DGP_OLS <- function() { X <- runif(100,2,10) Y <- X + rnorm(100, sd = sqrt(X)) return( c("beta_1_hat" = sum(X*Y)/sum(X^2)) ) } set.seed(1) # generate 1000 estimates of beta_1 using `GDP_OLS()` and store them in `estimates` # estimate the variance of the estimator and assign the result to `est_var_OLS` set.seed(1) # generate 1000 estimates of beta_1 using `GDP_OLS()` and store them in `estimates` estimates <- replicate(1000, DGP_OLS()) # estimate the variance of the estimator and assign the result to `est_var_OLS` est_var_OLS <- var(estimates) test_predefined_objects("DGP_OLS") test_object("estimates") test_object("est_var_OLS")