cossonet.predict: The function 'cossonet.predict' predicts predictive values...

In cossonet: Sparse Nonparametric Regression for High-Dimensional Data

The function cossonet.predict predicts predictive values for new data based on an object from the cossonet function.

Description

The function cossonet.predict predicts predictive values for new data based on an object from the cossonet function.

Usage

cossonet.predict(model, testx)

Arguments

model	The fitted cossonet object.
testx	The new data set to be predicted.

Value

A list of predicted values for the new data set.

Examples

set.seed(20250101)
tr = data_generation(n = 200, p = 20, SNR = 9, response = "continuous")
tr_x = tr$x
tr_y = tr$y

te = data_generation(n = 1000, p = 20, SNR = 9, response = "continuous")
te_x = te$x
te_y = te$y

# Fit the model
fit = cossonet(tr_x, tr_y, family = 'gaussian', gamma = 0.95, kernel = "spline", scale = TRUE,
      lambda0 = exp(seq(log(2^{-4}), log(2^{0}), length.out = 20)),
      lambda_theta = exp(seq(log(2^{-8}), log(2^{-6}), length.out = 20))
      )

# Predict new dataset
pred = cossonet.predict(fit, te_x)

cossonet documentation built on April 3, 2025, 8:12 p.m.