Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression
We advocate linear regression by modeling the error term through a finite mixture of asymmetric Laplace distributions (ALDs). The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum likelihood estimatio...
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Main Authors: | Wang, Shangshan, Xiang, Liming |
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Other Authors: | School of Physical and Mathematical Sciences |
Format: | Article |
Language: | English |
Published: |
2017
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/83377 http://hdl.handle.net/10220/43534 |
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Institution: | Nanyang Technological University |
Language: | English |
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