chainladder.ClarkLDF#
- class chainladder.ClarkLDF(growth='loglogistic', groupby=None)#
A Estimator that allows for curve fitting development pattterns according to Clark 2003.
The method fits incremental triangle amounts to one of
loglogistic
orweibull
growth curves. Both Clarks methods, LDF and Cape Cod, can be estimated. To invoke the Cape Cod method, includesample_weight
in when fitting the estimator.- Parameters:
- growth: {‘loglogistic’, ‘weibull’}
The growth function to be used in curve fitting development patterns. Options are ‘loglogistic’ and ‘weibull’
- groupby:
An option to group levels of the triangle index together for the purposes of 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.
- incremental_fits_: Triangle
The fitted incrementals of the model.
- theta_: DataFrame
Estimates of the theta parameter of the growth curve.
- omega_: DataFrame
Estimates of the omega parameter of the growth curve.
- elr_: DataFrame
The Expected Loss Ratio parameter. This only exists when a
sample_weight
is provided to the Estimator.- scale_: DataFrame
The scale parameter of the model.
- norm_resid_: Triangle
The “Normalized” Residuals of the model according to Clark.
Methods
G_
(age)Growth function of the estimator.
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