class statsmodels.gam.smooth_basis.CyclicCubicSplines(x, df, constraints=None, variable_names=None)[source]

additive smooth components using cyclic cubic regression splines

This spline basis is the same as in patsy.

xarray_like, 1-D or 2-D

underlying explanatory variable for smooth terms. If 2-dimensional, then observations should be in rows and explanatory variables in columns.


numer of basis functions or degrees of freedom

constraints{None, str, array}

Constraints are used to transform the basis functions to satisfy those constraints.

variable_names{list[str], None}

The names for the underlying explanatory variables, x used in for creating the column and parameter names for the basis functions. If x is a pandas object, then the names will be taken from it.



create the spline basis for new observations

Last update: May 25, 2024