In order to compute the optimal theta e.g. in logistic regression, I have to create a costFunction (the function to be minimized) which is then passed to fminunc in order to obtain the optimal theta. Also, if the gradient of costFunction can be computed, I set the 'GradObj' option to 'on' using
options = optimset('GradObj','on');
and code the costFunction so that it returns, as a second output argument, the gradient value g of X. Then I give
[theta, cost] = fminunc(@(t)(costFunction(t, X, y)), initial_theta, options);
where X is the data matrix and y the response. How can I implement the above in R?