Time Series Analysis (online)

This course is CANCELLED.

This one-day course will be offered via Zoom only. Course schedule is 10:00am – 4:00pm, with a 1 hour lunch and (2) 10 minute breaks (1 in morning and 1 in afternoon). Attendance is required as it will not be recorded.

Description: This course will be a brief and thorough introduction to modern methods of time series analysis. Topics to be covered include elementary time series models, trend and seasonality, stationary processes, autoregressive/integrated/moving average (ARIMA) processes, fitting ARIMA models, forecasting, spectral analysis, the periodogram, spectral estimation techniques, multivariate time series. Additional topics may be covered if time permits. Some applications will be provided to illustrate the usefulness of the techniques.

Prerequisites:
Course in probability and statistics and familiarity with matrix theory and linear algebra.

Course Goals:
This course will provide students with a theoretical foundation in the analysis of time series in the time domain including identification, estimation, and prediction in several well-established time series models.

Course Objectives:
By the end of the course, you will be able to:
• Analyze datasets to construct plausible time series models
• Estimate parameters of ARMA and ARIMA models
• Model and forecast with ARMA, ARIMA and SARIMA processes
• Analyze multivariate time series models

Instructor: Moustapha Pemy

Moustapha Pemy received his bachelor’s degree in mathematics in 1996 and his master’s degree in 1998 at the University of Yaoundé 1 in Cameroon. In 2000 he joined the Diploma Program of the Abdus Salam International Centre for Theoretical Physics in Trieste, Italy. He completed this program in August 2001. In 2005, he received a Ph.D. in Mathematics from the University of Georgia. He then spent one year at the Centre for Research in Scientific Computation at North Carolina State University as a research assistant and at the Statistical and Applied Mathematical Sciences Institute in Raleigh, North Carolina. He joined the Department of Mathematics of Towson University in August 2006 and is currently a full professor. He was the director of the master’s program in Applied and Industrial Mathematics from August 2013 to August 2016. In the summer of 2007, he was appointed adjunct faculty at the JHU Whiting School of Engineering. His research interests include Stochastic Analysis, Control Theory, Mathematical Finance, Mathematical Economics, and Applied Probability. He has authored and co-authored numerous peer-reviewed papers on those topics.

Registration fees:

• UNC-CH Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
• UNC-CH Faculty/Staff/Postdoc: $95
• Non UNC-CH: $145

Additional course information:

• Registration closes at 12:01am, February 26, 2023. Once registration closes, no late registrations will be accepted, no exceptions.
• Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
• Zoom link for this course will be sent prior to the course. Registration must be made at least 3 days prior to the course date to receive the Zoom link.

For questions regarding the this class, please contact Jill Stevens at jill_stevens@unc.edu