MLE_linear: MLE estimator for linear 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 independent variables, apply MLE estimator, and returned corrected coefficient estimates.
Usage
1
MLE_linear(formula, data, predicted_col_name, ppv = 0, npv = 0)
Arguments
formula
R formula, such as y ~ x
data
a data.frame object
predicted_col_name
string or integer indicating the column of the variable that is predicted
ppv
positive predicted value
npv
negative predicted value
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 independent variables, apply MLE estimator, and returned corrected coefficient estimates.
Usage
1 | MLE_linear(formula, data, predicted_col_name, ppv = 0, npv = 0)
|
Arguments
formula |
R formula, such as y ~ x |
data |
a data.frame object |
predicted_col_name |
string or integer indicating the column of the variable that is predicted |
ppv |
positive predicted value |
npv |
negative predicted value |
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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