Approximating the Sum of Independent Non-Identical Binomial Random Variables
Approximating the Sum of Independent Non-Identical Binomial Random Variables
复制标题
近似独立不同二项式随机变量之和
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
T. Quertermous
中科院分区：
文献类型：
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作者：
Boxiang Liu;T. Quertermous
在基因组学、医疗保健和运筹学等领域中，经常会遇到独立的、不同的二项随机变量之和的分布。密度和分布的解析解通常很难找到，也很难计算。已发展出几种近似分布的方法，其中之一是鞍点近似。然而，鞍点近似的实现并不是平凡的，据我们所知，R包仍然缺乏。在本文中，我们在extbf{sinib}程序包中实现了鞍点近似。我们提供两个例子来说明它的用法。一个例子使用模拟数据，而另一个例子使用真实世界的医疗数据。Extbf{sinib}包解决了近似独立的非全等二项式之和的理论和实现之间的差距。
The distribution of sum of independent non-identical binomial random variables is frequently encountered in areas such as genomics, healthcare, and operations research. Analytical solutions to the density and distribution are usually cumbersome to find and difficult to compute. Several methods have been developed to approximate the distribution, and among these is the saddlepoint approximation. However, implementation of the saddlepoint approximation is non-trivial and, to our knowledge, an R package is still lacking. In this paper, we implemented the saddlepoint approximation in the extbf{sinib} package. We provide two examples to illustrate its usage. One example uses simulated data while the other uses real-world healthcare data. The extbf{sinib} package addresses the gap between the theory and the implementation of approximating the sum of independent non-identical binomials.