论文标题
通用逆高斯分布的发电机
A Generator for Generalized Inverse Gaussian Distributions
论文作者
论文摘要
我们通过将GIG的密度分解为两个组件，为广义反向高斯（GIG）分布提出了一个新的发电机。第一个组件是截短的反伽马密度，以便采样我们改善传统的逆CDF方法。第二个成分是指数PDF和逆伽马CDF的乘积。为了从该准密度中采样，我们开发了一个拒绝采样程序，该过程根据用户指定的拒绝率或所需的截止点数量自适应地调节分段建议密度。由此产生的完整算法具有可控的拒绝率和适度的设置时间。它可以保留参数变化案例和大型样本案例的效率。
We propose a new generator for the generalized inverse Gaussian (GIG) distribution by decomposing the density of GIG into two components. The first component is a truncated inverse Gamma density, in order to sample from which we improve the traditional inverse CDF method. The second component is the product of an exponential pdf and an inverse Gamma CDF. In order to sample from this quasi-density, we develop a rejection sampling procedure that adaptively adjusts the piecewise proposal density according to the user-specified rejection rate or the desired number of cutoff points. The resulting complete algorithm enjoys controllable rejection rate and moderate setup time. It preserves efficiency for both parameter varying case and large sample case.
