Cox proportional hazards model with Weibull base hazard rate
This function implements a Cox PH model with a Weibull base hazard rate (also called a Weibull proportional hazards model).
The standard Cox model assumes (usually implicitly) Breslow's non-parametric baseline hazard estimator. This is ill suited to predicting the event time for new individuals. For this purpose the Weibull-Cox model can provide predictions with error bars (given by the standard deviation) along with the usual regression coefficients, (smooth) survival functions and (smooth) hazard rates.
Functions are included for predicting the event time for an individual once a model has been trained.
Get started by running example.m.
Please email me with comments or requests.
Citation pour cette source
James Barrett (2024). Cox proportional hazards model with Weibull base hazard rate (https://www.mathworks.com/matlabcentral/fileexchange/46415-cox-proportional-hazards-model-with-weibull-base-hazard-rate), MATLAB Central File Exchange. Récupéré le .
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- AI and Statistics > Statistics and Machine Learning Toolbox > Industrial Statistics >
- Computational Finance > Financial Instruments Toolbox > Price Instruments Using Functions > Credit Derivatives and Credit Exposures >
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weibull_cox_v_1_1_4/
Version | Publié le | Notes de version | |
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1.6.0.0 | Fixed a bug where the upper integration bound was not computed correctly when making predictions. |
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1.5.0.0 | Fixed a bug in the prediction function. |
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1.4.0.0 | Fixed bug with large values of rho. Fixed bug where incorrect values of rho and nu were returned. Relaxed the accuracy of numerical integrals. |
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1.3.0.0 | Fixed bug in gradient and hessian computation, updated documentation |
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1.2.0.0 | Switched to gradient based optimisation |
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1.1.0.0 | Changed name |
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1.0.0.0 |