bind_predictor#
- superglm.bind_predictor(
- family: DistributionalFamily,
- name: str,
- *terms: TermInput,
- intercept: bool = True,
- link: str | Link | None = None,
Declare a predictor by parameter name, including for custom families.
Built-in family helpers are the usual entry point. Use this function when a custom family declares its parameters without helper methods.
- Parameters:
- familyDistributionalFamily
The same family instance that will be passed to
SuperLSS.- namestr
A name from
family.parameters. This is also the name used in model results and offsets.- *termsstr or BoundTerm or BoundInteraction
Numeric column names or declarations made by the term helpers. Supply no terms for an intercept-only predictor.
- interceptbool, default=True
Include an intercept in this predictor.
- linkstr or Link, optional
Override the family’s default link. The model checks compatibility with the parameter’s support.
- Returns:
- BoundPredictor
A declaration for one parameter. Every family parameter needs one.
Examples
The generic binder and a built-in helper declare the same parameter:
>>> from superglm import GaussianLS, bind_predictor >>> family = GaussianLS() >>> bind_predictor(family, "location", "age").name 'location' >>> family.location("age").name 'location'