Evaluating divorce dynamics through ODE modeling and statistical hypothesis testing
Abstract To understand divorce, a quantitative method is used which considers the social, economic, and psychological elements impacting marital changes. We introduce a model based on Ordinary Differential Equations (ODEs), combined with statistical hypothesis testing, to examine divorce trends over...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-07205-9 |
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| Summary: | Abstract To understand divorce, a quantitative method is used which considers the social, economic, and psychological elements impacting marital changes. We introduce a model based on Ordinary Differential Equations (ODEs), combined with statistical hypothesis testing, to examine divorce trends over two decades using longitudinal, real-world data. Model parameters are estimated through nonlinear least-squares fitting, resulting in a high predictive accuracy $$(R^2 = 0.9878)$$ ( R 2 = 0.9878 ) , indicating the model’s dependability. Robustness is further confirmed through residual analysis, Durbin-Watson (DW), Jarque-Bera (JB) statistics, and normality testing. Consequently, the results provide important understandings of how divorce trends are changing, supplying a data-supported basis for policymakers and researchers to develop helpful intervention strategies to foster marital stability and lower divorce rates. |
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| ISSN: | 3004-9261 |