1. A method for sampling a state space of a system with states x and a probability density ρ(x) indicating the probability for the system to be in state x by iteratively generating states xi,t and their weighting factors ρi,t, wherein the index i is the iteration parameter and the index t distinguishes different states xi,t generated by an iteration i, the method comprising: sampling the state space of the system and performing, a first step for selecting an initial sampling distribution function ρi(x), to execute an iteration procedure including: a second step for generating Nj states xj,t by a numerical sampling algorithm, a third step determining weighting factors ρi,t for states xi,t generated so far by using sampling distribution functions ρi(x) determined so far, a fitting step for determining a sampling distribution function ρj(x) for the next iteration by fitting ρj(x) to ρi,tO(xi,t) for states xi,t generated so far, wherein O(xi,t) is a function, respectively a property of the states xi,t, identifying a desired property in the state space of the system based on sampled state space, and a fourth step for testing at least one criterion to decide whether to continue the iteration procedure or to stop the iteration procedure and to go to a fifth step for performing an analysis using simulated data.