casl_glenet: Compute generalized linear elastic net with coordinate...
In BillyTian/bis557: Package containing assignments, projects or other products in BIS557
Description
Usage
Arguments
Value
Author(s)
References
Description
Compute generalized linear elastic net with coordinate descent.
Usage
1
2
casl_glenet(X, y, lambda, alpha = 1, family = stats::binomial(),
maxit = 10000L, tol = 1e-05)
Arguments
X
A numeric data matrix.
y
Response vector.
lambda
The penalty term.
alpha
Value from 0 and 1; balance between l1/l2 penalty.
family
Instance of an R family object.
maxit
Integer maximum number of iterations.
tol
Numeric tolerance parameter.
Value
Regression vector beta of length ncol(X).
Author(s)
Taylor Arnold, Michael Kane, Bryan Lewis.
References
Taylor Arnold, Michael Kane, and Bryan Lewis.
A Computational Approach to Statistical Learning.
Chapman & Hall/CRC Texts in Statistical Science, 2019.
BillyTian/bis557 documentation built on Dec. 19, 2020, 7:30 a.m.
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Description Usage Arguments Value Author(s) References
Description
Compute generalized linear elastic net with coordinate descent.
Usage
1 2 | casl_glenet(X, y, lambda, alpha = 1, family = stats::binomial(),
maxit = 10000L, tol = 1e-05)
|
Arguments
X |
A numeric data matrix. |
y |
Response vector. |
lambda |
The penalty term. |
alpha |
Value from 0 and 1; balance between l1/l2 penalty. |
family |
Instance of an R |
maxit |
Integer maximum number of iterations. |
tol |
Numeric tolerance parameter. |
Value
Regression vector beta of length ncol(X).
Author(s)
Taylor Arnold, Michael Kane, Bryan Lewis.
References
Taylor Arnold, Michael Kane, and Bryan Lewis. A Computational Approach to Statistical Learning. Chapman & Hall/CRC Texts in Statistical Science, 2019.
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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