Creating a newer, faster model for performing complex estimations
“Count data,” the number of times an event occurs within a given time interval, poses a number of statistical modeling challenges with widespread applications in web analytics, epidemiology, economics, finance, operations and other fields.
In 2018, Paul College associate professor of decision sciences Tevfik Aktekin developed a new class of statistical model that performs complex estimations roughly 20 times faster than other commonly used estimation methods. Aktekin dubbed the methodology the Multivariate Poisson-Scaled Beta (MPSB) and says it “can be applied to many settings where there is a need for fast and efficient demand forecasting of multiple series.”
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