Kernel Semi-Parametric Models

To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables.


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install.packages("KSPM")

0.1.1 by Catherine Schramm, 20 days ago


Browse source code at https://github.com/cran/KSPM


Authors: Catherine Schramm [aut, cre] , Aurelie Labbe [ctb] , Celia M. T. Greenwood [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports usethis, expm, CompQuadForm, DEoptim

Suggests testthat


See at CRAN