Hierarchical Mixtures-of-experts for Exponential Family Regression Models: Approximation and Maximum Likelihood Estimation

@inproceedings{Jiang1999HierarchicalMF,
  title={Hierarchical Mixtures-of-experts for Exponential Family Regression Models: Approximation and Maximum Likelihood Estimation},
  author={Wenxin Jiang and Martin A. Tanner},
  year={1999}
}
2 We consider hierarchical mixtures-of-experts (HME) models where exponential family regression models with generalized linear mean functions of the form (+ x T) are mixed. Here () is the inverse link function. Suppose the true response y follows an exponential family regression model with mean function belonging to a class of smooth functions of the form (h(x)) where h() 2 W 1 2;K 0 (a Sobolev class over 0; 1] s). It is shown that the HME probability density functions can approximate the true… CONTINUE READING
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Hierarchical mixtures-of-experts for exponential family

  • W. Jiang, M. A. Tanner
  • 1998
Highly Influential
6 Excerpts

On the approximation rate of hierarchical mixtures - of - experts for generalized linear models

  • M. A. Tanner
  • 1999
Highly Influential
4 Excerpts

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