k-Nearest neighbor density estimation on Riemannian Manifolds

Karl Pearson's meta-analysis revisited

Kendall's tau in high-dimensional genomic parsimony

Kernel change-point detection

Kernel deconvolution estimation for random fields

Kernel density estimation for stationary random fields

Kernel density estimation via diffusion

Kernel dimension reduction in regression

Kernel Estimation of Density Level Sets

Kernel Inverse Regression for spatial random fields

Kernel methods in machine learning

Kernel regression uniform rate estimation for censored data under $α$-mixing condition

Kink estimation in stochastic regression with dependent errors and predictors

Kullback Leibler property of kernel mixture priors in Bayesian density estimation

Kumaraswamy and beta distribution are related by the logistic map