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Linear Regression Analysis - Theory and Computing
Abstract
This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields. Introduction Simple Linear Regression Multiple Linear Regression Detection of Outliers and Influential Observations in Multiple Linear Regression Model Selection Model Diagnostics Extensions of Least Squares Generalized Linear Models Bayesian Linear Regression
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Cited by
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Sujath, R., Chatterjee, J. M., & Hassanien, A. E. (2020) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-020-01827-8 · Cited by 339
Pontes, H. M., Taylor, M., & Stavropoulos, V. (2018) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2017.0609 · Cited by 163
Hoefman, R. J., van Exel, J., & Brouwer, W. B. (2013) · Health and Quality of Life Outcomes · doi:10.1186/1477-7525-11-173 · Cited by 101
Pinchuk, I., Kohen, R., Stuetz, W., Weber, D., Franceschi, C., Capri, M., Hurme, M., Grubeck-Loebenstein, B., Schön, C., Bernhardt, J., et al. (2021) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2021.109061 · Cited by 17
Metadata
- Authors
- Xin, Y., & Su, X. G.
- Venue
- WORLD SCIENTIFIC eBooks
- Publisher
- World Scientific
- Published
- 2009-01-01
- OpenAlex
- W652265168
- Cited by
- 480
- References
- 0
- FWCI
- 1.59
- Type
- book
- Language
- en
- Open access
- closed
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- Xin, Y., & Su, X. G. (2009). Linear Regression Analysis - Theory and Computing. WORLD SCIENTIFIC eBooks. https://doi.org/10.1142/9789812834119
Data sources
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.
