arXiv subjects

Jane L. Harvill

Publications and source records attributed to Jane L. Harvill.

4 recordsLinked to original sources

arXiv2024

Evaluating Approximations of Count Distributions and Forecasts for Poisson-Lindley Integer Autoregressive Processes

Although many time series are realizations from discrete processes, it is often that a continuous Gaussian model is implemented for modeling and forecasting the data, resulting in incoherent forecasts. Forecasts using a Poisson-Lindley integer autoregressive (PLINAR) model are compared to variations of Gaussian forecasts via simulation by equating relevant moments of the marginals of the PLINAR to the Gaussian AR. To illustrate utility, the methods discussed are applied and compared using a discrete series with model parameters being estimated using each of conditional least squares, Yule-Walker, and maximum likelihood.

stat.ME↗

arXiv2022

Converting College Football Point Spread Differentials to Probabilities

For NCAA football, we provide a method for sports bettors to determine if they have a positive expected value bet based on the betting lines available to them and how they believe the game will end. The method we develop modifies probabilities based on a normal distribution using historical data. The result is that more common point differentials are given appropriate weights. We provide a freely available online tool for implementing our technique.

stat.AP↗

arXiv2022

Bayesian estimation of in-game home team win probability for Division-I FBS college football

Maddox, et al. [9, 10] establish Bayesian methods for estimating home-team in-game win probability for college and NBA basketball. This paper introduces a Bayesian approach for estimating in-game home-team win probability for Division-I FBS college (American) football that uses expected number of remaining possessions and expected score as two predictors. Models for estimating these are presented and compared. These, along with other predictors are introduced into two Bayesian approaches for the final estimate of in-game home-team win probability. To illustrate utility, methods are applied to the 2021 Big XII Conference Football Championship game between Baylor and Oklahoma State.

stat.ME↗

arXiv2022

Bayesian estimation of in-game home team win probability for National Basketball Association games

Maddox, et al. (2022) establish a new win probability estimation for college basketball and compared the results with previous methods of Stern (1994), Desphande and Jensen (2016) and Benz (2019). This paper proposes modifications to the approach of Maddox, et al. (2022) for the NBA game and investigates the performance of the model. Enhancements to the model are developed, and the resulting adjusted model is compared with existing methods and to the ESPN counterpart. To illustrate utility, all methods are applied to the November 23, 2019 game between the Chicago Bulls and Charlotte Hornets.

stat.AP↗