Diagnostics for HierArchical Regession Models
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regression-diagnostics
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A statistical framework that serves as a common interface to a large range of models
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An introductory statistics course for social scientists, using Stata
statistics course linear-regression stata statistical-methods data-visualization statistical-analysis data-analysis logistic-regression regression-models regression-diagnostics social-sciences
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2SLS Regression with Diagnostics in R
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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.
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Detailed implementation of various regression analysis models and concepts on real dataset.
python3 outliers autocorrelation feature-engineering goodness-of-fit regression-diagnostics multicollinearity quantile-regression residuals regression-analysis simple-linear-regression poisson-regression-model heteroskedasticity leverages q-q-plot multiple-linear-regression-model ols-regression-model cooks-distance influential-cases gls-regression-model
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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.
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Classical Linear Regression
machine-learning statistics linear-regression regression supervised-learning regression-diagnostics regression-analysis
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Influence diagnostics for ridge regression based on the Kullback-Leibler divergence
kullback-leibler-divergence ridge-regression regression-diagnostics collinearity influence-diagnostics ridge-estimator
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Statistical Methods for Heart Disease & Indicators Using R Programming
data-science statistics exploratory-data-analysis data-visualization statistical-analysis classification logistic-regression inferential-statistics regression-diagnostics r-programming regression-analysis computational-statistics
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Functions and data for Darlington's and Hayes' "Regression Analysis and Linear Models" book used in Utah State University's EDUC 7610 course
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Diagnostic tools for regression modeling.
r statistics regression ols regression-models regression-diagnostics residuals regression-analysis heteroskedasticity cook-distance diagnoser
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This script analyses the relationship between the Human Development Index (HDI), population, and non-religious groups in various countries. Plots visualise relationships between HDI, population, and non-religious groups and using scatterplots and a linear regression model to predict.
ggplot2 linear-regression data-transformation data-visualization regression-diagnostics scatterplots data-inspection missing-data-handling
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Diagnostic tools for regression modeling. Julia-equivalent for diagnoser (https://github.com/robertschnitman/diagnoser).
statistics julia regression ols regression-models regression-diagnostics residuals regression-analysis heteroskedasticity diagnoser diagnoserjl
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Modelldiagnostik der linearen Regression mit R
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An R Companion for the Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, and Li (2005).
linear-regression regression regression-models regression-diagnostics linear-models statistical-models regression-algorithms regression-analysis
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Statistical Analysis for Student Exam Scores Using SAS Studio
statistics exploratory-data-analysis statistical-analysis inferential-statistics regression-diagnostics multiple-linear-regression descriptive-analysis sas-studio variance-inflation student-exam-scores
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This repository contains a price prediction model for King County, Washington. The model results and analysis would prove invaluable to investors and stakeholders in the King County, WA housing market.
data-science machine-learning data-transformation outlier-detection feature-engineering predictive-modeling regression-diagnostics multicollinearity prediction-model house-price-prediction regression-analysis king-county
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This was a course project for the course " Multivariate Data Analysis ".
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