Longley

Longley

class Longley(y_name: str = 'TOTEMP')[source]

Load the Longley dataset for forecasting with exogenous variables.

Parameters:

y_name: str, optional (default=”TOTEMP”)

Name of target variable (y)

Notes

This mulitvariate time series dataset contains various US macroeconomic variables from 1947 to 1962 that are known to be highly collinear.

Dimensionality: multivariate, 6 Series length: 16 Frequency: Yearly Number of cases: 1

Variable description:

TOTEMP - Total employment GNPDEFL - Gross national product deflator GNP - Gross national product UNEMP - Number of unemployed ARMED - Size of armed forces POP - Population

References

[1]

Longley, J.W. (1967) “An Appraisal of Least Squares Programs for the Electronic Computer from the Point of View of the User.” Journal of the American Statistical Association. 62.319, 819-41. (https://www.itl.nist.gov/div898/strd/lls/data/LINKS/DATA/Longley.dat)

Examples

>>> from sktime.datasets.forecasting import Longley
>>> y, X = Longley().load("y", "X")

Methods

cache_files_directory()	Get the directory where cache files are stored.
cleanup_cache_files()	Cleanup cache files from the cache directory.
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.
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_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])	Test parameter settings for the dataset.
is_composite()	Check if the object is composed of other BaseObjects.
keys()	Return a list of available sets.
load(*args)	Load the dataset.
load_from_path(serial)	Load object from file location.
load_from_serial(serial)	Load object from serialized memory container.
loader_func()	Load the Longley dataset for forecasting with exogenous variables.
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.

get_loader_func