Threshold selection is a key aspect in extreme values analysis, especially when the sample size is small. The main idea underpinning this work is that extreme observations are assumed to be outliers of a specified parametric model. We propose a threshold selection method based on outlier detection using a suitable measure of surprise
Novelty detection, one-class classification, or outlier detection, is typically employed for analysi...
It is our aim in this presentation to give a brief overview about several tests pub-lished in the co...
A new approach is suggested for choosing the threshold when fitting the Hill estimator of a tail exp...
Threshold selection is a key aspect in extreme values analysis, especially when the sample size is s...
Statistical extreme value theory is concerned with the use of asymptotically motivated models to des...
Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behav...
Extreme value theory (EVT) is a branch of statistics which concerns the distributions of data of unu...
This paper proposes several test statistics to detect additive or innovative outliers in adaptive fu...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
We study a variant of the thresholding bandit problem (TBP) in the context of outlier detection, whe...
Abstract. This article is concerned with detecting additive outliers using extreme value methods. Th...
This article is concerned with detecting additive outliers using extreme value methods. The test rec...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
This article is concerned with detecting additive outliers using extreme value methods. The test rec...
Given a data set arising from a series of observations, an outlier is a value that deviates substant...
Novelty detection, one-class classification, or outlier detection, is typically employed for analysi...
It is our aim in this presentation to give a brief overview about several tests pub-lished in the co...
A new approach is suggested for choosing the threshold when fitting the Hill estimator of a tail exp...
Threshold selection is a key aspect in extreme values analysis, especially when the sample size is s...
Statistical extreme value theory is concerned with the use of asymptotically motivated models to des...
Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behav...
Extreme value theory (EVT) is a branch of statistics which concerns the distributions of data of unu...
This paper proposes several test statistics to detect additive or innovative outliers in adaptive fu...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
We study a variant of the thresholding bandit problem (TBP) in the context of outlier detection, whe...
Abstract. This article is concerned with detecting additive outliers using extreme value methods. Th...
This article is concerned with detecting additive outliers using extreme value methods. The test rec...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
This article is concerned with detecting additive outliers using extreme value methods. The test rec...
Given a data set arising from a series of observations, an outlier is a value that deviates substant...
Novelty detection, one-class classification, or outlier detection, is typically employed for analysi...
It is our aim in this presentation to give a brief overview about several tests pub-lished in the co...
A new approach is suggested for choosing the threshold when fitting the Hill estimator of a tail exp...
DOI
Add to ORKG