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catherineschramm
KSPM: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. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.
Maintained by Catherine Schramm. Last updated 5 years ago.
2.26 score 18 scripts
cran
Fgmutils:Forest Growth Model Utilities
Growth models and forest production require existing data manipulation and the creation of new data, structured from basic forest inventory data. The purpose of this package is provide functions to support these activities.
Maintained by Clayton Vieira Fraga Filho. Last updated 6 years ago.
1.48 score 1 dependents