In GLMs, quasi-likelihood estimation is a way to allow over- or under-dispersion by choosing an appropriate variance function.
In GLMs, quasi-likelihood estimation is a way to allow over- or under-dispersion by choosing an appropriate variance function. It's often used for binary or count data, e.g. in quasi-binomial or quasi-Poisson models; there it does not correspond to any actual count distribution.
Wikipedia has an article https://en.wikipedia.org/wiki/Quasi-likelihood with further information and references.
