/j.0006-341x.1999.01071.x.
A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is described to obtain the estimate of the hazard function as well as the survival curve.
一种贝叶斯多元自适应回归样条拟合方法被用于对含删失的单变量和多变量生存数据进行建模。可能的模型将比例风险模型作为一个子类包含在内,并能自动检测偏离该模型的情况。描述了一种可逆跳跃马尔可夫链蒙特卡罗算法以获得风险函数以及生存曲线的估计值。