linreg_svd: Linear Regression Coefficients (Singular Value...
In jeksterslabds/jeksterslabRds: Jekster's Lab Data Science and Statistics
Description
Usage
Arguments
Value
Description
Estimates coefficients of a linear regression model
using the Singular Value Decomposition.
Usage
1
linreg_svd(X, y)
Arguments
X
The data matrix,
that is an n \times k matrix of n observations
of k regressors,
which includes a regressor whose value is 1 for each observation.
y
n \times 1 vector of observations on the regressand variable.
Value
Returns a k \times 1 matrix of k unknown regression coefficients
(\hat{β})
estimated using ordinary least squares.
jeksterslabds/jeksterslabRds documentation built on July 16, 2020, 3:41 p.m.
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Description Usage Arguments Value
Description
Estimates coefficients of a linear regression model using the Singular Value Decomposition.
Usage
1 | linreg_svd(X, y)
|
Arguments
X |
The data matrix, that is an n \times k matrix of n observations of k regressors, which includes a regressor whose value is 1 for each observation. |
y |
n \times 1 vector of observations on the regressand variable. |
Value
Returns a k \times 1 matrix of k unknown regression coefficients (\hat{β}) estimated using ordinary least squares.
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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