The stationary sampling distribution of a neutral decoupled Moran or Wright–Fisher diffusion with neutral mutations is known to first order for a general rate matrix with small but otherwise unconstrained mutation rates. Using this distribution as a starting point we derive results for maximum likelihood estimates of scaled mutation rates from site frequency data under three model assumptions: a twelve-parameter general rate matrix, a nine-parameter reversible rate matrix, and a six-parameter strand-symmetric rate matrix. The site frequency spectrum is assumed to be sampled from a fixed size population in equilibrium, and to consist of allele frequency data at a large number of unlinked sites evolving with a common mutation rate matrix without selective bias. We correct an error in a previous treatment of the same problem (Burden and Tang, 2017) affecting the estimators for the general and strand-symmetric rate matrices. The method is applied to a biological dataset consisting of a site frequency spectrum extracted from short autosomal introns in a sample of Drosophila melanogaster individuals.

具有中性突变的中性解耦的Moran或Wright-Fisher扩散的静态采样分布对于具有较小但不受限制的突变率的一般速率矩阵而言，已知为一阶。以这种分布为出发点，我们在三种模型假设下，根据站点频率数据得出了按比例缩放的突变率的最大似然估计结果：一个十二参数的一般速率矩阵，一个九参数的可逆速率矩阵以及一个六参数链对称速率矩阵。假定位点频谱是从固定大小的种群中均衡采样的，并且由大量未链接位点的等位基因频率数据组成，这些位点频率随共同的突变率矩阵而发展，而没有选择偏倚。我们更正了先前对同一问题的处理中的错误（Burden和Tang，2017年）影响一般和股对称率矩阵的估计量。该方法应用于生物学数据集，该数据集由从短小常染色体内含子中提取的位点频谱组成果蝇果蝇个体。