sim_gp: Simulate data with measurment error from a Gaussian process...

In ncahill89/EIVmodels: Fit Errors-in-variables regression model

Simulate data with measurment error from a Gaussian process regression

Description

Simulate data with measurment error from a Gaussian process regression

Usage

sim_gp(
  n_sim = 50,
  min_x = 0,
  max_x = 2,
  alpha = 0,
  sigma_g = 2,
  phi = 2,
  sigma = 0.1,
  x_err = 0.1,
  y_err = 0.1
)

Arguments

n_sim	number of data points to simulate
min_x	Minimum x value
max_x	Maximum x value
alpha	regression intercept
sigma_g	GP variance parameter
phi	GP correlation parameter
sigma	nugget variation
x_err	x measurement error
y_err	y measurement error

Value

Simulated dataset with columns x, x_err, y, y_err

Examples

sim_gp(n_sim = 50)

ncahill89/EIVmodels documentation built on Dec. 5, 2022, 2:10 p.m.