13 citations · 32 across the 4 of their papers we have counts for
4 papers · 1 filter
Time-Dependent Pseudo for Assessing Predictive Performance in Competing Risks Data
Zian Zhuang, Wen Su, Eric Kawaguchi +1
Evaluating and validating the performance of prediction models is a fundamental task in statistics, machine learning, and their diverse applications. However, developing robust per…
Probability-scale residuals for event-time data
Eric S. Kawaguchi, Bryan E. Shepherd, Chun Li
The probability-scale residual (PSR) is defined as , where is the observed outcome and is a random variable from the fitted distribution. The PSR is pa…
Scalable Algorithms for Large Competing Risks Data
Eric S. Kawaguchi, Jenny I. Shen, Marc A. Suchard +1
This paper develops two orthogonal contributions to scalable sparse regression for competing risks time-to-event data. First, we study and accelerate the broken adaptive ridge meth…
Scalable Sparse Cox's Regression for Large-Scale Survival Data via Broken Adaptive Ridge
Eric S. Kawaguchi, Marc A. Suchard, Zhenqiu Liu +1
This paper develops a new scalable sparse Cox regression tool for sparse high-dimensional massive sample size (sHDMSS) survival data. The method is a local -penalized Cox regr…