chainladder.Trend

class chainladder.Trend(trends=0.0, dates=None, axis='origin')

Estimator to create and apply trend factors to a Triangle object. Allows for compound trends as well as storage of the trend matrix to be used in other estimators, such as CapeCod.

Parameters:

trends: list-like

The list containing the annual trends expressed as a decimal. For example, 5% decrease should be stated as -0.05

dates: list of date-likes

A list-like of (start, end) dates to correspond to the trend list.

axis: str (options: [‘origin’, ‘valuation’])

The axis on which to apply the trend

Attributes:

trend_:

A triangle representation of the trend factors

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_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.
set_transform_request(*[, sample_weight])	Configure whether metadata should be requested to be passed to the transform method.
to_json()	Serializes triangle object to json format
to_pickle(path[, protocol])	Serializes triangle object to pickle.
transform(X[, y, sample_weight])	If X and self are of different shapes, align self to X, else return self.