You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...

An example of such an outcome would be something ... becomes more dynamic with complex decisions, Bayesian probability models must be implemented to determine priori probabilities.

Missing values can occur, for example ... between the steps of guessing a probability distribution over completions of missing data given the current model (known as the E-step) and then re ...