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An application of the local influence approach to ridge regression

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  • Nedret Billor

Abstract

In this study, the method of local influence, which was introduced by Cook as a general tool for assessing the influence of local departures from the underlying assumptions, is applied to ridge regression, by defining the maximum pseudo-likelihood ridge estimator obtained using the augmentation approach, because this method is suitable for likelihood-based models. In addition, an alternative local influence approach suggested by Billor and Loynes is applied to ridge regression. A comparison of these approaches and an example are given.

Suggested Citation

  • Nedret Billor, 1999. "An application of the local influence approach to ridge regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(2), pages 177-183.
    • Handle: RePEc:taf:japsta:v:26:y:1999:i:2:p:177-183
    DOI: 10.1080/02664769922511
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    Cited by:

    1. Michelli Barros & Manuel Galea & Víctor Leiva & Manoel Santos-Neto, 2018. "Generalized Tobit models: diagnostics and application in econometrics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(1), pages 145-167, January.
    2. Hadi Emami & Mostafa Emami, 2016. "New influence diagnostics in ridge regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(3), pages 476-489, March.
    3. Carolina Marchant & Víctor Leiva & Francisco José A. Cysneiros & Juan F. Vivanco, 2016. "Diagnostics in multivariate generalized Birnbaum-Saunders regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2829-2849, November.
    4. Yonghui Liu & Ruochen Sang & Shuangzhe Liu, 2017. "Diagnostic analysis for a vector autoregressive model under Student-super-′s t-distributions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 71(2), pages 86-114, May.

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