Statistics Colloquium by Gracie Guidotti '23

Predicting the Distribution of U.S. Residential Solar Arrays in the U.S. using Zero-Inflated Regression Models by Gracie Guidotti ’23, Statistics Colloquium, Wednesday, February 8, 1:10 – 1:50 pm, North Science Building 114, Wachenheim.

Abstract:  How can we model count data with a high amount of zeros?  We will explore how the zero-inflated negative binomial regression model can be used to model over-dispersed and zero-inflated count data.  We will discuss the theory behind this model and explore how the expectation-maximization (EM) algorithm can be used to estimate the model parameters.  Lastly, we will examine how this model can be applied to a zero-inflated dataset of residential solar PV installations in the US.