New Perspectives on Linear Calibration
New Perspectives on Linear Calibration
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线性校准的新视角
DOI：
10.1006/jmva.1994.1056
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发表时间：
1994
影响因子：
1.6
通讯作者：
C. Robert
中科院分区：
文献类型：
--
作者：
T. Kubokawa;C. Robert
在单变量校正中，两种标准估计量通常是对立的：经典估计量和逆回归估计量。争议已经遵循这两个估计的使用，我们认为他们从决策理论的角度来看，建立经典估计的不可接受性和逆回归估计的可接受性。后者允许贝叶斯解释，我们还开发了一个完全noninformative研究的校准模型，并推导出一个参考先验，避免了逆回归估计的不一致的缺点。
In univariate calibration, two standard estimators are usually opposed: the classical estimator and the inverse regression estimator. Controversies have followed the use of both estimators and we consider them from a decision-theoretic perspective, establishing the inadmissibility of the classical estimator and the admissibility of the inverse regression estimator. The latter allowing for a Bayesian interpretation, we also develop a fully noninformative study of the calibration model and derive a reference prior which avoids the inconsistency drawbacks of the inverse regression estimator.