R package to manage multicollinearity in modeling data frames.
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Dec 1, 2025 - R
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multicollinearity
Here are 18 public repositories matching this topic...
R function to detect multicollinearity in ERGM
social-networks diagnostics network-analysis social-network-analysis multicollinearity ergm collinearity-diagnostics exponential-random-graph-models
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Dec 19, 2022 - R
The main objective of this project is to build a model to identify whether the delivery of an order will be late or on time.
random-forest pca-analysis hyperparameter-optimization logistic-regression outlier-detection tableau multicollinearity xgboost-algorithm bivariate-analysis univariate-analysis
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Dec 9, 2021 - R
Assess multicollinearity between predictors when running the dredge function (MuMIn - R)
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Nov 26, 2019 - R
Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.
ggplot2 dplyr regression-models hypothesis-testing multicollinearity correlation-matrix stepwise-regression p-values reduced-order-models normality-test alsm
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Jan 9, 2021 - R
📈 Hands-on regression analysis project in R using a dataset with 30 predictors. Includes manual OLS implementation without lm(), p-value computation, and comparison with built-in functions. Applies stepwise selection (AIC/BIC), Ridge, and Lasso to minimize test error and identify key predictors.
data-science machine-learning r statistics linear-regression cross-validation regression feature-selection model-selection predictive-modeling ridge-regression multicollinearity lasso-regression stepwise-regression
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Aug 11, 2025 - R
This project is about to use linear regression to examine the relationship between various economic variables and the mortgage rate in the United States.
r linear-regression economics statistical-analysis data-analytics wls multicollinearity skewness heteroscedasticity ols-regression-model
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Aug 7, 2023 - R
Analysis of Influencing Factors Leading to Suicidal Actions via Linear Regression and Regularization Methods
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Mar 27, 2021 - R
Skript zur Videoreihe Regressionsdiagnostik in R
linear-regression regression diagnostics multicollinearity heteroscedasticity assumptions-in-regression
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Jan 9, 2023 - R
Research, Analysis, and Final Paper for my Intro to Econometrics class taken in Fall 2023
r data-visualization econometrics html-css regression-models multicollinearity regression-analysis significance-testing
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Jan 29, 2024 - R
Linear regression, VIF, Auto Correlation.
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Aug 25, 2023 - R
Variable selection with uncertainty quantification for general regression models with highly correlated predictors using the our generalized sum of single effects (gSuSiE) framework.
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Oct 29, 2025 - R
The project involves the multivariate regression analysis of a dataset.
cross-validation least-squares model-selection t-test confidence-intervals outlier-detection multicollinearity multivariate-regression bias-variance simple-linear-regression akaike-information-criterion prediction-intervals adjusted-r-squared r-squared underlying-assumptions categorical-covariates partial-f-test
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Oct 24, 2020 - R
Variable selection with uncertainty quantification for general regression models with highly correlated predictors using the our generalized sum of single effects (gSuSiE) framework.
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Oct 28, 2025 - R
This repository has scripts that are part of the programming assignments of the course Linear and Generalized Linear Models taught at FME, UPC Barcelonatech.
statistics fme regression-models anova linear-models multicollinearity regression-algorithms regression-analysis linearregression upc-barcelonatech
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Mar 25, 2019 - R
The project involves deciding on the mode of transport that the employees prefer while commuting to the office.
naive-bayes-classifier logistic-regression outlier-detection knn multicollinearity imbalanced-data smote-analysis
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Dec 10, 2021 - R
The project involves analyzing certain issues of customer churn faced by telecom companies. Models are required to be built so as to predict whether a customer will cancel their service in the future or not and then model comparison measures are made for taking interpretation and recommendations from the best model.
naive-bayes-classifier accuracy logistic-regression outlier-detection sensitivity multicollinearity knn-classification auc-roc-curve
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Dec 9, 2021 - R
Determined the best regression model which represents the data
regression model-selection multicollinearity normality regression-analysis shapiro-wilk vif durbin-watson
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May 23, 2020 - R
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