Asymptotic normality of the recursive kernel regression estimate under dependence conditions
Let \(\{(X_i,Y_i)\}_{i\geq 1}\) be a strictly stationary and \(\alpha\)-mixing stochastic process, where \(X_i\) and \(Y_i\) are \(d\)- and one-dimensional random variables, resp. The authors study the limit behavior of certain recursive kernel estimators of the conditional expectation \(m(x) = E(Y_1| X_1=x), x\in R^d\).
scientific article; zbMATH DE number 61831