On the Existence of Maximum Likelihood Estimators for Graphical Gaussian Models
On the Existence of Maximum Likelihood Estimators for Graphical Gaussian Models
复制标题
关于图解高斯模型最大似然估计量的存在性
DOI：
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发表时间：
1993
期刊：
影响因子：
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通讯作者：
Søren Ladegaard Buhl
中科院分区：
文献类型：
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作者：
Søren Ladegaard Buhl
在图形高斯模型中，众所周知，如果重复的数量至少与变量的数量一样大，则最大似然估计以概率1存在。在本文中，我们处理的情况下，较少的重复。对于两个重复的无弦p-圈，我们证明了极大似然估计的存在概率严格在0和1之间。(In在p = 4且独立的情况下，概率为2/3。
In graphical Gaussian models, it is well known that the maximum likelihood estimator exists with probability one if the number of replicates is at least as large as the number of variates. In this paper we deal with the case of fewer replicates. For the chordless p-cycle with two replicates, we prove that the maximum likelihood estimator exists with probability strictly between zero and one. (In case of p = 4 and independence, the probability is 2/3.)