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 Book Chapter Faculty Publications- Book Chapter 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 Jain, Lakshya; Chopra, Puja Title A name given to the resource Hybrid EconometricMachine Learning Models for High- Dimensional Data: Robust Approaches to Anomaly Detection and Inference Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Robust Methods for Anomaly Detection in Econometrics;pp.165-208 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-8297-5.ch006" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-8297-5.ch006</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105031551896?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031551896?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 Jain L., Christ University, India; Chopra P., Christ University, India Description An account of the resource This chapter, according to the authors, looks at making modeling robust and interpretable when faced with complex, irregular, and contaminated data environments. As empirical research continues to move towards larger datasets having numerous variables and high dependency among variables, along with instances of irregular data, traditional models of analysis can no longer be very effective. The chapter looks at the possibility of having a comprehensive modeling approach by integrating concepts of robustness like bounded sensitivity and stability analysis, along with flexible modeling at the analytical and computational levels. A major focus is on finding influential data points, rare observations, and structural breaks during the modeling process and not after the process is complete. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833738299-9; 979-833738297-5; Language A language of the resource English Type The nature or genre of the resource Book chapter 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