In this short note, we consider the problem of estimating multivariate hypergeometric parameters under squared error loss when side information in aggregated data is available. We use the symmetric multinomial prior to obtain Bayes estimators. It is shown that by incorporating the side information, we can construct an improved estimator.
翻译:在这个简短的注释中,我们考虑了在可得到汇总数据的侧面信息时,在方差错误损失下估算多变超几何参数的问题。我们在获得贝耶斯测算器之前,先使用对称的多数值参数。通过纳入侧数信息,我们可以建立一个改进的估测器。