The panel data regression models have become one of the most widely appl...
The presence of outlying observations may adversely affect statistical
t...
We propose a new sampling algorithm combining two quite powerful ideas i...
Density-based minimum divergence procedures represent popular techniques...
We propose a robust variable selection procedure using a divergence base...
In multivariate nonparametric regression the additive models are very us...
A new approach of obtaining stratified random samples from statistically...
In this paper a new family of minimum divergence estimators based on the...
The log-normal distribution is one of the most common distributions used...
We consider the problem of robust inference under the important generali...