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Varying Coefficient Models for Sparse Noise-contaminated Longitudinal Data
In this paper we propose a varying coefficient model for highly sparse longitudinal data that allows for error-prone time-dependent variables and time-invariant covariates. We develop a new estimation procedure, based on covariance representation techniques, that enables effective borrowing of infor...
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| Publié dans: | Stat Sin |
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| Auteurs principaux: | , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2011
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4291232/ https://ncbi.nlm.nih.gov/pubmed/25589822 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5705/ss.2009.328 |
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