Researchers developed a method called the kernel method to estimate overlapping coefficients without assuming specific models for population densities. The method can estimate three overlapping coefficients accurately, even when the population distributions are unknown. The kernel method outperforms traditional parametric methods when there is no information about the structure of the population distributions.