In statistics, linear regression is a linear method to model the relationship between a scalar response (dependent variable), y, and one or more explanatory variables (independent variables), x, a vector. When there is only one explanatory variable, it is called simple linear regression. When there is more than one explanatory variable, it is called multiple linear regression. The parameters of such a linear model, β, are the coefficients for the explanatory variables. The parameters are estimated from the data. When such a linear model is used to predict the outcome of the response given ...
© Haksun Li, PhD 2022
H. Li, PhDNumerical Methods Using Javahttps://doi.org/10.1007/978-1-4842-6797-4_1414. Linear Regression
Haksun Li, PhD1
(1)
Hong Kong, China
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