Multivariate outlier detection in exploration geochemistry
โ Scribed by Peter Filzmoser; Robert G. Garrett; Clemens Reimann
- Book ID
- 113510852
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 813 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0098-3004
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Multivariate time series (MTS) samples which differ significantly from other MTS samples are referred to as outlier samples. In this paper, an algorithm designed to efficiently detect the top n outlier samples in MTS dataset, based on Solving Set, is proposed. An extended Frobenius Norm is used to c
This paper deals with the problem of identifying and testing a number of extreme sample elements ( t = !. 2. 3 and ,1) as significant outliers in a sample of size n from a K-dimensional normal distribution with unknown parameters. Accommodation of detected outliers is effected through outlier-robust