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Orthodox BLUP versus h-likelihood methods for inferences about random effects in Tweedie mixed models

机译:正统BLUP与h似然法推论Tweedie混合模型中的随机效应

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摘要

Recently, the orthodox best linear unbiased predictor (BLUP) method was introduced for inference about random effects in Tweedie mixed models. With the use of h-likelihood, we illustrate that the standard likelihood procedures, developed for inference about fixed unknown parameters, can be used for inference about random effects. We show that the necessary standard error for the prediction interval of the random effect can be computed from the Hessian matrix of the h-likelihood. We also show numerically that the h-likelihood provides a prediction interval that maintains a more precise coverage probability than the BLUP method.
机译:最近,引入了正统最佳线性无偏预测器(BLUP)方法来推断Tweedie混合模型中的随机效应。通过使用h似然,我们说明了为推断固定的未知参数而开发的标准似然过程可用于推断随机效应。我们表明,可以从h可能性的Hessian矩阵中计算出随机效应预测间隔所需的标准误差。我们还从数字上显示,h可能性提供了一个预测间隔,该预测间隔比BLUP方法保持更精确的覆盖概率。

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