Proper linear model

From Wikipedia, the free encyclopedia
Revision as of 18:02, 25 October 2023 by imported>Citation bot (Removed proxy/dead URL that duplicated identifier. | Use this bot. Report bugs. | #UCB_CommandLine)
(diff) ← Previous revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

In statistics, a proper linear model is a linear regression model in which the weights given to the predictor variables are chosen in such a way as to optimize the relationship between the prediction and the criterion. Simple regression analysis is the most common example of a proper linear model. Unit-weighted regression is the most common example of an improper linear model.

Bibliography

  • Script error: No such module "Citation/CS1".


Template:Asbox