regression-diagnostics

Diagnostics for HierArchical Regession Models

A statistical framework that serves as a common interface to a large range of models

An introductory statistics course for social scientists, using Stata

2SLS Regression with Diagnostics in R

Comprehensive Stata do-file for testing and correcting violations of classical OLS assumptions: model specification, heteroskedasticity, multicollinearity, spatial autocorrelation, endogeneity, residual normality, and outlier/influence detection.

An R package aimed at making specification curve analysis easy, fast, and pretty. It improves upon existing offerings with additional features and tidyverse integration. Users can easily visualize and evaluate how their models behave under different specifications with a high degree of customization.

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

Classical Linear Regression

Influence diagnostics for ridge regression based on the Kullback-Leibler divergence

Statistical Methods for Heart Disease & Indicators Using R Programming

Monte Carlo experiments testing OLS robustness to sample size, outliers, multicollinearity, and nonlinearity, with method comparisons and a real-data case study.

OLS model selection and diagnostics on the Boston housing data: best subsets under four criteria, LOOCV, VIF, assumption checks.

Seguros médicos · Parte 2 (v2): regresión lineal interpretable. Escalón en IMC 30, validación cruzada (R² 0,86, supera a Gradient Boosting) y diagnóstico de residuos · Python

Diagnostic tools for regression modeling.

Análisis estadístico y econométrico de los factores que influyen en el precio de automóviles mediante regresión lineal y diagnósticos del modelo en R.

Modelldiagnostik der linearen Regression mit R

An R Companion for the Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, and Li (2005).

Functions and data for Darlington's and Hayes' "Regression Analysis and Linear Models" book used in Utah State University's EDUC 7610 course

Applied multiple linear regression and regression diagnostics on NSSO consumption data and IPL performance data to analyze prediction accuracy, model assumptions, and the relationship between player performance and compensation.

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