Efficient parameter-estimating algorithms for symmetry-motivated models: Econometrics and beyond
© 2018, Springer International Publishing AG. It is known that symmetry ideas can explain the empirical success of many non-linear models. This explanation makes these models theoretically justified and thus, more reliable. However, the models remain non-linear and thus, identification or the model’...
محفوظ في:
| المؤلفون الرئيسيون: | , , , |
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| التنسيق: | Book Series |
| منشور في: |
2018
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| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85038827524&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/43923 |
| الوسوم: |
إضافة وسم
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| المؤسسة: | Chiang Mai University |
| الملخص: | © 2018, Springer International Publishing AG. It is known that symmetry ideas can explain the empirical success of many non-linear models. This explanation makes these models theoretically justified and thus, more reliable. However, the models remain non-linear and thus, identification or the model’s parameters based on the observations remains a computationally expensive nonlinear optimization problem. In this paper, we show that symmetry ideas can not only help to select and justify a nonlinear model, they can also help us design computationally efficient almost-linear algorithms for identifying the model’s parameters. |
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