I asked this question here which @Glen_b had kindly answered. I thought I could get a more detailed explanation with references if I posted it as a whole new question.
So my questions is why residuals plots such as residual vs fitted plot and normal QQ normal can be used for diagnostic of glm? Residuals vs fitted are used for OLS to checked for heterogeneity of residuals and normal qq plot is used to check normality of residuals. However there is no such assumption for glm (e.g. gamma, poisson and negative binomial). So why are these plot still being used to diagnose glm? There are questions (1,2 and etc.) that discussed its usage but the did not explain the reason for their relevance. There is even a command
boot that provides residuals plots for glm.
Here are some plots from my current analysis. I am trying to select a model among the three: OLS, lognormal OLS and gamma with log link. Perhaps it will be easier to discuss using these plots as examples.
Additional plots for log link gamma glm