1,222 research outputs found
Generative AI for Data Science 101: Coding Without Learning To Code
Should one teach coding in a required introductory statistics and data
science class for non-technical students? Many professors advise against it,
considering it a distraction from the important and challenging statistical
topics that need to be covered. By contrast, other professors argue that the
ability to interact flexibly with data will inspire students with a lasting
love of the subject and a continued commitment to the material beyond the
introductory course. With the release of large language models that write code,
we saw an opportunity for a middle ground, which we tried in Fall 2023 in a
required introductory data science course in our school's full-time MBA
program. We taught students how to write English prompts to the AI tool Github
Copilot that could be turned into R code and executed. In this short article,
we report on our experience using this new approach
Empirical Bayes Prediction for the Multivariate Newsvendor Loss Function
We develop a novel Empirical Bayes methodology for prediction under check loss in high-dimensional Gaussian models. The check loss is a piecewise linear loss function having differential weights for measuring the amount of underestimation or overestimation. Prediction under it differs in fundamental aspects from estimation or prediction under weighted-quadratic losses. Because of the nature of this loss, our inferential target is a pre-chosen quantile of the predictive distribution rather than the mean of the predictive distribution. We develop a new method for constructing uniformly efficient asymptotic risk estimates which are then minimized to produce effective linear shrinkage predictive rules. In calculating the magnitude and direction of shrinkage, our proposed predictive rules incorporate the asymmetric nature of the loss function and are shown to be asymptotically optimal. Using numerical experiments we compare the performance of our method with traditional Empirical Bayes procedures and obtain encouraging results
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