Publication Type : Journal Article
Campus : Coimbatore
School : School of Physical Sciences
Year : 2025
Abstract : Data depth procedures are statistical methods used to measure the centrality or depth of a point within a multivariate dataset. These procedures provide a way to quantify how deep or outlying a point is relative to the overall distribution of the data. This study explores various data depth procedures to find reliable location estimations in cases like with and without outliers. In this paper, various depth procedures, such as Mahalanobis depth, Halfspace depth, Euclidean depth, Simplicial depth, and Projection depth, are studied and compared. The efficiency of these depth functions is evaluated using real datasets and simulation studies with R software.
Cite this Research Publication : Dr. Kalaivani S. , A Significant Study on Robust Measure of Location Parameters Using Data Depth Approaches 2025