Volatility estimation in a nonlinear heteroscedastic functional regression model with martingale difference errors

DOI10.1016/j.jmva.2018.11.008zbMath1409.60042OpenAlexW2903205732WikidataQ128848086 ScholiaQ128848086MaRDI QIDQ1733275

Mohamed Chaouch

Publication date: 21 March 2019

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2018.11.008

zbMATH Keywords

asymptotic normalityempirical likelihoodergodic processesconditional varianceuniform consistencyfunctional datamartingale difference

Mathematics Subject Classification ID

Density estimation (62G07) Hypothesis testing in multivariate analysis (62H15) Large deviations (60F10) Asymptotic properties of parametric tests (62F05)

Related Items (2)

Real-time estimation for functional stochastic regression models ⋮ Recent advances in functional data analysis and high-dimensional statistics

Uses Software

• fda (R)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• An introduction to recent advances in high/infinite dimensional statistics
• A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data
• Adaptive estimation in the functional nonparametric regression model
• Bootstrap confidence intervals in functional nonparametric regression under dependence
• A partial overview of the theory of statistics with functional data
• Inference for functional data with applications
• Rate of uniform consistency for a class of mode regression on functional stationary ergodic data
• Nonparametric kernel regression estimation for functional stationary ergodic data: Asymptotic properties
• Rates of strong consistencies of the regression function estimator for functional stationary ergodic data
• Nonparametric regression estimation under mixing conditions
• Consistency of the regression estimator with functional data under long memory conditions
• Conditional variance estimation in heteroscedastic regression models
• Some mixing properties of time series models
• A limit theorem for the maximum of autoregressive processes with uniform marginal distributions
• The asymptotic distribution theory of the empiric cdf for mixing stochastic processes
• Local polynomial estimators of the volatility function in nonparametric autoregression
• Linear processes in function spaces. Theory and applications
• Recursive estimation of nonparametric regression with functional covariate
• Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data
• Curse of dimensionality and related issues in nonparametric functional regression
• Recursive estimation of the conditional geometric median in Hilbert spaces
• Online estimation of the geometric median in Hilbert spaces: nonasymptotic confidence balls
• Functional data analysis.
• Nonparametric regression estimation for dependent functional data: asymptotic normality
• Kernel estimates of the mean and the volatility functions in a nonlinear autoregressive model with ARCH errors
• Nonparametric functional data analysis. Theory and practice.
• Nonparametric Estimation of Variance Function for Functional Data Under Mixing Conditions
• Empirical Likelihood Inference for Nonparametric Regression Functions with Functional Stationary Ergodic Data
• A NONPARAMETRIC REGRESSION ESTIMATOR THAT ADAPTS TO ERROR DISTRIBUTION OF UNKNOWN FORM
• Conditional mode estimation for functional stationary ergodic data with responses missing at random
• EMPIRICAL-LIKELIHOOD-BASED CONFIDENCE INTERVALS FOR CONDITIONAL VARIANCE IN HETEROSKEDASTIC REGRESSION MODELS
• Non-strong mixing autoregressive processes
• Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
• Nonparametric estimation of the conditional variance function with correlated errors
• Error variance estimation in semi-functional partially linear regression models
• Locally modelled regression and functional data
• UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
• Efficient estimation of conditional variance functions in stochastic regression
• Local Polynomial Estimation of Regression Functions for Mixing Processes
• Local Polynomial Variance-Function Estimation
• Nonparametric modelling for functional data: selected survey and tracks for future
• NONPARAMETRIC ESTIMATION OF VOLATILITY FUNCTIONS: THE LOCAL EXPONENTIAL ESTIMATOR
• Nonparametric models for functional data, with application in regression, time series prediction and curve discrimination
• Bootstrap-based testing of equality of mean functions or equality of covariance operators for functional data
• NONPARAMETRIC REGRESSION ON FUNCTIONAL DATA: INFERENCE AND PRACTICAL ASPECTS

This page was built for publication: Volatility estimation in a nonlinear heteroscedastic functional regression model with martingale difference errors