Suppose I have a multiple linear regression model $$ Y=\beta_0+\beta_1X_1+\cdots+\beta_pX_p+\epsilon$$ How can I obtain the regression coefficients $\hat{\beta_i}$ by fitting just a series of simple linear regression models (additionally using sample means of the response/predictor variables if needed)?


marked as duplicate by whuber regression Feb 28 at 14:56

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

  • $\begingroup$ Why would you? If this is homework, please use the self-study tag. Hint: you could search this site for "Frisch Waugh Lovell". $\endgroup$ – Christoph Hanck Feb 28 at 11:02
  • $\begingroup$ Alternatively, look into Gram-Schmidt orthogonalization. $\endgroup$ – Glen_b Feb 28 at 12:12