1. Provide instruction for an introduction to state space modeling. Explain the relation between SSM, maximum likelihood estimation, Kalman Filter and Kalman Smoother. Help interpret a few papers on the previously mentioned topics.
2. Provide instruction on running SSM analysis packages (dlm) on given data sets in the statistical software, R. Use other data sets to provide additional examples of running the dlm package in R.
TUTOR SESSIONS WILL BE HELD VIA SKYPE AND WILL BE SCHEDULED. THE FREELANCER SHOULD BE PREPARED TO ATTEND ALL SCHEDULED MEETINGS.
FREELANCER SHOULD HAVE MASTERY OF THE TOPICS AND SKILLS LISTED IN THIS PROJECT. MULTIPLE TUTORING SESSIONS WILL LIKELY BE REQUIRED. POTENTIAL FOR LONG-TERM WORKING RELATIONSHIP WILL BE AVAILABLE FOR THE AWARDED FREELANCER.