In this paper we study a class of exponential family on permutations, which includes some of the commonly studied Mallows models. We show that the pseudo-likelihood estimator for the natural parameter in the exponential family is asymptotically normal, with an explicit variance. Using this, we are able to construct asymptotically valid confidence intervals. We also show that the MLE for the same problem is consistent everywhere, and asymptotically normal at the origin. In this special case, the asymptotic variance of the cost effective pseudo-likelihood estimator turns out to be the same as the cost prohibitive MLE. To the best of our knowledge, this is the first inference result on permutation models including Mallows models, excluding the very special case of Mallows model with Kendall's Tau.
翻译:在本文中,我们研究了排列指数族的一类,其中包括一些常见的Mallows模型。我们显示出指数族中自然参数的伪似然估计量渐近正态,具有明确的方差。利用这一点,我们能够构建渐近有效的置信区间。我们还表明,同样问题的MLE在任何地方都是一致的,并在原点处渐近正态。在这种特殊情况下,经济有效的伪似然估计器的渐近方差结果与代价高昂的MLE相同。据我们所知,这是关于包括Mallows模型在内的排列模型的第一个推理结果,排除了Kendall的Tau Mallows模型这个非常特殊的情况。