Broken adaptive ridge regression for right-censored survival data

Kernel Ridge Estimator for the Partially Linear Model under Right-Censored Data

Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is t...

Rotation survival forest for right censored data

Recently, survival ensembles have found more and more applications in biological and medical research when censored time-to-event data are often confronted. In this research, we investigate the plausibility of extending a rotation forest, originally proposed for classification purpose, to survival analysis. Supported by the proper statistical analysis, we show that rotation survival forests are...

Umbrella Tests for Right-censored Survival Data

This paper considers the problem of testing for umbrella alternatives in the one-way layout when survival data are subject to random right censorship. Testing procedures based on two-sample weighted logrank statistics are suggested for both cases when the peak of the umbrella is known or unknown. The Pitman efficacy of the peak-known umbrella test is derived. A class of Lehmann and scale altern...

Nonparametric regression with censored survival time data

The paper deals with a class of nonparametric regression estimates introduced by Beran (1981) to estimate conditional survival functions in the presence of right censoring. Weak convergence results are established for kernel and nearest neighbour estimates of the conditional cumulative hazard and survival functions as well as the quantile and L-type regression functionals.

Smoothing Spline Regression Estimates for Randomly Right Censored Data