Metadata-Version: 2.0
Name: smoothfdr
Version: 0.9.0
Summary: False discovery rate smoothing
Home-page: https://github.com/tansey/smoothfdr
Author: Wesley Tansey
Author-email: tansey@cs.utexas.edu
License: MIT
Keywords: statistics biostatistics fdr hypothesis machinelearning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib

False Discovery Rate Smoothing
==============================

The smoothfdr package provides an implementation of false dicovery rate smoothing as presented in the paper by Tansey et al. (arxiv link).

The documentation is still being written. To-do list includes:

1) Basic usage

2) Examples

    - 2a) 1-d
    - 2b) 2-d (rectangular)
    - 2c) fMRI (non-rectangular)

All of these cases are covered by the code, but detailed examples still need to be written up.

