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])	Configure whether metadata should be requested to be 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