论文标题
使用k-vector随机采样
Random Sampling using k-vector
论文作者
论文摘要
这项工作介绍了两种基于K-Vector方法的规定非线性分布的随机数生成的新技术。第一种方法是基于使用最佳k-vector的反变换采样来通过反转累积分布来生成样品的采样。第二种方法通过在先前通过使用K-Vector大规模反转构建的预先生成的大型数据库中进行随机搜索来生成样品。两种方法均显示适合大量生成随机样品。提供了示例以阐明这些方法。
This work introduces two new techniques for random number generation with any prescribed nonlinear distribution based on the k-vector methodology. The first approach is based on inverse transform sampling using the optimal k-vector to generate the samples by inverting the cumulative distribution. The second approach generates samples by performing random searches in a pre-generated large database previously built by massive inversion of the prescribed nonlinear distribution using the k-vector. Both methods are shown suitable for massive generation of random samples. Examples are provided to clarify these methodologies.
