A collection of algorithms on the subjects written in R

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

Functions for conducting regression estimation on nonsmooth data

Here is a collection of machine learning methods implemented from scratch.

My research

Classic metrics methods used in machine learning

bark R package for Bayesian nonparametric kernel regression

Nonparametric regression examples with R and Python

Simple local constant and local linear regressions in Julia

Source files for R package Sieve

Anisotropic smoothing for change-point regression data

Nonparametric Sobol Estimator with Bootstrap Bandwidth

Reproducibility repo for the simulation and real data results in the SINATRA manuscript set to appear in AoAS.

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.

Development version of the TrendLSW R package

Regularized Bayesian varying coefficient regression for group testing data

Some R Code for My Paper

Companion Jupyter notebook of the paper "Functional Estimation of Anisotropic Covariance and Autocovariance Operators on the Sphere"

regression discontinuity design; incumbency effect; advanced econometrics