Accelerated failure-time model with weighted least-squares estimation: application on survival of HIV positives

Least Absolute Deviations Estimation for the Accelerated Failure Time Model

The accelerated failure time (AFT) model assumes a linear relationship between the event time and the covariates. We propose a robust weighted least-absolute-deviations (LAD) method for estimation in the AFT model with right-censored data. This method uses the Kaplan-Meier weights in the LAD objective function to account for censoring. We show that the proposed estimator is root-n consistent an...

Weighted Least Squares Estimation with Missing Data

Application of the Weibull Accelerated Failure Time Model in the Determination of Disease-Free Survival Rate of Patients with Breast Cancer

Background and Purpose: The goal of this study is application of the proportional hazards model (PH) and accelerated failure time model (AFT), with consideration Weibull distribution, to determine the level of effectiveness of the factors affecting on the level of disease-free survival (DFS) of the patients with breast cancer. Materials and Methods: Based on the retrospective descriptive stu...

Power System State Estimation Using Weighted Least Squares (WLS) and Regularized Weighted Least Squares(RWLS) Method

In this paper, a new formulation for power system state estimation is proposed. The formulation is based on regularized least squares method which uses the principle of Thikonov’s regularization to overcome the limitations of conventional state estimation methods. In this approach, the mathematical unfeasibility which results from the lack of measurements in case of ill-posed problems is elimin...

Estimation Methods for Accelerated Failure Time Model

In the literature, a lot of effort has been devoted to develop effective estimation and inference methods for the accelerated failure time (AFT) model for right censored data. In the talk, we will give a review on the recent development on the estimation and inference methods for the AFT model based on the work in [Jin et al., 2003] and [Jin et al., 2004].