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Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
Linear, IV and GMM Regressions With Any Number of Fixed Effects
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
A MATLAB library for sparse representation problems
R package that provides estimation methods for Gravity Models
Popular Econometrics content with code; Simple Linear Regression, Multiple Linear Regression, OLS, Event Study including Time Series Analysis, Fixed Effects and Random Effects Regressions for Panel Data, Heckman_2_Step for selection bias, Hausman Wu test for Endogeneity in Python, R, and STATA.
This project includes a widget component library derived from the semantic lookup service SemLookP. SemLookP supports metadata annotation as well as data search in the area of translational medicine.
Master Degree Coursework: Econometrics I
Detecting structural breaks in time series data using statistical analysis and regression models in R.
Apex team`s multiple regression project. It contains: What is Multiple Regression? Advantages and disadvantages of multiple regression, least square method and real implementation.
This page will host scripts used to increase students productivity in remote learning education. Primarily aimed at k-5.
Implementation of Linear Regression (OLS)
OLS Bootstrap on Cross-Sectional Data
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
Machine Learning Algorithms
Generalized Improved Second Order RBF Neural Network with Center Selection using OLS
IV technique. Replication & critique of N. Nunn paper using R
Gradient descent via OLS
Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon
OLS (twoway clustered standard errors), Imperfect Multicollinearity (Ridge and PCA), ARMA(p,q) with Bootstrap
Comparing the different types of Regression
This project was conducted for "API 222: Machine Learning and Data Analytics", taught at the Harvard Kennedy School. We created a novel dataset and explored how machine learning can predict the onset of civil conflict.
🕊️Use of non-traditional data sources to nowcast migration trends through Artificial Intelligence technologies (academic research project).
MS Excel OLS spreadsheets for geodesy
OLS results and Linear Regression in R
OLS Interpretition
This repository provides a simulation of Ordinary Least-Squares in Mata.
OLS for an Inflation-Targeting Policy Analysis (Chile)
This R code implements the Bonferroni Q test from Yogo and Campbell's (2006) paper "Efficient Tests of Stock Return Predictability."