Outlier detection in spatial error models using modified thresholding-based iterative procedure for outlier detection approach.

ABSTRACT:

Background

Outliers, data points that significantly deviate from the norm, can have a substantial impact on statistical inference and provide valuable insights in data analysis. Multiple methods have been developed for outlier detection, however, almost all available approaches fail to consider the spatial dependence and heterogeneity in spatial data. Spatial data has diverse formats and semantics, requiring specialized outlier detection methodology to handle these unique properties. For now, there is limited research exists on robust spatial outlier detection methods designed specifically under the spatial error model (SEM) structure.

Method

We propose the Spatial-Θ-Iterative Procedure for Outlier Detection (Spatial-Θ-IPOD), which utilizes a mean-shift vector to identify ou

SUBMITTER: Cai J 

PROVIDER: S-EPMC11323683 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature