box_cox: Compare the Box-Cox Transformation at Different Levels of...
In ryan-heslin/RegLesson: Linear Regression from Scratch
box_cox R Documentation
Compare the Box-Cox Transformation at Different Levels of λ
Description
Compare the Box-Cox Transformation at Different Levels of λ
Usage
box_cox(X, Y, lambdas, n = NROW(Y))
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.
lambdas
Vector of values of λ. The transformation entails raising Y to the power of λ, or logging it in the case of λ = 0.
n
Number of rows in the design matrix.
Details
This function assess the Box-Cox transformation at different values of
λ, the tuning parameter. The best corresponds to the lowest model SSE.
Value
Two-column matrix with the vector of λ in one column and the estimated SSE in the other.
ryan-heslin/RegLesson documentation built on Aug. 5, 2022, 9:03 p.m.
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| box_cox | R Documentation |
Compare the Box-Cox Transformation at Different Levels of λ
Description
Compare the Box-Cox Transformation at Different Levels of λ
Usage
box_cox(X, Y, lambdas, n = NROW(Y))
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. |
lambdas |
Vector of values of λ. The transformation entails raising Y to the power of λ, or logging it in the case of λ = 0. |
n |
Number of rows in the design matrix. |
Details
This function assess the Box-Cox transformation at different values of λ, the tuning parameter. The best corresponds to the lowest model SSE.
Value
Two-column matrix with the vector of λ in one column and the estimated SSE in the other.
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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