Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data
classification
📊 stat.ME
keywords
distributionfunctiondataheteroskedasticmissingnonparametricregressionasymptotically
read the original abstract
A residual-based empirical distribution function is proposed to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and this estimator is shown to be asymptotically most precise.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.