Examples:
- uniform(0,1) calls the function jstat.uniform.sample(0,1)
- exponential(1) calls the function jstat.exponential.sample(1)
- weibull(1,2) calls the function jstat.weibull.sample(1,2)
- gamma(2,1) calls the function jstat.gamma.sample(2,1)

Let $\zeta >0$ be a random variable (target distribution). For $N\in \mathbb N$ let $$T_1 \leq \ldots \leq T_N$$ be the order statistics corresponding to $N$ independent samples from $\zeta$. Let $$(X_t^i)_{i\in A(t),t\geq 0}$$ be the process which results from the following scheme. We start with $N$ independent Brownian motions on $\mathbb R$. At every timepoint $T_i$ we remove the particle with the largest absolute value from the system. Between the timepoints $T_i$ the particles perform independent Brownian motion. We define the index set $A(t)$ of surviving particles up to a time $t$ as the particles which have not been removed up to this time.