MLE_logit: MLE estimator for logistic regression with binary...
In philohistoria/CCER: Correct Machine Learning Classification Error in Next-Step Regression
Description
Usage
Arguments
Value
Description
This functions takes binary classification as outcome variables, apply MLE estimator, and returned corrected coefficient estimates.
Usage
1
Arguments
formula
R formula, such as y ~ x
data
a data.frame object
fnr
false negative rate
fpr
false positive rate
Value
a dataframe contining estimated values, standard errors, z values and p values
philohistoria/CCER documentation built on Dec. 22, 2021, 7:50 a.m.
R Package Documentation
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Description Usage Arguments Value
Description
This functions takes binary classification as outcome variables, apply MLE estimator, and returned corrected coefficient estimates.
Usage
1 |
Arguments
formula |
R formula, such as y ~ x |
data |
a data.frame object |
fnr |
false negative rate |
fpr |
false positive rate |
Value
a dataframe contining estimated values, standard errors, z values and p values
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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