Jensen C S, Sheehan N
Department of Mathematics and Computer Science, Aalborg University, Denmark.
Biometrics. 1998 Jun;54(2):416-25.
Exact calculations for probabilities on complex pedigrees are computationally intensive and very often infeasible. Markov chain Monte Carlo methods are frequently used to approximate probabilities and likelihoods of interest. However, when a locus with more than two alleles is considered, the underlying Markov chain is not guaranteed to be irreducible and the results of such analyses are unreliable. A method for finding the noncommunicating classes of the Markov chain would be very useful in designing algorithms that can jump between these classes. In this paper, we will examine some existing work on this problem and point out its limitations. We will also comment on the difficulty of developing a useful algorithm.
对于复杂谱系的概率进行精确计算在计算上是密集的，而且通常是不可行的。马尔可夫链蒙特卡罗方法经常被用于近似感兴趣的概率和似然性。然而，当考虑一个具有两个以上等位基因的基因座时，潜在的马尔可夫链不能保证是不可约的，并且此类分析的结果是不可靠的。一种用于找到马尔可夫链的非连通类别的方法在设计能够在这些类别之间跳转的算法时将非常有用。在本文中，我们将研究关于这个问题的一些现有工作并指出其局限性。我们还将评论开发一种有用算法的难度。
