The researchers developed a new way to model data that is skewed and has heavy tails. They used a special type of distribution called normal weighted inverse Gaussian. This distribution is better at capturing the behavior of data taken over short time intervals compared to the normal distribution. By using a mixture of two special cases of Generalized Inverse Gaussian distribution, they were able to make the model more flexible. The researchers used the EM-algorithm to estimate the parameters of the model.