This function combines one or more existing prediction models into a so/called meta-model.
stackedglm(models, family = binomial, data)a list containing the historical prediction models, which can be defined in several ways. For instance,
historical regression models can be specified using a named vector containing the regression coefficients of the
individual predictors (no need to include the intercept term). List items may also represent an object for
which the function predict() exists.
a description of the error distribution and link function to be used in the meta-model. This can be a character string naming a family function, a family function or the result of a call to a family function. (See family for details of family functions.)
an optional data frame, list or environment (or object coercible by as.data.frame to a data frame)
containing the variables in the model. If not found in data, the variables are taken from environment(formula),
typically the environment from which stackedglm is called.
Thomas Debray <thomas.debray@gmail.com>