Generalized quasi-likelihood (GQL) inference is a statistical framework that extends the principles of likelihood-based inference to scenarios where the complete likelihood function is challenging or impractical to specify. In situations where the full likelihood function is unknown or difficult to work with, GQL provides an alternative by constructing a quasi-likelihood function that captures certain aspects of the data’s probabilistic structure. This approach is particularly useful in cases where the assumptions of traditional likelihood inference are not fully met.