Although there is an extensive literature on the upper bound for cumulative standard normal distribution, there are relatively not sharp for all values of the interested argument x. The aim of this paper is to establish a sharp upper bound for standard normal distribution function, in the sense that its maximum absolute difference from phi(x) is less than for all values of x. The established bound improves the well-known Polya upper bound and it can be used as an approximation for Phi(x) itself with a very satisfactory accuracy. Numerical comparisons between the proposed upper bound and some other existing upper bounds have been achieved, which show that the proposed bound is tighter than alternative bounds found in the literature.
翻译:虽然关于累积标准正态分布的上限文献很多,但有关参数 x 的所有值相对并不尖锐。 本文件的目的是为标准正态分布功能建立一个尖锐的上限,即它与hi(x)的最大绝对差小于X的所有值。 确定的下限改进了众所周知的Polina上限,并且可以非常精确地用作Phi(x)本身的近似值。 在拟议的上限和其他一些现有的上限之间实现了数值比较,这表明拟议的约束比文献中发现的替代界限更紧。