MONarchy module for MON estimators
MONArchy provides :
- estimation functions using MON and derivative methods
- The MONArchy class to call each function on a set of data
Analyse.py
- Analyse : to load data and return a JSON file with estimations and descriptive statistics
exemple :
a = Analyse(path)
print(a.head())
print(a.infos())
a.save_graph("0_0_R","fig.png")
with
-
path: the path of a CSV file (string) -
column_name: the column name (string)
produce a JSON file with statistical estimators
Changelog
1.0.8
- add a method to list column name
1.0.7
- correct requirements.txt
1.0.6
- add save_graph in Analyse
1.0.5
- add bayesian MoN
References
@article{orenstein_robust_2019,
title = {Robust Mean Estimation with the Bayesian Median of Means},
url = {http://arxiv.org/abs/1906.01204},
journaltitle = {{arXiv}:1906.01204 [math, stat]},
author = {Orenstein, Paulo},
urldate = {2021-04-08},
date = {2019-06-04},
eprinttype = {arxiv},
eprint = {1906.01204},
keywords = {Bayesian, Estimators, {MON}, Math, Mathematics - Statistics Theory, Statistics - Methodology},
}
@unpublished{buisine:hal-03201630,
TITLE = {{Fireflies removing in Monte Carlo rendering with adaptive Median of meaNs}},
AUTHOR = {Buisine, J{\'e}r{\^o}me and Delepoulle, Samuel and Renaud, Christophe},
URL = {https://hal.archives-ouvertes.fr/hal-03201630},
NOTE = {working paper or preprint},
YEAR = {2021},
MONTH = Apr,
PDF = {https://hal.archives-ouvertes.fr/hal-03201630/file/Gini_MON_2021_arXiv.pdf},
HAL_ID = {hal-03201630},
HAL_VERSION = {v1},
}
