Abstract
A single index model (SIM) summarizes the effects of the explanatory variables X1, ..., Xd within a single variable called the index. As stated at the beginning of Part II, the SIM is one possibility for generalizing the GLM or for restricting the multidimensional regression E(Y|X) to overcome the curse of dimensionality and the lack of interpretability. For more examples of motivating the SIM see Ichimura (1993). Among others, this reference mentions duration, truncated regression (Tobit) and errors-in-variables modeling.
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© 2004 Springer-Verlag Berlin Heidelberg
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Härdle, W., Werwatz, A., Müller, M., Sperlich, S. (2004). Single Index Models. In: Nonparametric and Semiparametric Models. Springer Series in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17146-8_6
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DOI: https://doi.org/10.1007/978-3-642-17146-8_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-62076-8
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