Local polynomial variance-function estimation
Technometrics
Lower Bounds for Bayes Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Variance estimation for high-dimensional regression models
Journal of Multivariate Analysis
Rates of convergence for partitioning and nearest neighbor regression estimates with unbounded data
Journal of Multivariate Analysis
Variance function estimation in multivariate nonparametric regression with fixed design
Journal of Multivariate Analysis
On Nonparametric Residual Variance Estimation
Neural Processing Letters
Rates of convergence of nearest neighbor estimation under arbitrary sampling
IEEE Transactions on Information Theory
On the mutual nearest neighbors estimate in regression
The Journal of Machine Learning Research
Hi-index | 0.00 |
In this paper we consider the problem of estimating E[(Y-E[Y|X])^2] based on a finite sample of independent, but not necessarily identically distributed, random variables (X"i,Y"i)"i"="1^M. We analyze the theoretical properties of a recently developed estimator. It is shown that the estimator has many theoretically interesting properties, while the practical implementation is simple.