In this paper, the task of identifying outliers in exponential samples is treated conceptionally in the sense of Davies and Gather (1989, 1993) by means of a so-called outlier region. In case of an exponential distribution, an empirical approximation of such a region - also called an outlier identifier - is mainly dependent on some estimator of the unknown scale parameter. The worst-case behaviour of several reasonable outlier identifiers is investigated thoroughly and it is shown that only robust estimators of scale should be used to construct reliable identifiers. These fifindings lead to the recommendation of an outlier identifier that is based on a standardized version of the sample median
Outliers are often ubiquitous in surveys that involve linear measurements. Knowing that the presence...
Abstract: Zerbet and Nikulin presented the new statistic Z k for detecting outliers in exponential d...
This paper considers how best to identify statistical outliers in psychophysical datasets, where the...
In this paper, the task of identifying outliers in exponential samples is treated conceptionally in ...
In this paper we consider the problem of identifying outliers in exponential samples with stepwise p...
In this paper we discuss the distribution of the ratio of the maximum and the appropriately standard...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
In this paper, we consider one-step outlier identifiation rules for multivariate data, generalizing ...
In investigations on the behaviour of robust estimators, typically their consistency and their asymp...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
Outliers are often ubiquitous in surveys that involve linear measurements. Knowing that the presence...
Abstract: Zerbet and Nikulin presented the new statistic Z k for detecting outliers in exponential d...
This paper considers how best to identify statistical outliers in psychophysical datasets, where the...
In this paper, the task of identifying outliers in exponential samples is treated conceptionally in ...
In this paper we consider the problem of identifying outliers in exponential samples with stepwise p...
In this paper we discuss the distribution of the ratio of the maximum and the appropriately standard...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
In this paper, we consider one-step outlier identifiation rules for multivariate data, generalizing ...
In investigations on the behaviour of robust estimators, typically their consistency and their asymp...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investig...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
One approach to identifying outliers is to assume that the outliers have a different distribution fr...
In their paper, Davies and Gather (1993) formalized the task of outlier identification, considering ...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
Outliers are often ubiquitous in surveys that involve linear measurements. Knowing that the presence...
Abstract: Zerbet and Nikulin presented the new statistic Z k for detecting outliers in exponential d...
This paper considers how best to identify statistical outliers in psychophysical datasets, where the...