On Convergence Rates of Convex Regression in Multiple Dimensions
INFORMS Journal on Computing · 2014 · Volume 26 · Issue 3
Abstract
We consider a least squares estimator for estimating a convex function f * : [0, 1] d → ℝ with bounded subgradients. A rate at which the sum of squared differences between the estimator and the true function f * converges to zero is computed. This work sheds light on computing the convergence rate of the multidimensional convex regression estimator.
Keywords
nonparametric regression, multidimensional convex functions, convergence rates, asymptotic properties
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