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- Title
A Note on the Adaptive LASSO for Zero-Inflated Poisson Regression.
- Authors
Banerjee, Prithish; Garai, Broti; Mallick, Himel; Chowdhury, Shrabanti; Chatterjee, Saptarshi
- Abstract
We consider the problem of modelling count data with excess zeros using Zero-Inflated Poisson (ZIP) regression. Recently, various regularization methods have been developed for variable selection in ZIP models. Among these, EM LASSO is a popular method for simultaneous variable selection and parameter estimation. However, EM LASSO suffers from estimation inefficiency and selection inconsistency. To remedy these problems, we propose a set of EM adaptive LASSO methods using a variety of data-adaptive weights. We show theoretically that the new methods are able to identify the true model consistently, and the resulting estimators can be as efficient as oracle. The methods are further evaluated through extensive synthetic experiments and applied to a German health care demand dataset.
- Subjects
ZERO-inflated probability distribution; POISSON regression; PARAMETER estimation; EXPECTATION-maximization algorithms; REGULARIZATION parameter
- Publication
Journal of Probability & Statistics, 2018, p1
- ISSN
1687-952X
- Publication type
Article
- DOI
10.1155/2018/2834183