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...
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2008.
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| Edition: | 1st ed. 2008. |
| Series: | Lecture Notes in Statistics,
192 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-0-387-76721-5 |
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