Our contributions take the format of open-source packages for Python or R software:
ARMADA (R package)
Two steps variable selection procedure in a context of high-dimensional dependent data with few observations. A first step is dedicated to eliminate the dependency between variables (clustering of variables, followed by factor analysis inside each cluster). A second step consists in variable selection by aggregation of adapted methods.
cvmgof (R package)
cvmgof is an R library devoted to Cramer-von Mises goodness-of-fit tests. It implements three nonparametric statistical methods based on Cramer-von Mises statistics to estimate and test a regression model.
Harissa (Python package)
Harissa is a Python package for both inference and simulation of gene regulatory networks, based on stochastic gene expression with transcriptional bursting. It was implemented in the context of a mechanistic approach to gene regulatory network inference from single-cell transcriptomic data.
HSPOR (R package)
Several functions that allow by different methods to infer a piecewise polynomial regression model under regularity constraints, namely continuity or differentiability of the link function. The implemented functions are either specific to data with two regimes, or generic for any number of regimes, which can be given by the user or learned by the algorithm.
kosel (R package)
Performs variable selection for many types of L1-regularised regressions using the revisited knockoffs procedure. This procedure uses a matrix of knockoffs of the covariates independent from the response variable. The idea is to determine if a covariate belongs to the model depending on whether it enters the model before or after its knockoff. The procedure is suitable for a wide range of regressions with various types of response variables. Regression models available are exported from the R packages ‘glmnet’ and ‘ordinalNet’.
quantCurves (R package)
Non-parametric methods as local normal regression, polynomial local regression and penalized cubic B-splines regression are used to estimate quantiles curves.
SesIndexCreatoR (R package)
This package allows computing and visualizing socioeconomic indices and categories distributions from datasets of socioeconomic variables. These tools were developed as part of the EquitArea Project, a public health program.
starm (R package)
Estimation and model selection of the two-time centered autologistic regression model. Application for the spatio-temporal modeling of the spread of a disease on a grid over time.
