Kernel methods and support vector machines (SVMs) serve as cornerstones in modern machine learning, offering robust techniques for both classification and regression tasks. At their core, kernel ...

Simulations are necessary to assess the performance of home-range estimators because the true distribution of empirical data is unknown, but we must question whether that performance applies to ...

A two-step nonparametric regression quantile smoothing technique is presented here, combining a standard k-NN technique and a locally linear kernel smoother. There ...