论文标题
来自马尔可夫链的离散分布
Discrete distributions from a Markov chain
论文作者
论文摘要
从篮球模型得出的离散时间随机过程用于概括任何离散分布。广义分布可以比父分布多一个或两个参数。从二项式，泊松和负二项式分布中得出的那些人可能会被散布或过度分散。平均值可以简单地用模型参数表示，从而推断出平均直率。概率可以快速计算，从而可以基于可能性的推理。随机数生成也很简单。描述了一些新分布的属性，并用示例说明了它们的使用。
A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from binomial, Poisson and negative binomial distributions can be underdispersed or overdispersed. The mean can be simply expressed in terms of model parameters, thus making inference for the mean straightforward. Probabilities can be quickly computed, enabling likelihood-based inference. Random number generation is also straightforward. The properties of some of the new distributions are described and their use is illustrated with examples.
