In this paper we propose an unbiased Monte Carlo maximum likelihood estimator for discretely observed Wright-Fisher diffusions. Our approach is based on exact simulation techniques that are of special interest for diffusion processes defined on a bounded domain, where numerical methods typically fail to remain within the required boundaries. We start by building unbiased maximum likelihood estimators for scalar diffusions and later present an extension to the multidimensional case. Consistency results of our proposed estimator are also presented and the performance of our method is illustrated through a numerical example.
翻译:在本文中,我们建议为离散观测的Wright-Fisher扩散建立一个不带偏见的Monte Carlo最大可能性估计器,我们的方法以精确的模拟技术为基础,这些技术对于在封闭域界定的传播过程具有特殊意义,因为数字方法通常不能保持在所需的界限之内。我们首先为天平扩散建立没有偏见的最大可能性估计器,然后对多层面案例进行扩展。我们提议的天线测量仪的一致结果也得到介绍,我们方法的性能通过数字示例加以说明。</s>