mus_glm: Generalized Matrix Uncertainty Selector for logistic...
In osorensen/hdme: High-Dimensional Regression with Measurement Error
mus_glm R Documentation
Generalized Matrix Uncertainty Selector for logistic regression
Description
Internal function.
Usage
mus_glm(W, y, lambda, delta, family = c("binomial", "poisson"), weights = NULL)
Arguments
W
Design matrix, measured with error.
y
Vector of the binomial response value.
lambda
Regularization parameter due to model error.
delta
Regularization parameter due to measurement error.
family
"binomial" or "poisson"
weights
Case weights.
Value
Intercept and coefficients at the values of lambda and delta specified.
osorensen/hdme documentation built on May 18, 2023, 11:35 p.m.
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| mus_glm | R Documentation |
Generalized Matrix Uncertainty Selector for logistic regression
Description
Internal function.
Usage
mus_glm(W, y, lambda, delta, family = c("binomial", "poisson"), weights = NULL)
Arguments
W |
Design matrix, measured with error. |
y |
Vector of the binomial response value. |
lambda |
Regularization parameter due to model error. |
delta |
Regularization parameter due to measurement error. |
family |
"binomial" or "poisson" |
weights |
Case weights. |
Value
Intercept and coefficients at the values of lambda and delta specified.
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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