Local linear smoothing for regression surfaces on the simplex using Dirichlet kernels. [PDF]
Genest C, Ouimet F.
europepmc +1 more source
Hellinger distance and Kullback--Leibler loss for the kernel density estimator
The optimal window width, which asymptotically minimizes mean Hellinger distance between the kernel estimator and density, is known to be equivalent to the one that maximizes expected Kullback--Leibler loss for compactly supported densities. Implications
Kanazawa, Yuichiro
core
TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-Based Data. [PDF]
Gu Z, Yu S, Wang G, Lai MJ, Wang L.
europepmc +1 more source
Linear Wavelet-Based Estimators of Partial Derivatives of Multivariate Density Function for Stationary and Ergodic Continuous Time Processes. [PDF]
Didi S, Bouzebda S.
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Estimators of scale parameters in linear regression
This note discusses the asymptotic distribution of two scale and location invariant estimators of two scale parameters in the multiple linear regression model. Both of these estimators need an initial estimator of the regression parameter vector.
Susarla, V., Koul, H. L.
core
A Simple Nonparametric Least-Squares-Based Causal Inference for Heterogeneous Treatment Effects. [PDF]
Zhang Y +5 more
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Asymptotic properties of a conditional quantile estimator with randomly truncated data
Let be a response variable that is subject to left-truncation by a variable . We consider the problem of estimating its conditional quantile function given a vector of covariates . We derive almost sure (a.s.) consistency and asymptotic normality results
Poulin, Nicolas +2 more
core
Inverse-Probability-Weighted Wavelet Estimation of Regression Derivatives Under Missing-at-Random Responses for Stationary Ergodic Processes. [PDF]
Bouzebda S, Didi S.
europepmc +1 more source
A difference-based approach in the partially linear model with dependent errors. [PDF]
Zeng Z, Liu X.
europepmc +1 more source

