# NOT RUN {
# Number of Points
n = 1000
# Select beta parameters
beta = c(-2, 1.5, 3, 8.2, 6.6)
# Number of Predictors (including intercept)
p = length(beta)
# Generate predictors from a normal distribution
X_i = matrix(rnorm(n), ncol = p - 1)
# Add an intercept
X = cbind(1, X_i)
# Generate y values
y = X%*%beta + rnorm(n / (p - 1))
# Run optimization with lbfgs
theta_hat = lin_reg_lbfgs(X, y)
# Verify parameters were recovered
cbind(actual = beta, estimated = theta_hat)
# }
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