gino wrote: > Because MLE gives a lot of local minimum, and depending on the initial > values, the optimum points jump around; it is really hard to harness. And in > our optimization procedure using Matlab's "fmincon", some unwanted > points(often boundary) give -infinity, which became our global minimum, > which is definitely undesirable... > > We'd like to try out other alternatives other than MLE. From data we don't > neccessarily know if they are with normal errors or not... thus do you still > have theoretical results showing that KF is exactly the same as MLE?
The KF estimates the mean and variance of a state space model; the usual SSM has normal errors.
If the actual likelihood of your model is badly behaved, the KF won't solve that.
If the model is fine and it's a problem with MATLAB's optimization, then many things may work.