chainladder.DevelopmentConstant#
- class chainladder.DevelopmentConstant(patterns=None, style='ldf', callable_axis=0, groupby=None)#
- A Estimator that allows for including of external patterns into a
Development style model. When this estimator is fit against a triangle, only the grain of the existing triangle is retained.
- Parameters:
- patterns: dict or callable
A dictionary key:value representation of age(in months):value. If callable is supplied, callable must return a dict for each element of the callable axis
- style: string, optional (default=’ldf’)
Type of pattern given to the Estimator. Options include ‘cdf’ or ‘ldf’.
- callable_axis: 0 or 1
If a callable is supplied, the axis (index or column) along which to apply the callable. If patterns is not a callable, then this parameter is ignored.
- groupby:
option to group levels of the triangle index together for the purposes estimating patterns. If omitted, each level of the triangle index will receive its own patterns.
- Attributes:
- ldf_: Triangle
The estimated loss development patterns
- cdf_: Triangle
The estimated cumulative development patterns
Methods
fit
(X[, y, sample_weight])Fit the model with X.
fit_transform
(X[, y])Fit to data, then transform it.
get_metadata_routing
()Get metadata routing of this object.
get_params
([deep])Get parameters for this estimator.
set_backend
(backend[, inplace, deep])Converts triangle array_backend.
set_fit_request
(*[, sample_weight])Request metadata passed to the
fit
method.set_output
(*[, transform])Set output container.
set_params
(**params)Set the parameters of this estimator.
to_json
()Serializes triangle object to json format
to_pickle
(path[, protocol])Serializes triangle object to pickle.
transform
(X)If X and self are of different shapes, align self to X, else return self.
pipe