Semiparametric modeling and estimation of heteroscedasticity in regression analysis of cross-sectional data

DOI10.1214/09-EJS547zbMath1329.62203MaRDI QIDQ1952046

Lan Wang, Ingrid Van Keilegom

Publication date: 27 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1265033306

zbMATH Keywords

semiparametric regressionheteroscedasticityquantile regressionvariance functiondispersion functionsingle-index modelpartially linear model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (9)

Discussion on “on studying extreme values and systematic risks with nonlinear time series models and tail dependence measures” ⋮ Estimation of extreme quantiles from heavy-tailed distributions with neural networks ⋮ Heteroscedastic partially linear model under skew-normal distribution with application in ragweed pollen concentration ⋮ Estimation of extreme quantiles from heavy-tailed distributions in a location-dispersion regression model ⋮ Quality of Fit Measures in the Framework of Quantile Regression ⋮ Semiparametric efficiency for partially linear single-index regression models ⋮ High-dimensional index volatility models via Stein's identity ⋮ Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models ⋮ Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

Uses Software

• SemiPar

Cites Work

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• Estimation in a semiparametric partially linear errors-in-variables model
• On a semiparametric variance function model and a test for heteroscedasticity
• Weak convergence and empirical processes. With applications to statistics
• Weighted least squares estimates in partly linear regression models
• Optimal smoothing in single-index models
• On semiparametric \(M\)-estimation in single-index regression
• Non-parametric Estimation of the Residual Distribution
• Variances Are Not Always Nuisance Parameters
• L-estimatton for linear heteroscedastic models
• Variance Function Estimation
• Variance functions and the minimum detectable concentration in assays
• Local Linear Quantile Regression
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Local Polynomial Variance-Function Estimation
• Semiparametric Regression
• EFFICIENT SEMIPARAMETRIC ESTIMATION OF A PARTIALLY LINEAR QUANTILE REGRESSION MODEL
• Semiparametric Regression for the Applied Econometrician
• Quasi-Likelihood Regression with Multiple Indices and Smooth Link and Variance Functions
• ASYMPTOTICALLY EFFICIENT MEDIAN REGRESSION IN THE PRESENCE OF HETEROSKEDASTICITY OF UNKNOWN FORM
• Estimation of Semiparametric Models when the Criterion Function Is Not Smooth
• Efficient semiparametric estimator for heteroscedastic partially linear models
• Nonparametric Estimation of an Additive Quantile Regression Model

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