nadayara_prediction: nadayara_prediction

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

nadayara_prediction

Description

Functional non-parametric Nadaraya-Watson prediction with 2-Wasserstein distance.

Usage

nadayara_prediction(nadaraya, Qpred, hs=NULL)

Arguments

nadaraya	A Nadaraya regression object.
Qpred	Quantile curves that will be used in the predictions
hs	Smoothing parameters for the predictions, by default hs = seq(0.8, 15, length = 200)

Value

An object of class bnadarayapred: prediction The Nadaraya-Watson prediction for the test data at each value of hs. hs Hs values used for the prediction.

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)
nada = nadayara_regression(data, "BMI")
# Example of prediction with the column mean of quantiles
npre = nadayara_prediction(nada, t(colMeans(data$quantiles$data)))

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