GPLVM-WPHM

Version 1.2.0.0 (378 KB) by James Barrett
Dimensionality reduction tool for survival (time-to-event) data.
4.0
(1)
412 Downloads
Updated 7 Jun 2015

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This is a combination of the non-linear dimensionality reduction Gaussian process latent variable model (GPLVM) and the Weibull proportional hazard model (WPHM). It is suitable for high dimensional data with time-to-event measurements. That is, survival analysis with high dimensional covariates. This work is based on the publication: http://arxiv.org/abs/1406.0812. Please don't hesitate to contact me if there are any issues.

Cite As

James Barrett (2024). GPLVM-WPHM (https://www.mathworks.com/matlabcentral/fileexchange/48565-gplvm-wphm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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v_1_2_0/

v_1_2_0/example/

v_1_2_0/wphm/

Version Published Release Notes
1.2.0.0

Discontinued use of Laplace approximation. This will achieve greater computational speed.

Added an example of dimensionality detection.
1.1.0.0

Updated description
1.0.0.0