{"id":22985,"date":"2025-12-14T17:52:09","date_gmt":"2025-12-14T17:52:09","guid":{"rendered":"https:\/\/scientificassociation.org\/?post_type=journal-paper&#038;p=22985"},"modified":"2025-12-14T18:15:39","modified_gmt":"2025-12-14T18:15:39","slug":"a-novel-robust-m-estimator-for-the-random-coefficients-regression-model-simulation-and-its-application-in-energy-management-systems","status":"publish","type":"journal-paper","link":"https:\/\/scientificassociation.org\/ar\/journal-paper\/a-novel-robust-m-estimator-for-the-random-coefficients-regression-model-simulation-and-its-application-in-energy-management-systems\/","title":{"rendered":"A Novel Robust M-Estimator for the Random-Coefficients Regression Model: Simulation and Its Application in Energy Management Systems"},"content":{"rendered":"<div class=\"padding_abstract justify ltr\">A random coefficient regression (RCR) model refers to a statistical model that incorporates random coefficients into degradation models, typically assumed to be normally distributed. \u00a0An RCR model is a special type of panel data model. The RCR model provides a wide range of consequences for situations involving decision-making difficulties. The classical estimation methods for the RCR model perform well without outliers, but their performance degrades in the presence of outliers. To this end, this paper proposes a novel robust M-estimator with different objective functions and compares these with the non-robust (classical) estimators. The proposed robust M-estimators provide stable and reliable results even when outliers are present. A Monte Carlo simulation study and an empirical application to energy management systems were conducted to evaluate the performance of the non-robust RCR classical pooling (RCRCP) estimator, RCR mean group (RCRMG) estimator, and RCR Swamy\u2019s (RCRSW) estimator, with the proposed robust M-estimators: RCR Huber (RCRHU), RCR Hampel (RCRHM), and RCR Bisquare (RCRBI). The findings from the simulation and application indicate that the proposed robust M-estimators outperform the non-robust estimators in the presence of outliers in the RCR model. Furthermore, the RCRBI estimator is more efficient than the other proposed robust M-estimators.<\/div>\n","protected":false},"featured_media":22987,"template":"","meta":{"_acf_changed":false},"journal-name":[218],"paper-tag":[224,223],"class_list":["post-22985","journal-paper","type-journal-paper","status-publish","has-post-thumbnail","hentry","journal-name-cjmss","paper-tag-no-2","paper-tag-vol-4"],"acf":[],"_links":{"self":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper\/22985","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper"}],"about":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/types\/journal-paper"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media\/22987"}],"wp:attachment":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media?parent=22985"}],"wp:term":[{"taxonomy":"journal-name","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-name?post=22985"},{"taxonomy":"paper-tag","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/paper-tag?post=22985"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}