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Articles 1 - 3 of 3
Full-Text Articles in Statistical Models
Reevaluating Texas Energy Market Forecasts In The Wake Of Recent Extreme Weather Events, Robert A. Derner, Richard W. Butler Ii, Alexandria Neff, Adam R. Ruthford
Reevaluating Texas Energy Market Forecasts In The Wake Of Recent Extreme Weather Events, Robert A. Derner, Richard W. Butler Ii, Alexandria Neff, Adam R. Ruthford
SMU Data Science Review
This paper provides updated forecasts of energy demand in Texas and recognizes the impact of sustainable energy. It is important that the forecasts of the adoption of sustainable energy are reexamined after Winter Storm Uri crippled the Texas power grid and left many without power. This storm highlighted the issues the Texas power grid had and has continued to struggle with in supplying the state with energy. This paper will offer an overview of the relevant literature on the adoption of sustainable energy and relevant events that have occurred in the state of Texas that will give the reader the …
Predicting Insulin Pump Therapy Settings, Riccardo L. Ferraro, David Grijalva, Alex Trahan
Predicting Insulin Pump Therapy Settings, Riccardo L. Ferraro, David Grijalva, Alex Trahan
SMU Data Science Review
Millions of people live with diabetes worldwide [7]. To mitigate some of the many symptoms associated with diabetes, an estimated 350,000 people in the United States rely on insulin pumps [17]. For many of these people, how effectively their insulin pump performs is the difference between sleeping through the night and a life threatening emergency treatment at a hospital. Three programmed insulin pump therapy settings governing effective insulin pump function are: Basal Rate (BR), Insulin Sensitivity Factor (ISF), and Carbohydrate Ratio (ICR). For many people using insulin pumps, these therapy settings are often not correct, given their physiological needs. While …
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, Robert Slater
Demand Forecasting In Wholesale Alcohol Distribution: An Ensemble Approach, Tanvi Arora, Rajat Chandna, Stacy Conant, Bivin Sadler, Robert Slater
SMU Data Science Review
In this paper, historical data from a wholesale alcoholic beverage distributor was used to forecast sales demand. Demand forecasting is a vital part of the sale and distribution of many goods. Accurate forecasting can be used to optimize inventory, improve cash ow, and enhance customer service. However, demand forecasting is a challenging task due to the many unknowns that can impact sales, such as the weather and the state of the economy. While many studies focus effort on modeling consumer demand and endpoint retail sales, this study focused on demand forecasting from the distributor perspective. An ensemble approach was applied …