{"_buckets": {"deposit": "21bf05ca-21af-46e8-9bc6-cb85d69ad100"}, "_deposit": {"id": "1610", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "1610"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/1610", "sets": ["user-yueco"]}, "communities": ["yueco"], "control_number": "1610", "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "A Simulation Study on Robust Alternatives of Least Squares Regression", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Five methods of regression namely the ordinary least squares, least absolute value, M, least\r median squares and least trimmed squares are applied to the multiple regression model. The\r several distributional assumptions of errors are considered in this study. The required data sets are\r generated by using multiple linear regression models with three explanatory variables. Then, these\r data sets are transformed into outlier contaminated data sets. After that, the performances are\r compared in terms of bias and mean squared errors criteria and then the most suitable estimation\r method is chosen. Same sets of simulated data are used and mean squared errors and bias of these\r methods are compared. It is found that ordinary least squares estimation under a heavy-tailed\r distribution does not yield outlier robust estimates. Indeed, not only with the Gaussian distribution\r but also with the skewed distributions, ordinary least squares estimators collapse in the presence of\r small levels of outlier contamination. The Huber M-estimate and bisquare M-estimate estimate\r have shown to be more appropriate alternatives to the ordinary least squares in heavy-tailed\r distributions whereas the LMS estimates are better choices for skewed data. One best method\r could not be suggested in all situations; however the use of more than one method of exploratory\r data analysis is recommended in practice."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Robust Estimators"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-05-05"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Dr Maw Maw Khin A Simulation study on Robus Alternatives....pdf", "filesize": [{"value": "538 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 538000.0, "url": {"url": "https://meral.edu.mm/record/1610/files/Dr Maw Maw Khin A Simulation study on Robus Alternatives....pdf"}, "version_id": "fdc59110-0d33-4259-bf52-c36f5beeeb71"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "1", "subitem_journal_title": "Yangon University of Economics", "subitem_volume": "6"}]}, "item_1583103147082": {"attribute_name": "Conference papaers", "attribute_value_mlt": [{}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_supervisor(s)": []}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Maw Maw Khin, Dr."}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-11"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "https://ecor.yueco.edu.mm/handle/123456789/621"}, "item_title": "A Simulation Study on Robust Alternatives of Least Squares Regression", "item_type_id": "21", "owner": "1", "path": ["1582965639643"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000001610", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-05"}, "publish_date": "2020-03-05", "publish_status": "0", "recid": "1610", "relation": {}, "relation_version_is_last": true, "title": ["A Simulation Study on Robust Alternatives of Least Squares Regression"], "weko_shared_id": -1}