regmod_regression: regmod_regression

In glucodensities/biosensors.usc: Distributional Data Analysis Techniques for Biosensor Data

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")

glucodensities/biosensors.usc documentation built on May 12, 2022, 1:57 a.m.