🤠 📿 The Highly Adaptive Lasso

Cubic smoothing splines in Julia.

The julia package for nonparametric density estimate and regression

📦 R/haldensify: Highly Adaptive Lasso Conditional Density Estimation

B-Spline Density Estimation Library - nonparametric density estimation using B-Spline density estimator from univariate sample.

Chinese Restaurant Process Models for Regression and Clustering. Master branch contains latest stable build.

A statistical framework for feature selection and association mapping with 3D shapes

Multi-dimensional Functional Principal Component Analysis

Nonparametric regression and prediction using the highly adaptive lasso algorithm

Simple local constant and local linear regressions in Julia

The state-of-the-art method for denoising 1D signals

Regularized Bayesian varying coefficient regression for group testing data

Source files for R package Sieve

Easy-to-use collection of statistical methods and techniques, all written in R 🗂

Some R Code for My Paper

Lecture on Local Polynomial Regression given for the Statistical Machine Learning exam at University of Trieste

Classic metrics methods used in machine learning

This is an R package to compute the multivariate quasiconvex/quasiconcave nonparametric LSE with or without additional monotonicity constraints described in "Least Squares Estimation of a Monotone Quasiconvex Regression Function" by Somabha Mukherjee, Rohit K. Patra, Andrew L. Johnson, and Hiroshi Morita.

My research

regression discontinuity design; incumbency effect; advanced econometrics