regmod_regression {biosensors.usc} | R Documentation |
regmod_regression
Description
Performs the Wasserstein regression using quantile functions.
Usage
regmod_regression(data, response)
Arguments
data |
A biosensor object. |
response |
The name of the scalar response. The response must be a column name in data$variables. |
Value
An object of class bregmod containing the components:
beta
The beta coefficient functions of the fitting.
prediction
The prediction for each training data.
residuals
The residuals for each prediction value.
Examples
# Data extracted from the paper: Hall, H., Perelman, D., Breschi, A., Limcaoco, P., Kellogg, R.,
# McLaughlin, T., Snyder, M., Glucotypes reveal new patterns of glucose dysregulation, PLoS
# biology 16(7), 2018.
file1 = system.file("extdata", "data_1.csv", package = "biosensors.usc")
file2 = system.file("extdata", "variables_1.csv", package = "biosensors.usc")
data = load_data(file1, file2)
regm = regmod_regression(data, "BMI")
[Package biosensors.usc version 1.0 Index]