Mixing distributions on a Markov chain
研究了一个简单齐次连续时间马尔可夫链，其中强度被随机变量替代，通过混合变量的联合拉普拉斯变换表达完整强度函数，并讨论了过程的其他性质及多元混合分布的构造方法。
I consider a simple homogeneous, time-continuous Markov chain where the inten- sities are substituted by random variables (each being the product of a parameter and a mixing variable). The dynamic structure of the resulting process may be described by complete intensity functions given the entire past. I show how these functions can be expressed by means of the joint Laplace transform of the mixing variables. Some further properties of the process are also dis- cussed. I then consider various ways to construct non-negative multivariate mixing distributions with a known Laplace transform. Finally some computations are made for a two-state Markov chain.