what would be a good strategy when using a generalized linear model and a new batch of inputs comes with a missing value? what is the missing input why would it be useful to imputation for missing inputs in generalized linear modelling? how to minimize the loss of information from the missing inputs to the generalization of a linear model what is missing inputs for an estimate glm missing data what is the missing value in generalized linear model which model can i use for missing input values? missing value in a generalized model missing input when making predictions can gl model predict missing input what to do if a generalized linear model contains inputs how to minimize missing input value how should i use a missing input in general linear model which model uses missing input value when doing prediction what is meant by missing data in generalized linear model what is miss input mean in predicting what does missing input mean when doing a prediction which imputation is better what's wrong when you miss an input in generalized linear modelling