\(\sqrt{n}\)-consistent density estimation in semiparametric regression models
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Publication:1658728
DOI10.1016/j.csda.2016.06.013zbMath1466.62143OpenAlexW2471047867MaRDI QIDQ1658728
Publication date: 15 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.06.013
Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)
Related Items (3)
Root-\(n\) consistent estimation of the marginal density in semiparametric autoregressive time series models ⋮ A joint test for parametric specification and independence in nonlinear regression models ⋮ Testing independence between exogenous variables and unobserved errors
Cites Work
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- The thick market effect on local unemployment rate fluctuations
- Estimating the density of a possibly missing response variable in nonlinear regression
- \(\sqrt{n}\)-uniformly consistent density estimation in nonparametric regression models
- Uniformly root-\(n\) consistent density estimators for weakly dependent invertible linear proc\-esses
- Optimal bandwidth choice for density-weighted averages
- Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables
- Rate of convergence of a convolution-type estimator of the marginal density of a MA(1) process
- On bandwidth variation in kernel estimates. A square root law
- Density estimation for nonlinear parametric models with conditional heteroscedasticity
- On local \(U\)-statistic processes and the estimation of densities of functions of several sample variables
- On the estimation of the marginal density of a moving average process
- Non Standard Behavior of Density Estimators for Functions of Independent Observations
- Kernel Density-Based Linear Regression Estimate
- A Convolution Estimator for the Density of Nonlinear Regression Observations
- Testing independence and goodness-of-fit in linear models
- Remarks on Some Nonparametric Estimates of a Density Function
- A Class of Improved Parametrically Guided Nonparametric Regression Estimators
- Root-N-Consistent Semiparametric Regression
- Estimating Densities of Functions of Observations
- Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors
- Rootnconsistent density estimators for sums of independent random variables
- Parametrically Guided Non‐parametric Regression
- Root n consistent and optimal density estimators for moving average processes
- On Estimation of a Probability Density Function and Mode
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