Quadratic errors for nonparametric estimates under dependence
From MaRDI portal
Publication:1182766
DOI10.1016/0047-259X(91)90105-BzbMath0751.62022MaRDI QIDQ1182766
Publication date: 28 June 1992
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
equivalenceasymptotic expansionsconditional densityintegrated square errorfunctional estimationasymptotic equivalencehazardstrong mixing conditiondependent observationsregression functionsmean integrated square erroralpha-mixing conditionkernel type estimatorsaverage square errornonparametric curve estimates
Related Items
On convergence rates for quadratic errors in kernel hazard estimation ⋮ A nonparametric method to estimate time varying coefficients under seasonal constraints ⋮ Growth curves: A two-stage nonparametric approach ⋮ Density estimation for time series by histograms ⋮ Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data ⋮ Recursive regression estimators with application to nonparametric prediction ⋮ MODIFIED CROSS-VALIDATION IN SEMIPARAMETRIC REGRESSION MODELS WITH DEPENDENT ERRORS ⋮ Optimal asymptotic quadratic error of density estimators for strong mixing or chaotic data ⋮ Quadratic error of the kernel estimate of the conditional density when the regressor is functional ⋮ Nonparametric estimation of density derivatives of dependent data ⋮ Choice of regressors in nonparametric estimation ⋮ Kernel estimation of the regression function with random sampling times ⋮ Functional projection pursuit regression ⋮ Optimal smooth hazard estimates ⋮ Strong convergence of sums of \(\alpha \)-mixing random variables with applications to density estimation ⋮ On histograms for linear processes ⋮ A plug-in technique in nonparametric regression with dependence ⋮ Order Choice in Nonlinear Autoregressive Models ⋮ Density estimation in \(\mathbb{L}^\infty\) norm for mixing processes ⋮ Optimal bandwidth selection for multivariate kernel deconvolution density estimation ⋮ Nonparametric density estimation for nonmixing approximable stochastic processes ⋮ Some Classes of Stochastic Differential Equations as an Alternative Modeling Approach to Biomedical Problems ⋮ A local cross-validation algorithm for dependent data ⋮ Nonparametric estimation of the hazard function under dependence conditions ⋮ New kernel estimators of the hazard ratio and their asymptotic properties ⋮ Plug-in bandwidth selection in kernel hazard estimation from dependent data ⋮ Nonparametric estimation under long memory dependence ⋮ Nonparametric estimation for dependent data ⋮ Automatic smoothing parameter selection for the nonparametric regression estimation of functional data. ⋮ Nonparametric Estimation for the Hazard Function ⋮ Convergence rate for cross-validatory bandwidth in kernel hazard estimation from dependent samples ⋮ Asymptotic behavior of bandwidth selected by the cross-validation method for local polynomial fitting ⋮ Nonparametric estimation of time varying parameters under shape restrictions
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
- Smoothing parameter selection in hazard estimation
- Central limit theorem for integrated square error of multivariate nonparametric density estimators
- Nonparametric regression estimation under mixing conditions
- Data-driven bandwidth choice for density estimation based on dependent data
- Estimation de la transition de probabilité d'une chaîne de Markov Doeblin-recurrente. Étude du cas du processus autoregressif général d'ordre 1
- Random approximations to some measures of accuracy in nonparametric curve estimation
- Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations
- Hazard rate estimation under dependence conditions
- Limit theorems for stochastic measures of the accuracy of density estimators
- Probabilities of maximal deviations for nonparametric regression function estimates
- Kernel density estimation under dependence
- Convergence properties of an empirical error criterion for multivariate density estimation
- Robust nonparametric regression estimation for dependent observations
- A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
- Estimation of the failure rate-a survey of nonparametric methods Part I: Non-Bayesian Methods
- Kernel Estimators of the Failure-Rate Function and Density Estimation: An Analogy
- Nonparametric Density Estimation, Prediction, and Regression for Markov Sequences
- Estimation Non-paramétrique de la Régression: Revue Bibliographique
- Empirical distribution function for mixing random variables. application in nonparametric hazard estimation
- Hazard analysis. I
- Curve Estimates
- On Estimation of a Probability Density Function and Mode