Bootstrap bandwidth selection method for local linear estimator in exponential family models

K. Zychaluk

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Bootstrap bandwidth selection method for local linear estimator in exponential family models

机译：指数族模型中局部线性估计量的自举带宽选择方法

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Many biological experiments involve data whose distribution belongs to the exponential family. Such data are often analysed using generalised linear models but this method requires specification of the link function which can have strong influence on the resulting estimate. Instead a local method based on quasi-likelihood can be used, but the choice of the smoothing parameter is crucial for its performance. A bootstrap bandwidth selection method is proposed and shown to be consistent. Examples of application to data from biological and psychometric experiments are given.

机译：许多生物学实验都涉及其分布属于指数族的数据。通常使用广义线性模型来分析此类数据，但是此方法需要指定链接函数，这可能会对所得的估计产生重大影响。相反，可以使用基于拟似然的局部方法，但是平滑参数的选择对其性能至关重要。提出了一种引导带宽选择方法，该方法显示出一致性。给出了应用到生物学和心理测量实验数据的例子。

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来源
《Journal of nonparametric statistics》 |2014年第2期|305-319|共15页
作者
K. Zychaluk;
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作者单位

Department of Mathematical Sciences, University of Liverpool, Mathematical Sciences Building, Peach Street, Liverpool L69 7ZL, UK;

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原文格式 PDF
正文语种 eng
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关键词
bandwidth selection; bootstrap; local linear estimation;

机译：带宽选择;引导程序局部线性估计;

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Bootstrap bandwidth selection method for local linear estimator in exponential family models

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