The normal or Gaussian distribution plays a prominent role in almost all fields of science. However, it is well known that the Gauss (or Euler--Poisson) integral over a finite boundary, as it is necessary for instance for the error function or the cumulative distribution of the normal distribution, cannot be expressed by analytic functions. This is proven by the Risch algorithm. Still, there are proposals for approximate solutions. In this paper, we give a new solution in terms of normal distributions by applying a geometric procedure iteratively to the problem.
翻译:正常分布或高斯分布在几乎所有科学领域都起着突出作用。然而,众所周知,由于对错误函数或正常分布的累积分布等必要,对有限边界构成的高斯人(或欧勒-普瓦松人)无法用分析函数来表示。这在Risch算法中得到了证明。然而,仍然有一些关于近似解决方案的建议。在本文中,我们通过对问题进行迭接的几何程序,在正常分布方面给出了新的解决方案。