Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kalaivani, S. Title A name given to the resource A SIGNIFICANT STUDY ON ROBUST MEASURE OF LOCATION PARAMETERS USING DATA DEPTH APPROACHES Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Reliability: Theory and Applications;Volume;20;Issue;1;pp.573-579 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.24412/1932-2321-2025-182-573-579" target="_blank" rel="noreferrer noopener">https://doi.org/10.24412/1932-2321-2025-182-573-579</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105001163827?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105001163827?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Kalaivani S., Department of Statistics and Data Science, Christ University, Bangalore, India Description An account of the resource 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. 2025, Gnedenko Forum. All rights reserved. Subject The topic of the resource data depth; inference; outliers; robust procedures Publisher An entity responsible for making the resource available Gnedenko Forum Relation A related resource ISSN: 19322321; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online