A library for the copula
Project description
==================================================
This library is now part of the ambhas
(http://pypi.python.org/pypi/ambhas/) library.
Updates will only be made in the ambhas library.
==================================================
============
Copulalib
============
This is a package/library in python to model the copulas.
This is being developed under the project `AMBHAS <http://www.ambhas.com/>`_.
This contains module for the following copula
------------------------------------------------
* Frank
* Clayton
* Gumbel
Installing copulalib
======================
Installing copulalib can be done by downloading source file (copulalib--<version>.tar.gz),
and after unpacking issuing the command::
python setup.py install
This requires the usual Distutils options available.
Or, download the copulalib--<version>.tar.gz file and issue the command::
pip /path/to/copulalib--<version>.tar.gz
Or, directly using the pip::
pip install copulalib
Usage
=========
Import required modules::
import numpy as np
import matplotlib.pyplot as plt
from copulalib.copulalib import Copula
Generate random (normal distributed) numbers::
x = np.random.normal(size=100)
y = 2.5*x+ np.random.normal(size=100)
Make the instance of Copula class with x, y and clayton family::
foo = Copula(x, y, family='clayton')
Print the Kendall's rank correlation::
print foo.tau
Print spearmen's correlation::
print foo.sr
Print pearson's correlation::
print foo.pr
Print the parameter (theta) of copula::
print foo.theta
Generate the 1000 samples (U,V) of copula::
X1, Y1 = foo.generate_xy(1000)
For more details see the test.py file inside module.
Changelog
=========
1.1.0 (June 2011)
------------------
- Changed from function orieted to object oriented, documentation improved.
1.0.0 (May 2011)
------------------
- Initial release
Any questions/comments
=========================
If you have any comment/suggestion/question,
please feel free to write me at satkumartomer@gmail.com
So far, the documents are not well explained,
I will be updating them soon.
This library is now part of the ambhas
(http://pypi.python.org/pypi/ambhas/) library.
Updates will only be made in the ambhas library.
==================================================
============
Copulalib
============
This is a package/library in python to model the copulas.
This is being developed under the project `AMBHAS <http://www.ambhas.com/>`_.
This contains module for the following copula
------------------------------------------------
* Frank
* Clayton
* Gumbel
Installing copulalib
======================
Installing copulalib can be done by downloading source file (copulalib--<version>.tar.gz),
and after unpacking issuing the command::
python setup.py install
This requires the usual Distutils options available.
Or, download the copulalib--<version>.tar.gz file and issue the command::
pip /path/to/copulalib--<version>.tar.gz
Or, directly using the pip::
pip install copulalib
Usage
=========
Import required modules::
import numpy as np
import matplotlib.pyplot as plt
from copulalib.copulalib import Copula
Generate random (normal distributed) numbers::
x = np.random.normal(size=100)
y = 2.5*x+ np.random.normal(size=100)
Make the instance of Copula class with x, y and clayton family::
foo = Copula(x, y, family='clayton')
Print the Kendall's rank correlation::
print foo.tau
Print spearmen's correlation::
print foo.sr
Print pearson's correlation::
print foo.pr
Print the parameter (theta) of copula::
print foo.theta
Generate the 1000 samples (U,V) of copula::
X1, Y1 = foo.generate_xy(1000)
For more details see the test.py file inside module.
Changelog
=========
1.1.0 (June 2011)
------------------
- Changed from function orieted to object oriented, documentation improved.
1.0.0 (May 2011)
------------------
- Initial release
Any questions/comments
=========================
If you have any comment/suggestion/question,
please feel free to write me at satkumartomer@gmail.com
So far, the documents are not well explained,
I will be updating them soon.
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