simple_ols: Conduct Simple Linear Regression
In ryan-heslin/RegLesson: Linear Regression from Scratch
simple_ols R Documentation
Conduct Simple Linear Regression
Description
Conduct Simple Linear Regression
Usage
simple_ols(X, Y, add_intercept = FALSE)
Arguments
X
An n \times m design matrix, optionally with an intercept column present.
Y
An n-length vector or n \times 1 matrix representing the response.
add_intercept
Logical. Should an intercept column (a column of 1s) be added to X?
Details
This function finds the minimum-norm least squares solution of X^T X β = X^T Y.
Value
Vector of estimated beta coefficients.
ryan-heslin/RegLesson documentation built on Aug. 5, 2022, 9:03 p.m.
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| simple_ols | R Documentation |
Conduct Simple Linear Regression
Description
Conduct Simple Linear Regression
Usage
simple_ols(X, Y, add_intercept = FALSE)
Arguments
X |
An n \times m design matrix, optionally with an intercept column present. |
Y |
An n-length vector or n \times 1 matrix representing the response. |
add_intercept |
Logical. Should an intercept column (a column of 1s) be added to |
Details
This function finds the minimum-norm least squares solution of X^T X β = X^T Y.
Value
Vector of estimated beta coefficients.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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