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Articles 1 - 7 of 7
Full-Text Articles in Statistical Methodology
Major And Institution Transfer Path Combinations And The Relaxed Lasso Method: Parsimonious Prediction Of Vertical Transfer Student Success, David Wutchiett, A. W. Logue, Martin Kurzweil, Colin Chellman
Major And Institution Transfer Path Combinations And The Relaxed Lasso Method: Parsimonious Prediction Of Vertical Transfer Student Success, David Wutchiett, A. W. Logue, Martin Kurzweil, Colin Chellman
Publications and Research
The majors, institutions, and their combinations, which characterize transfer between higher education institutions relate to student success but introduce high-dimensionality and multicollinearity to statistical modeling. Relaxed lasso regression, a procedure blending regularized lasso models with unregularized refit models, selects variables and facilitates unbiased coefficient estimation in high-dimensional settings. Using a large sample of students transferring from associate to bachelor’s programs (n=28,166), we compared lasso and ridge regression parsimonious models predicting bachelor’s graduation and posttransfer GPA improvement, evaluating associations using unregularized parsimonious predictive models. Relaxed lasso parsimonious optimal models outperformed standard lasso and ridge regression models while including few of 702 …
Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri
Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri
Publications and Research
Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years …
What’S Brewing? A Statistics Education Discovery Project, Marla A. Sole, Sharon L. Weinberg
What’S Brewing? A Statistics Education Discovery Project, Marla A. Sole, Sharon L. Weinberg
Publications and Research
We believe that students learn best, are actively engaged, and are genuinely interested when working on real-world problems. This can be done by giving students the opportunity to work collaboratively on projects that investigate authentic, familiar problems. This article shares one such project that was used in an introductory statistics course. We describe the steps taken to investigate why customers are charged more for iced coffee than hot coffee, which included collecting data and using descriptive and inferential statistical analysis. Interspersed throughout the article, we describe strategies that can help teachers implement the project and scaffold material to assist students …
Teaching Size And Power Properties Of Hypothesis Tests Through Simulations, Suleyman Taspinar, Osman Dogan
Teaching Size And Power Properties Of Hypothesis Tests Through Simulations, Suleyman Taspinar, Osman Dogan
Publications and Research
In this study, we review the graphical methods suggested in Davidson and MacKinnon (Davidson, Russell, and James G. MacKinnon. 1998. “Graphical Methods for Investigating the Size and Power of Hypothesis Tests.” The Manchester School 66 (1): 1–26.) that can be used to investigate size and power properties of hypothesis tests for undergraduate and graduate econometrics courses. These methods can be used to assess finite sample properties of various hypothesis tests through simulation studies. In addition, these methods can be effectively used in classrooms to reinforce students’ understanding of basic hypothesis testing concepts such as Type I error, Type II error, …
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
Publications and Research
Forecasters often encounter situations in which the local pattern of a time series is not expected to persist over the forecasting horizon. Since exponential smoothing models emphasize recent behavior, their forecasts may not be appropriate over longer horizons. In this paper, we develop a new model in which the local trend line projected by exponential smoothing converges asymptotically to an assumed future long-run trend line, which might be an extension of a historical long-run trend line. The rapidity of convergence is governed by a parameter. A familiar example is an economic series exhibiting persistent long-run trend with cyclic variation. This …
Performance Indices For On-Ice Hockey Statistics, William (Bill) H. Williams
Performance Indices For On-Ice Hockey Statistics, William (Bill) H. Williams
Publications and Research
No abstract provided.
A Simple Method For The Construction Of Empirical Confidence Limits For Economic Forecasts, William (Bill) H. Williams, M. L. Goodman
A Simple Method For The Construction Of Empirical Confidence Limits For Economic Forecasts, William (Bill) H. Williams, M. L. Goodman
Publications and Research
A simple method for the construction of empirical confidence intervals for time series forecasts is described. The procedure is to go through the series making a forecast from each point in time. The comparison of these forecasts with the known actual observations will yield an empirical distribution of forecasting errors. This distribution can then be used to set confidence intervals for subsequent forecasts. The technique appears to be particularly useful when the mechanism generating the series cannot be fully identified from the available data or when limits based on more standard considerations are difficult to obtain.