# Modelling Inverse Gaussian Distribution for Survival Data in R

I am fitting survival data with different distributions in order to determine what best characterises my data. I believe that the inverse gaussian distribution may be a good fit but I have been having trouble modelling the distribution in R. I have been using the flexsurvreg R package because it provides log likelihood and AIC values for each distribution and allows for distributions to be plotted visually. flexsurvreg does not have the inverse gaussian distribution built-in but allows for custom-made distributions. Could anyone provide a bit of help regarding how the inverse gaussian distribution could be modelled in flexsurvreg?

For a bit of reference, here is what my survival distribution looks like: