Systematic Component: This is the linear predictor, which is a linear combination of the explanatory variables (X1, X2, ..., Xn) and their corresponding coefficients (β0, β1, ..., βn).
While both Genmod and traditional linear regression aim to model relationships between variables, Genmod is a more general framework. Traditional linear regression is actually a special case of Genmod where the random component is the Normal distribution and the link function is the Identity link. genmod work
The primary goal of Genmod is to estimate the unknown coefficients (β) in the systematic component. This is typically achieved using a method called Maximum Likelihood Estimation (MLE). The MLE process involves: Systematic Component: This is the linear predictor, which
Specifying the Likelihood Function: This function represents the probability of observing the given data, given the model parameters (the coefficients). The primary goal of Genmod is to estimate