Given distinct climatic periods in the various facets of the Earth’s climate system, many attempts have been made to determine the exact timing of ‘change points’ or regime boundaries.

However, identification of change points is not always a simple task. A time series containing N data points has approximately N k distinct placements of k change points, rendering brute force enumeration futile as the length of the time series increases.

Moreover, how certain are we that any one placement of change points is superior to the rest?

Dr. Eric Ruggieri, College of the Holy Cross, will speak on this topic Wednesday, Oct. 9, 4-5 p.m., in room 308 of the Feinstein Building at Providence College.

In his talk, titled “A Bayesian Approach to Detecting Change Points in Climatic Records,” Dr. Ruggieri will describe a Bayesian Change Point algorithm, which provides uncertainty estimates both in the number and location of change points through an efficient probabilistic solution to the multiple change point problem.

To illustrate the algorithm, he will talk about its application to the NOAA/NCDC annual global surface temperature anomalies time series, which has often been cited as evidence of global warming, as well as a much longer 5 million year record of global ice volume.

Dr. Ruggieri earned his B.A. in Mathematics and Computer Science from Providence College (’05) and his Sc.M. and Ph.D. in Applied Mathematics from Brown University. For the past three years, Dr. Ruggieri was an Assistant Professor of Statistics at Duquesne University before joining the faculty at Holy Cross this fall.