Simulate data with measurment error from a change-point linear regression

Usage

sim_cp(
  n_sim = 50,
  min_x = 0,
  max_x = 2,
  alpha = 0,
  beta = c(1, 2),
  cp = 1,
  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
beta: Regression slope
cp: Change point
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_cp(n_sim = 50)
#> # A tibble: 50 × 6
#>        x x_err      y y_err true_y true_x
#>    <dbl> <dbl>  <dbl> <dbl>  <dbl>  <dbl>
#>  1 0.218   0.1 -0.623   0.1 -0.706  0.294
#>  2 0.548   0.1 -0.493   0.1 -0.423  0.577
#>  3 0.483   0.1 -0.675   0.1 -0.624  0.376
#>  4 0.314   0.1 -0.709   0.1 -0.698  0.302
#>  5 1.78    0.1  1.27    0.1  1.37   1.68 
#>  6 0.514   0.1 -0.578   0.1 -0.536  0.464
#>  7 1.31    0.1  0.506   0.1  0.566  1.28 
#>  8 1.26    0.1  0.518   0.1  0.488  1.24 
#>  9 1.92    0.1  1.77    0.1  1.78   1.89 
#> 10 1.68    0.1  1.19    0.1  1.12   1.56 
#> # … with 40 more rows