The article compares different methods for estimating parameters of a normal inverse Gaussian distribution. Ordinary methods like maximum likelihood and method of moments can have issues, so adjusted methods were tested. The simulation results showed that the adjusted estimators had smaller errors and were less affected by initial values compared to ordinary methods. Real data also supported these findings. The researchers recommend using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values for accurate parameter estimation.