Random Effect and Latent Variable Model Selection
Random effects and latent variable models are broadly used in analyses of multivariate data. These models can accommodate high dimensional data having a variety of measurement scales. Methods for model selection and comparison are needed in conducting hypothesis tests and in building sparse predicti...
| Corporate Author: | SpringerLink (Online service) |
|---|---|
| Other Authors: | Dunson, David B. (Editor) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2008.
|
| Series: | Lecture Notes in Statistics,
192 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
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