Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion
Fires in buildings are significant public safety hazards and can result in fatalities and substantial financial losses. Studies have shown that the socioeconomic makeup of a region can impact the occurrence of building fires. However, existing models based on the classical stepwise regression proced...
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| Format: | Article |
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MDPI AG
2023-05-01
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| Series: | Axioms |
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| Online Access: | https://www.mdpi.com/2075-1680/12/6/524 |
| _version_ | 1797596151387521024 |
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| author | Albertus Untadi Lily D. Li Michael Li Roland Dodd |
| author_facet | Albertus Untadi Lily D. Li Michael Li Roland Dodd |
| author_sort | Albertus Untadi |
| collection | DOAJ |
| description | Fires in buildings are significant public safety hazards and can result in fatalities and substantial financial losses. Studies have shown that the socioeconomic makeup of a region can impact the occurrence of building fires. However, existing models based on the classical stepwise regression procedure have limitations. This paper proposes a more accurate predictive model of building fire rates using a set of socioeconomic variables. To improve the model’s forecasting ability, a backward elimination by robust final predictor error (RFPE) criterion is introduced. The proposed approach is applied to census and fire incident data from the South East Queensland region of Australia. A cross-validation procedure is used to assess the model’s accuracy, and comparative analyses are conducted using other elimination criteria such as <i>p</i>-value, Akaike’s information criterion (AIC), Bayesian information criterion (BIC), and predicted residual error sum of squares (PRESS). The results demonstrate that the RFPE criterion is a more accurate predictive model based on several goodness-of-fit measures. Overall, the RFPE equation was found to be a suitable criterion for the backward elimination procedure in the socioeconomic modeling of building fires. |
| first_indexed | 2024-03-11T02:46:32Z |
| format | Article |
| id | doaj.art-28079bd0fdc941c585865f3278ff737e |
| institution | Directory Open Access Journal |
| issn | 2075-1680 |
| language | English |
| last_indexed | 2024-03-11T02:46:32Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Axioms |
| spelling | doaj.art-28079bd0fdc941c585865f3278ff737e2023-11-18T09:16:17ZengMDPI AGAxioms2075-16802023-05-0112652410.3390/axioms12060524Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error CriterionAlbertus Untadi0Lily D. Li1Michael Li2Roland Dodd3School of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, AustraliaSchool of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, AustraliaSchool of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, AustraliaSchool of Engineering and Technology, Central Queensland University, Rockhampton, QLD 4701, AustraliaFires in buildings are significant public safety hazards and can result in fatalities and substantial financial losses. Studies have shown that the socioeconomic makeup of a region can impact the occurrence of building fires. However, existing models based on the classical stepwise regression procedure have limitations. This paper proposes a more accurate predictive model of building fire rates using a set of socioeconomic variables. To improve the model’s forecasting ability, a backward elimination by robust final predictor error (RFPE) criterion is introduced. The proposed approach is applied to census and fire incident data from the South East Queensland region of Australia. A cross-validation procedure is used to assess the model’s accuracy, and comparative analyses are conducted using other elimination criteria such as <i>p</i>-value, Akaike’s information criterion (AIC), Bayesian information criterion (BIC), and predicted residual error sum of squares (PRESS). The results demonstrate that the RFPE criterion is a more accurate predictive model based on several goodness-of-fit measures. Overall, the RFPE equation was found to be a suitable criterion for the backward elimination procedure in the socioeconomic modeling of building fires.https://www.mdpi.com/2075-1680/12/6/524robust final predictor errorlinear regressionmultiple regressionbackward eliminationpredictive modelingforecasting |
| spellingShingle | Albertus Untadi Lily D. Li Michael Li Roland Dodd Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion Axioms robust final predictor error linear regression multiple regression backward elimination predictive modeling forecasting |
| title | Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion |
| title_full | Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion |
| title_fullStr | Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion |
| title_full_unstemmed | Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion |
| title_short | Modeling Socioeconomic Determinants of Building Fires through Backward Elimination by Robust Final Prediction Error Criterion |
| title_sort | modeling socioeconomic determinants of building fires through backward elimination by robust final prediction error criterion |
| topic | robust final predictor error linear regression multiple regression backward elimination predictive modeling forecasting |
| url | https://www.mdpi.com/2075-1680/12/6/524 |
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