Fast computation of some matrices useful in statistics

Detecting structural breaks in time series data using statistical analysis and regression models in R.

Coefeasy is an R package under development for making regression coefficients more accessible. With this tool, you can read and report key coefficients instantly.

R package for residualizing covariates

Imputing immunogenic phenotypes using Elastic Net to infer causality between gut microbiome and immune system.

Easily install and load all Rsquared Academy R packages.

Bunch of exercises computed during the Machine Learning for Finance course.

Coursework for an R (STSCI @ Cornell) class on Statistical Computing (2025)

A curated collection of advanced statistical modeling projects applying techniques such as OLS regression, GLMs, Poisson distribution, survival analysis, multilevel models, and classification algorithms. Each folder contains a real-world case study with end-to-end analysis in R, including business insights, model diagnostics, and interpretation.

This study used the data collected from Lehigh University's peer tutoring program which focused on 20 courses involving problem-solving skills over three academic years, 2003-04 through 2005-06. An OLS model and generalized liner mixed-effects models were used to measure effect of participation in tutoring in terms of hours spent getting tutored…

Sentiment analysis of Swiss media coverage on asylum migration (2010–2022) using LDA, SentiMerge, and Swiss asylum statistics. University of Bern seminar project.

Data wrangling, regression modeling and analysis.

In this project, we explore the properties of Quantile Regression and compare its results with Ordinary Least Squares regression, using Monte Carlo simulations. The paper highlights Quantile Regression's advantages in handling heteroscedastic data and outliers, and strategies to mitigate quantile crossing.

A package of wrapper functions that are useful when analyzing data from randomized controlled trials (RCTs, especially with three or more treatment assignments)

Class projects

Ordinary least square (OLS) regression analysis carried out in this project. The selected dependent variables are some public health indicators like anxiety, diabetes. We tried to find the independent variables which are responsible for this health hazard.

Causal Inference project analyzing the impact of skilled manager interventions using OLS regression

Econometrics_regression analysis using R language