Comprehensive tutorial notes for ETC2410 Introductory Econometrics

Sketching of Data via Random Subspace Embeddings

Code to reproduce paper Adrian, Duarte and Iyer (2023), “The Market Price of Risk and Macro-Financial Dynamics”

GWAS of trait variance (C )

Detailed implementation of various regression analysis models and concepts on real dataset.

R Code for Bayesian Inference for Structural Vector Autoregressions Identified with Markov-Switching Heteroskedasticity

R package to perform regression-based Brown-Forsythe test

An R package for time series modelling with mixture autoregressive and related models.

Impact of macroecomonic variables on S&P 500

As part of this project, we have used Regression Analysis on top of a panel data on Guns in USA to determine the "Effect of Shall-Carry Law on Violence Rate and Incarceration Rate in United States".

Repo where different methods for price regression are used (supervised machine learning)

The purpose of my application was to solve a problem many businesses (small businesses in particular) face. They do not know how much to produce, where to price, how much to spend on advertising and many other questions. Eden’s purpose was to answer these questions for them easily and with no technical acumen required by the user. Eden would mod…

Script used for my undergraduate thesis

OLS regression with possibility of controlling for fixed effects and robust standard errors

Diagnostic tools for regression modeling. Julia-equivalent for diagnoser (https://github.com/robertschnitman/diagnoser).

Testing different models for the linear regression model with one estimator and heteroskedacity in data

Here I have checked and removed for heteroskedasticity .

Econometrics_regression analysis using R language

Basic methodologies of Empirical Research applied on various case studies (R language)

Full Log-Likelihood Heteroskedastic Regression with Deep Neural Networks and Tensorflow