What is the main difference between the two functions, the r Help manual says that gosolnp helps to set the initial parameters correctly. Is there any difference otherwise? Also, if so is the case, how do we determine the correct distribution type for the parameter space?
In my problem, the initial set of parameters is difficult to determine, which is why the optimization problem is used. However, I have idea about the parameter upper and lower bounds.
gsolnp is an extension of solnp, a wrapper, allowing for multiple restarts. Simply put, it uses solnp several times (controllable by n.restarts) to avoid getting stuck in local minima. If your function is known to have no local minima (e.g., it is convex, which can be derived analytically), use solnp to save time. Otherwise, use gsolnp. If you know any additional information (for instance, an area where a global minimum is supposed to be), you may use it for finer control of the starting parameter distribution: see parameters distr and distr.opt.
