Hughes John, Shastry Shankar, Hancock William O, Fricks John
Division of Biostatistics, University of Minnesota, Minneapolis, MN55455, USA.
J Agric Biol Environ Stat. 2013 Jun 1;18(2):204-217. doi: 10.1007/s13253-013-0131-4.
We show that, for a wide range of models, the empirical velocity of processive motor proteins has a limiting Pearson type VII distribution with finite mean but infinite variance. We develop maximum likelihood inference for this Pearson type VII distribution. In two simulation studies, we compare the performance of our MLE with the performance of standard Student's -based inference. The studies show that incorrectly assuming normality (1) can lead to imprecise inference regarding motor velocity in the one-sample case, and (2) can significantly reduce power in the two-sample case. These results should be of interest to experimentalists who wish to engineer motors possessing specific functional characteristics.
我们表明，对于广泛的模型，进行性运动蛋白的经验速度具有有限均值但无限方差的极限皮尔逊VII型分布。我们针对此皮尔逊VII型分布开发了最大似然推断。在两项模拟研究中，我们将最大似然估计（MLE）的性能与基于标准学生分布的推断性能进行了比较。研究表明，错误地假设正态性（1）在单样本情况下可能导致关于运动速度的推断不准确，并且（2）在两样本情况下可能会显著降低检验功效。这些结果对于希望设计具有特定功能特性的马达的实验人员应该是有意义的。
