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Goodness-of-link tests for multivariate regression models

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  • José M. R. Murteira

Abstract

This note presents an approximation to multivariate regression models which is obtained from a first-order series expansion of the multivariate link function. The proposed approach yields a variable-addition approximation of regression models that enables a multivariate generalization of the well-known goodness-of-link specification test, available for univariate generalized linear models. Application of this general methodology is illustrated with models of multinomial discrete choice and multivariate fractional data, in which context it is shown to lead to well-established approximation and testing procedures.

Suggested Citation

  • José M. R. Murteira, 2016. "Goodness-of-link tests for multivariate regression models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(24), pages 7367-7375, December.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:24:p:7367-7375
    DOI: 10.1080/03610926.2014.980518
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    Cited by:

    1. Oyarzo, Mauricio & Paredes, Dusan, 2021. "The impact of mining taxes on public education: Evidence for mining municipalities in Chile," Resources Policy, Elsevier, vol. 70(C).

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