Strong Uniform Convergence Rates for Some Robust Equivariant Nonparametric Regression Estimates for Mixing Processes
Copyright policy )Strong Uniform Convergence Rates for Some Robust Equivariant Nonparametric Regression Estimates for Mixing Processes
Summary: We prove the strong uniform consistency of some robust equivariant nonparametric regression estimates, based on kernel weights and on nearest neighbor with kernel weights, for strongly and uniform strongly processes. Strong uniform convergence rates for these estimates are obtained. Applications to robust nonparametric autoregression are given.
robust nonparametric autoregression, Density estimation, Time series, auto-correlation, regression, etc. in statistics (GARCH), Nonparametric robustness, strong uniform consistency, Asymptotic properties of nonparametric inference, uniform strongly processes, nearest neighbor with kernel weights, robust equivariant nonparametric regression estimates, kernel weights
robust nonparametric autoregression, Density estimation, Time series, auto-correlation, regression, etc. in statistics (GARCH), Nonparametric robustness, strong uniform consistency, Asymptotic properties of nonparametric inference, uniform strongly processes, nearest neighbor with kernel weights, robust equivariant nonparametric regression estimates, kernel weights
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