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Measurement Error in Nonlinear Models
Abstract
It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
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Cited by
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DNA methylation arrays as surrogate measures of cell mixture distribution
Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., Wiencke, J. K., & Kelsey, K. T. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-86 · Cited by 3,175
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Frequency ratio measurements at 18-digit accuracy using an optical clock network
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Metadata
- Authors
- Carroll, R. J., Ruppert, D., Stefanski, L. A., & Crainiceanu, C. M.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2006-06-21
- OpenAlex
- W4302338619
- Cited by
- 2,116
- References
- 0
- FWCI
- 11.04
- Type
- book
- Language
- en
- Open access
- closed
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- Carroll, R. J., Ruppert, D., Stefanski, L. A., & Crainiceanu, C. M. (2006). Measurement Error in Nonlinear Models. Chapman & Hall/CRC eBooks. https://doi.org/10.1201/9781420010138
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.