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Penalized regression methods for simultaneous variable selection and coefficient estimation, especially those based on the lasso of Tibshirani (1996), have received a great deal of attention in recent years, mostly through frequentist models. Properties such as consistency have been studied, and are achieved by different lasso variations. Here we look at a… (More)

- Jeff Gill, George Casella
- 2009

A generalized linear mixed model, ordered probit, is used to estimate levels of stress in presidential political appointees as a means of understanding their surprisingly short tenures. A Bayesian approach is developed, where the random effects are modeled with a Dirichlet process mixture prior, allowing for useful incorporation of prior information, but… (More)

We describe some progress toward a common framework for statistical analysis and software development built on and within the R language, including R’s numerous existing packages. The framework we have developed offers a simple unified structure and syntax that can encompass a large fraction of statistical procedures already implemented in R, without… (More)

- Andrew J Whelton, LaKia McMillan, +6 authors Caroline Novy
- Environmental science & technology
- 2015

During January 2014, an industrial solvent contaminated West Virginia’s Elk River and 15% of the state population’s tap water. A rapid in-home survey and water testing was conducted 2 weeks following the spill to understand resident perceptions, tap water chemical levels, and premise plumbing flushing effectiveness. Water odors were detected in all 10 homes… (More)

We develop a new Gibbs sampler for a linear mixed model with a Dirichlet process random effect term, which is easily extended to a generalized linear mixed model with a probit link function. Our Gibbs sampler exploits the properties of the multinomial and Dirichlet distributions, and is shown to be an improvement, in terms of operator norm and efficiency,… (More)

An alternative to the classical mixedmodel with normal random effects is to use a Dirichlet process to model the random effects. Such models have proven useful in practice, and we have observed a noticeable variance reduction, in the estimation of the fixed effects, when the Dirichlet process is used instead of the normal. In this paper we formalize this… (More)

- Jeff Gill, Jason Gainous
- 2003

The purpose of this article is to present a sample from the panoply of formal theories on voting and elections to Statistical Science readers who have had limited exposure to such work. These abstract ideas provide a framework for understanding the context of the empirical articles that follow in this volume. The primary focus of this theoretical literature… (More)

- Brady Jacob Rocks, Jeff Gill, Nalin M. Kumar, Peter M. Luthy, John Shareshian
- 2015

What should a researcher do when statistical analysis software terminates before completion with a message that the Hessian is not invertible? The standard textbook advice is to respecify the model, but this is another way of saying that the researcher should change the question being asked. Obviously, however, computer programs should not be in the… (More)