We develop a computationally efficient estimation procedure via a two-layer EM algorithm, where the first layer EM algorithm incorporates missing information.
We have developed an estimation procedure implemented through a two-layer EM algorithm, which includes two nested EM algorithms owing to the facts of a mixture ...
The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum ...
The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum likeli ...
Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression. June 2017; Computational Statistics & Data Analysis ...
[PDF] Two-layer EM algorithm for ALD mixture regression models: A ...
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This article presents a sufficient and necessary condition for the variable selection of the lasso quantile regression to enjoy the consistent property and ...
The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum ...
The model expands the flexibility of linear regression to account for heterogeneity among data and allows us to establish the equivalence between maximum ...
Title: Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression. Authors: Wang, Shangshan
Bibliographic details on Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression.