Everything about Multiple linear regression

🧭 Start here: a 6-step reading path

1. Read the overview: Multiple linear regressionA 5-minute orientation
2. Skim a recent paper: Multiple Linear Regression Model for Improved Project Cost ForecastingInfluential work since 2022
3. Pick up a classic book: Anwendung von multiplen Testprozeduren im linearen RegressionsmodellThe most-reprinted book on the subject
4. Read the landmark paper: A Study on Multiple Linear Regression AnalysisCited 914 times
5. Go sideways: Bayesian multivariate linear regressionA closely related topic
6. Go sideways: Polynomial regressionA closely related topic

🏆 Landmark papers (most cited)

• A Study on Multiple Linear Regression Analysis

  Gülden Kaya Uyanık, Neşe Güler · 2013 · Procedia - Social and Behavioral Sciences · 914 citations

• A Robust Method for Multiple Linear Regression

  D. F. Andrews · 1974 · Technometrics · 490 citations

• Predicting Multivariate Responses in Multiple Linear Regression

  Leo Breiman, Jerome H. Friedman · 1997 · Journal of the Royal Statistical Society Series B: Statistical Methodology · 383 citations

• Advanced Statistics: Linear Regression, Part II: Multiple Linear Regression

  Keith A. Marill · 2004 · Academic Emergency Medicine · 205 citations

• Multiple linear regression

  Martin Krzywinski, Naomi Altman · 2015 · Nature Methods · 164 citations

• Multiple Linear Regression

  Bryan K. Slinker, Stanton A. Glantz · 2008 · Circulation · 102 citations

• Etemadi multiple linear regression

  Sepideh Etemadi, Mehdi Khashei · 2021 · Measurement · 76 citations

• Advanced Statistics: Linear Regression, Part II: Multiple Linear Regression

  Keith A. Marill · 2004 · Academic Emergency Medicine · 70 citations

🆕 Influential since 2022

• Multiple Linear Regression Model for Improved Project Cost Forecasting

  Filippo Maria Ottaviani, Alberto De Marco · 2022 · Procedia Computer Science · 53 citations

• Estimating PM2.5 utilizing multiple linear regression and ANN techniques

  Sumita Gulati, Anshul Bansal, Ashok Pal · 2023 · Scientific Reports · 48 citations

• The OWA operator in multiple linear regression

  Martha Flores-Sosa, Ezequiel Avilés-Ochoa, José M. Merigó · 2022 · Applied Soft Computing · 35 citations

• Fuzzy multiple linear least squares regression analysis

  Yingfang Li, Xingxing He, Xueqin Liu · 2023 · Fuzzy Sets and Systems · 20 citations

• Multicollinearity in Multiple Linear Regression: Detection, Consequences, and Remedies

  Siddamsetty Upendra, Dr. R. Abbaiah, Dr. P. Balasiddamuni · 2023 · International Journal for Research in Applied Science and Engineering Technology · 15 citations

📚 Books worth reading

• 📕Anwendung von multiplen Testprozeduren im linearen RegressionsmodellRaimund Alt · 1986

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics

• Bayesian multivariate linear regression In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted…
• Polynomial regression In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable…
• Gauss–Markov theorem In statistics, the Gauss–Markov theorem (or simply Gauss theorem for some authors) states that, under certain conditions, the ordinary least squares (OLS)…
• Bayesian linear regression Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables…
• Multinomial logistic regression In statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than…
• Confidence region In statistics, a confidence region is a multivariate generalization of a confidence interval. For a bivariate normal distribution, it is an ellipse, also…
• Principal component regression In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). PCR is a form…
• Heteroskedasticity-consistent standard errors The topic of heteroskedasticity-consistent (HC) standard errors arises in statistics and econometrics in the context of linear regression and time series…