calc_pred_moments {shrinkGPR}R Documentation

Calculate Predictive Moments

Description

calc_pred_moments calculates the predictive means and variances for a fitted shrinkGPR model at new data points.

Usage

calc_pred_moments(object, newdata, nsamp = 100)

Arguments

object

A shrinkGPR object representing the fitted Gaussian process regression model.

newdata

Optional data frame containing the covariates for the new data points. If missing, the training data is used.

nsamp

Positive integer specifying the number of posterior samples to use for the calculation. Default is 100.

Details

This function computes predictive moments by marginalizing over posterior samples from the fitted model. If the mean equation is included in the model, the corresponding covariates are used.

Value

A list with two elements:

Examples


if (torch::torch_is_installed()) {
  # Simulate data
  set.seed(123)
  torch::torch_manual_seed(123)
  n <- 100
  x <- matrix(runif(n * 2), n, 2)
  y <- sin(2 * pi * x[, 1]) + rnorm(n, sd = 0.1)
  data <- data.frame(y = y, x1 = x[, 1], x2 = x[, 2])

  # Fit GPR model
  res <- shrinkGPR(y ~ x1 + x2, data = data)

  # Calculate predictive moments
  momes <- calc_pred_moments(res, nsamp = 100)
  }


[Package shrinkGPR version 1.0.0 Index]