JarqueBera

class JarqueBera(axis=0)[source]

Jarque-Bera test of normality.

Uses statsmodels.stats.stattools.jarque_bera as a test of normality.

Parameters:

axisint, optional: Axis to use if data has more than 1 dimension. Default is 0.

Attributes:

jb_stat_float: The Jarque-Bera test statistic.
pvalue_float: The pvalue of the test statistic.
skew_float: Estimated skewness of the data.
kurtosis_float: Estimated kurtosis of the data.

Examples

>>> from sktime.datasets import load_airline
>>> from sktime.param_est.residuals import JarqueBera
>>>
>>> X = load_airline()
>>> param_est = JarqueBera()
>>> param_est.fit(X)
JarqueBera(...)

Methods

`check_is_fitted`([method_name])	Check if the estimator has been fitted.
`clone`()	Obtain a clone of the object with same hyper-parameters and config.
`clone_tags`(estimator[, tag_names])	Clone tags from another object as dynamic override.
`create_test_instance`([parameter_set])	Construct an instance of the class, using first test parameter set.
`create_test_instances_and_names`([parameter_set])	Create list of all test instances and a list of names for them.
`fit`(X[, y])	Fit estimator and estimate parameters.
`get_class_tag`(tag_name[, tag_value_default])	Get class tag value from class, with tag level inheritance from parents.
`get_class_tags`()	Get class tags from class, with tag level inheritance from parent classes.
`get_config`()	Get config flags for self.
`get_fitted_params`([deep])	Get fitted parameters.
`get_param_defaults`()	Get object's parameter defaults.
`get_param_names`([sort])	Get object's parameter names.
`get_params`([deep])	Get a dict of parameters values for this object.
`get_tag`(tag_name[, tag_value_default, ...])	Get tag value from instance, with tag level inheritance and overrides.
`get_tags`()	Get tags from instance, with tag level inheritance and overrides.
`get_test_params`([parameter_set])	Return testing parameter settings for the estimator.
`is_composite`()	Check if the object is composed of other BaseObjects.
`load_from_path`(serial)	Load object from file location.
`load_from_serial`(serial)	Load object from serialized memory container.
`reset`()	Reset the object to a clean post-init state.
`save`([path, serialization_format])	Save serialized self to bytes-like object or to (.zip) file.
`set_config`(**config_dict)	Set config flags to given values.
`set_params`(**params)	Set the parameters of this object.
`set_random_state`([random_state, deep, ...])	Set random_state pseudo-random seed parameters for self.
`set_tags`(**tag_dict)	Set instance level tag overrides to given values.
`update`(X[, y])	Update fitted parameters on more data.