Gaussian process regression for survival data with competing risks

版本 1.0 (1.1 MB) 作者: James Barrett
Flexible non-parametric regression tool for survival data (including competing risks)
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更新时间 2014/11/25

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This tool performs Gaussian process (GP) regression on time-to-event measurements (survival data). GP regression offers a flexible non-parametric way to infer the relationship between covariates and survival outcomes. Predictions, hazard rates, and survival functions can all be computed. This work is based on the publication available here: http://arxiv.org/abs/1312.1591. Please don't hesitate to email me if there are any problems.

引用格式

James Barrett (2024). Gaussian process regression for survival data with competing risks (https://www.mathworks.com/matlabcentral/fileexchange/48566-gaussian-process-regression-for-survival-data-with-competing-risks), MATLAB Central File Exchange. 检索时间: .

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1.0