Abstract
When the form of a regression relationship with respect to some but not all of the explanatory variables is unknown, the statistician is caught in a quandary. Should parametric models be abandoned altogether, thus losing the opportunity of estimating parameters of real interest and sacrificing efficiency in estimation and prediction, or should the extraneous variables be forced into a parametric model by imposing a possibly inappropriate functional form without adequate justification?
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Green, P.J., Yandell, B.S. (1985). Semi-parametric Generalized Linear Models. In: Gilchrist, R., Francis, B., Whittaker, J. (eds) Generalized Linear Models. Lecture Notes in Statistics, vol 32. Springer, New York, NY. https://doi.org/10.1007/978-1-4615-7070-7_6
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DOI: https://doi.org/10.1007/978-1-4615-7070-7_6
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