Asymptotics for function derivatives estimators based on stationary and ergodic discrete time processes
DOI10.1007/s10463-021-00814-2zbMath1497.62085OpenAlexW4206567855WikidataQ114227661 ScholiaQ114227661MaRDI QIDQ2086282
Sultana Didi Biha, Mohamed Chaouch, Salim Bouzebda
Publication date: 25 October 2022
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-021-00814-2
kernel estimationmartingale differencesdensity estimationregression estimationnonparametric estimationergodic discrete time processesfunction derivative
Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Stationary stochastic processes (60G10)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Multivariate wavelet density and regression estimators for stationary and ergodic continuous time processes: asymptotic results
- Canonical higher-order kernels for density derivative estimation
- Kernel estimation for time series: an asymptotic theory
- Absolute regularity and ergodicity of Poisson count processes
- Root \(n\) estimates of vectors of integrated density partial derivative functionals
- Smoothing splines: Regression, derivatives and deconvolution
- Sizer analysis for the comparison of regression curves
- On estimation of a density and its derivatives
- Speed of convergence in nonparametric kernel estimation of a regression function and its derivatives
- Ergodic theorems. With a supplement by Antoine Brunel
- Bandwidth choice for differentiation
- Bounds for estimation of density functions and their derivatives
- Nonparametric estimation of mixed partial derivatives of a multivariate density
- Consistent nonparametric regression. Discussion
- Weak and strong uniform consistency of the kernel estimate of a density and its derivatives
- Improvements on strong uniform consistency of some known kernel estimates of a density and its derivatives
- On the asymptotic normality of kernel regression estimators of the mode in the nonparametric random design model.
- Applied functional data analysis. Methods and case studies
- A unified treatment of direct and indirect estimation of a probability density and its derivatives
- General asymptotic confidence bands based on kernel-type function estimators
- Rates of consistency for nonparametric estimation of the mode in absence of smoothness assumptions
- Degenerate \(U\)- and \(V\)-statistics under ergodicity: asymptotics, bootstrap and applications in statistics
- Data-driven density derivative estimation, with applications to nonparametric clustering and bump hunting
- Normal reference bandwidths for the general order, multivariate kernel density derivative estimator
- Some asymptotic properties of kernel regression estimators of the mode for stationary and ergodic continuous time processes
- Optimal asymptotic MSE of kernel regression estimate for continuous time processes with missing at random response
- The bootstrap in kernel regression for stationary ergodic data when both response and predictor are functions
- Gradient-based smoothing parameter selection for nonparametric regression estimation
- Limiting law results for a class of conditional mode estimates for functional stationary ergodic data
- Functional data analysis.
- An approximation to the density function
- Additive regression model for stationary and ergodic continuous time processes
- Multivariate wavelet density and regression estimators for stationary and ergodic discrete time processes: Asymptotic results
- An Effective Bandwidth Selector for Local Least Squares Regression
- Remarks on Some Nonparametric Estimates of a Density Function
- Bandwidth choice and confidence intervals for derivatives of noisy data
- Local Linear Quantile Regression
- Robust Locally Weighted Regression and Smoothing Scatterplots
- Design-adaptive Nonparametric Regression
- The estimation of the gradient of a density function, with applications in pattern recognition
- Mean squared errors of estimates of a density and its derivatives
- Confidence Bands in Nonparametric Regression
- Nonparametric estimation of a regression function and its derivatives under an ergodic hypothesis
- Optimal sampling for density estimation in continuous time
- On nonparametric kernel estimation of the mode of the regression function in the random design model
- On kernel density derivative estimation
- Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence
- Direct Density Derivative Estimation
- Estimation of a Probability Density Function and Its Derivatives
- On Estimation of a Probability Density Function and Mode
- Non-Parametric Inference for Density Modes
- Combinatorial methods in density estimation
- Maximum penalized likelihood estimation. Vol. 1: Density estimation
- On bootstrapping the mode in the nonparametric regression model with random design