Parametric rates of nonparametric estimators and predictors for continuous time processes
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Publication:1364733
DOI10.1214/aos/1069362734zbMath0885.62041OpenAlexW2036967785MaRDI QIDQ1364733
Publication date: 29 April 1998
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1069362734
Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
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A family of minimax rates for density estimators in continuous time ⋮ Asymptotic normality of kernel type density estimators for random fields ⋮ Local Hölder exponent estimation for multivariate continuous time processes ⋮ Asymptotic normality of kernel type regression estimators for random fields ⋮ Adaptive estimation of the stationary density of a stochastic differential equation driven by a fractional Brownian motion ⋮ Frequency polygons for continuous random fields ⋮ Consistency results for the kernel density estimate on continuous time stationary and dependent data ⋮ Adaptive estimation of density with sampled observations. ⋮ Kernel regression estimation for continuous spatial processes ⋮ Strong pointwise consistency of the \(k_T\)-occupation time density estimator ⋮ Super optimal rates for nonparametric density estimation via projection estimators ⋮ Piecewise linear density estimation for sampled data ⋮ Optimal and superoptimal convergence rate of the local linear estimator of nonparametric regression function in continuous time ⋮ Adaptive sampling schemes for density estimation ⋮ Adaptive invariant density estimation for continuous-time mixing Markov processes under sup-norm risk ⋮ Optimal convergence rates for the invariant density estimation of jump-diffusion processes
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