Add to ORKGRecent work on robust estimation has led to many procedures, which are easy to formulate and straigh...
High breakdown point, bounded influence and high efficiency at the Gaussian model are desired proper...
Robust statistics, as a concept, probably dates back to the prehistory of statistics. It has, howeve...
Econometrics often deals with data under, from the statistical point of view, non-standard condition...
A preeminent expert in the field explores new and exciting methodologies in the ever-growing field o...
Classic methods in multivariate analysis require the estimat.ion of mean vectors and covariance matr...
We study the problem of performing statistical inference based on robust estimates when the distrib...
Abstract: Robust methods are little applied (although much studied by statisticians). We monitor ver...
We consider the simple measurement error regression model y[subscript] t = [beta][subscript]0 + [bet...
Includes bibliography.This study initially set out to consider the possibility of constructing an ad...
We study the problem of performing statistical inference based on robust esti-mates when the distrib...
The bachelor thesis deals with the aspect of robustness of estimates, everything is dis- cussed in d...
[Δε διατίθεται περίληψη / no abstract available][Δε διατίθεται περίληψη / no abstract available
The properties of the usual one-sample T-statistic under nonnormal universes are investigated using ...
We argue that robust statistics has multiple goals, which are not always aligned. Robust thinking gr...
Recent work on robust estimation has led to many procedures, which are easy to formulate and straigh...
High breakdown point, bounded influence and high efficiency at the Gaussian model are desired proper...
Robust statistics, as a concept, probably dates back to the prehistory of statistics. It has, howeve...
Econometrics often deals with data under, from the statistical point of view, non-standard condition...
A preeminent expert in the field explores new and exciting methodologies in the ever-growing field o...
Classic methods in multivariate analysis require the estimat.ion of mean vectors and covariance matr...
We study the problem of performing statistical inference based on robust estimates when the distrib...
Abstract: Robust methods are little applied (although much studied by statisticians). We monitor ver...
We consider the simple measurement error regression model y[subscript] t = [beta][subscript]0 + [bet...
Includes bibliography.This study initially set out to consider the possibility of constructing an ad...
We study the problem of performing statistical inference based on robust esti-mates when the distrib...
The bachelor thesis deals with the aspect of robustness of estimates, everything is dis- cussed in d...
[Δε διατίθεται περίληψη / no abstract available][Δε διατίθεται περίληψη / no abstract available
The properties of the usual one-sample T-statistic under nonnormal universes are investigated using ...
We argue that robust statistics has multiple goals, which are not always aligned. Robust thinking gr...
Recent work on robust estimation has led to many procedures, which are easy to formulate and straigh...
High breakdown point, bounded influence and high efficiency at the Gaussian model are desired proper...
Robust statistics, as a concept, probably dates back to the prehistory of statistics. It has, howeve...