Abstract
Linear regression is based on the premise that the model is linear in parameters; a set of methods called “generalized linear models” relies on transformations of models that make them linear in parameters; however, the solution to estimation equations is often dependent on numerical approximations; Some more common and important generalized linear models are presented.
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Pardo, S. (2020). Generalized Linear Models. In: Statistical Analysis of Empirical Data. Springer, Cham. https://doi.org/10.1007/978-3-030-43328-4_9
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DOI: https://doi.org/10.1007/978-3-030-43328-4_9
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