Maximum Likelihood With a Time Varying Parameter
In: Statistical papers, Band 65, Heft 4, S. 2555-2566
ISSN: 1613-9798
AbstractWe consider the problem of tracking an unknown time varying parameter that characterizes the probabilistic evolution of a sequence of independent observations. To this aim, we propose a stochastic gradient descent-based recursive scheme in which the log-likelihood of the observations acts as time varying gain function. We prove convergence in mean-square error in a suitable neighbourhood of the unknown time varying parameter and illustrate the details of our findings in the case where data are generated from distributions belonging to the exponential family.