CoxFlexBoost: Project Home – R-Forge

CoxFlexBoost:
likelihood-based boosting approach to fit structured Cox-type survival models with linear, smooth and (linear/smooth) time-varying effects.
By applying a component-wise boosting approach variable selection and model choice are possible.

• Development Status : 4 - Beta
• Development Status : 5 - Production/Stable
• Intended Audience : Developers
• Intended Audience : End Users/Desktop
• License : OSI Approved : GNU General Public License (GPL)
• Natural Language : English
• Programming Language : R
• Topic : Machine Learning : Boosting
• Topic : Machine Learning : Model Selection and Validation
• Topic : Machine Learning : Regularized and Shrinkage Methods

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