Kernel Deep Stacking Networks (kernDeepStackNet)
Contains functions for estimation and model selection of kernel deep stacking networks. The model selection includes direct optimization or model based alternatives with arbitrary loss functions.
Finding the Optimal Cluster Number Using Progeny Clustering (progenyClust)
Implementing the Progeny Clustering algorithm, the progenyClust package assesses the clustering stability and identifies the optimal clustering number for a given data matrix. It uses kmeans clustering as default, but can be customized to work with other clustering algorithms and different parameter settings. The package includes one main function progenyClust(), plot and summary methods for progenyClust object, and one example dataset example for testing.
Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions (npregfast)
A method for obtain nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers. Additionally, a parametric model (allometric model) can be estimated.