Bhattacharya Rabi, Lin Lizhen
Department of Mathematics, The University of Arizona, Tucson, AZ, 85721, USA.
Sankhya Ser B. 2011 May;73(1):144-163. doi: 10.1007/s13571-011-0019-7.
We consider the finite sample performance of a new nonparametric method for bioassay and benchmark analysis in risk assessment, which averages isotonic MLEs based on disjoint subgroups of dosages, and whose asymptotic behavior is essentially optimal (Bhattacharya and Lin (2010)). It is compared with three other methods, including the leading kernel-based method, called , due to Dette et al. (2005) and Dette and Scheder (2010). In simulation studies, the present method, termed , outperforms the in the majority of cases considered, although both methods generally do well. In small samples, NAM and DNP both outperform the MLE.
我们考虑一种用于生物测定和风险评估中基准分析的新非参数方法的有限样本性能，该方法基于剂量的不相交子组对保序极大似然估计（MLE）进行平均，并且其渐近行为本质上是最优的（Bhattacharya和Lin（2010））。它与其他三种方法进行了比较，包括由Dette等人（2005年）以及Dette和Scheder（2010年）提出的领先的基于核的方法。在模拟研究中，本文提出的方法（称为 ）在大多数考虑的情况下优于 ，尽管两种方法总体上表现都不错。在小样本中，NAM和DNP都优于MLE。
