The researchers compared two methods to estimate parameters in a normal mixture distribution. They wanted to see which method gave better results for a two-component distribution with different variances. By using a simulation study, they found that the profile likelihood method provided more accurate estimates compared to the penalized EM algorithm. This approach helped avoid issues with unbounded likelihood functions and led to better parameter estimates.