Abstract
Using the maximum likelihood principle, nonparametric estimators are derived for discrete time nonhomogeneous Markov chains. As the number of observed chains becomes large, asymptotic unbiasedness and strong consistency of the estimators are proved, as well as asymptotic distribution results. Finally the estimators are compared with ones which have been proposed in continuous time.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
