Tailfree and Neutral Random Probabilities and Their Posterior Distributions
Tailfree and Neutral Random Probabilities and Their Posterior Distributions
The random distribution function $F$ and its law is said to be neutral to the right if $F(t_1), \lbrack F(t_2) - F(t_1) \rbrack/\lbrack 1 - F(t_1)\rbrack, \cdots, \lbrack F(t_k) - F(t_{k-1}) \rbrack/\lbrack 1 - F(t_{k-1}) \rbrack$ are independent whenever $t_1 < \cdots < t_k$. The posterior distribution of a random …