Metadata-Version: 1.1
Name: lad
Version: 0.1.dev1
Summary: Least absolute deviations with L1 regularization using majorization-minimization
Home-page: https://github.com/mirca/lad
Author: mirca
Author-email: jvmirca@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: lad
        ===
        |ci-badge| |cov-badge| |zenodo-badge|
        
        .. |ci-badge| image:: https://travis-ci.org/mirca/lad.svg?branch=master
            :target: https://travis-ci.org/mirca/lad
        .. |cov-badge| image:: https://codecov.io/gh/mirca/lad/branch/master/graph/badge.svg
            :target: https://codecov.io/gh/mirca/lad/branch/master/
        .. |zenodo-badge| image:: https://zenodo.org/badge/136721899.svg
           :target: https://zenodo.org/badge/latestdoi/136721899
        
        Least absolute deviations with L1 regularization using majorization-minimization.
        In estimation theory terms, this is the Maximum A Posterior (MAP) estimator for
        a Laplacian likelihood with Laplacian prior, i.e.
        
        .. image:: lad.png
            :align: center
        
        The MM algorithm update turns out to be
        
        .. image:: lad2.png
            :align: center
        
        which belongs to the class of iterative reweighted least-squares: https://en.wikipedia.org/wiki/Iteratively_reweighted_least_squares
        
        Python Version
        --------------
        
        To install the development version, proceed as follows::
        
            git clone https://github.com/mirca/lad.git
            pip install -e lad
        
        Or install the lastest version on PyPi::
        
            pip install lad
        
        Installation dependencies::
        
            - tensorflow
        
        Test dependencies::
        
            - numpy
            - tensorflow
            - pytest
            - pytest-cov
        
        R version
        =========
        
        To install the development version, proceed as follows::
        
            git clone https://github.com/mirca/lad.git
        
        Inside the R console (or your favourite terminal), type:
        
            install.packages("devtools") # you haven't installed devtools already
            install_github("mirca/lad")
        
        The R version depends on the package ``CVXR`` which can be installed as follows::
        
            install_github("anqif/CVXR")
        
Keywords: statistics optimization
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
