Abstract
A particular semiparametric model of interest is the generalized partial linear model (GPLM) which extends the generalized linear model (GLM) by a nonparametric component.
The paper reviews different estimation procedures based on kernel methods as well as test procedures on the correct specification of this model (vs. a parametric generalized linear model). Simulations and an application to a data set on East–West German migration illustrate similarities and dissimilarities of the estimators and test statistics.
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Müller, M. Estimation and testing in generalized partial linear models—A comparative study. Statistics and Computing 11, 299–309 (2001). https://doi.org/10.1023/A:1011981314532
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DOI: https://doi.org/10.1023/A:1011981314532