Compare the estimated standard errors resulting from the

Question

Section 2.2.1 gives an example of how to estimate a logistic regression model by creating an R function to calculate the log-likelihood function and then maximize it using optim(). Following this example, write an R function that calculates the log likelihood function for the probit regression model. Use this function with optim() to estimate probit(π) = β₀ + β₁distance with the placekicking data set. Compare the estimated standard errors resulting from the use of optim() to those obtained from glm(). Repeat this process with the corresponding complementary log-log regression model.