Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation
Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation
Let $(X, Y)$ be an $\mathbb{R}^d \times \mathbb{R}$-valued random vector and let $(X_1, Y_1), \cdots, (X_n, Y_n)$ be a random sample drawn from its distribution. We study the consistency properties of the kernel estimate $m_n(x)$ of the regression function $m(x) = E\{Y\mid X = x\}$ that is defined by $m_n(x) …