Pages that link to "Item:Q5155357"

The following pages link to Large and moderate deviation principles for averaged stochastic approximation method for the estimation of a regression function (Q5155357):

Displaying 8 items.

• Data-driven deconvolution recursive kernel density estimators defined by stochastic approximation method (Q2023841) (← links)
• Optimal bandwidth selection for recursive Gumbel kernel density estimators (Q2178952) (← links)
• Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method (Q2322619) (← links)
• Revisiting R\'ev\'esz's stochastic approximation method for the estimation of a regression function (Q3623899) (← links)
• On the Averaged Stochastic Approximation for Linear Regression (Q4874940) (← links)
• Bernstein polynomial of recursive regression estimation with censored data (Q5090307) (← links)
• Large and moderate deviation principles for nonparametric recursive kernel distribution estimators defined by stochastic approximation method (Q5106688) (← links)
• Nonparametric recursive estimation for multivariate derivative functions by stochastic approximation method (Q6133738) (← links)