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Boosting local quasi-likelihood estimators

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Abstract

For likelihood-based regression contexts, including generalized linear models, this paper presents a boosting algorithm for local constant quasi-likelihood estimators. Its advantages are the following: (a) the one-boosted estimator reduces bias in local constant quasi-likelihood estimators without increasing the order of the variance, (b) the boosting algorithm requires only one-dimensional maximization at each boosting step and (c) the resulting estimators can be written explicitly and simply in some practical cases.

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Authors and Affiliations

  1. Graduate School of Environmental Science, Okayama University, Naka 3-1-1, Tsushima, Okayama, 700-8530, Japan

    Masao Ueki & Kaoru Fueda

Authors
  1. Masao Ueki
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  2. Kaoru Fueda
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Correspondence to Masao Ueki.

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Ueki, M., Fueda, K. Boosting local quasi-likelihood estimators. Ann Inst Stat Math 62, 235–248 (2010). https://doi.org/10.1007/s10463-008-0173-5

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  • DOI: https://doi.org/10.1007/s10463-008-0173-5

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