• grpSLOPEMC — This is an extension package to the R package grpSLOPE. It contains Monte Carlo based methods for the estimation of the regularizing sequence. :octocat: github

  • grpSLOPE — Group SLOPE is a penalized linear regression method that is used for adaptive selection of groups of significant predictors in a high-dimensional linear model. A unique feature of the Group SLOPE method is that it offers (group) false discovery rate control (i.e., control of the expected proportion of irrelevant groups among the total number of groups of predictors selected by the Group SLOPE method). :octocat: github :page_facing_up: gh-pages :v: CRAN

  • mixed_models — Fit statistical (linear) models with fixed and mixed (random) effects in Ruby. The package supports the formula language of the R package lme4 for model specification (a pain to implement), many types of hypotheses tests and confidence intervals for the fixed and random effects coefficients, methods for prediction and prediction intervals, etc. It is my Google Summer Of Code 2015 project. :octocat: github :gem: rubygems

  • spitzy — Spitzy is the name of a cute Pomeranian. Spitzy reads backwards as yztips, which translates into: Your Zappy-Tappy Initial and boundary value Partial (and ordinary) differential equation Solver. It is my collection of numerical methods for differential equations written in Ruby. :octocat: github :page_facing_up: gh-pages :gem: rubygems

  • When I have some free time, I like to contribute code to open source software projects (mostly, related to mathematics, statistics or machine learning). Visit my github page for the projects that I contribute to.