GPLVM-WPHM

Dimensionality reduction tool for survival (time-to-event) data.
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Mise à jour 7 juin 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.

Citation pour cette source

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

Compatibilité avec les versions de MATLAB
Créé avec R2014b
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Version Publié le Notes de version
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