#### Filter Results:

- Full text PDF available (32)

#### Publication Year

1999

2017

- This year (5)
- Last 5 years (16)
- Last 10 years (31)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

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)

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)

- 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)

- JEFF GILL, GEORGE CASELLA
- 2010

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)

- 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)

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, Lee D. Walker
- 2013

- Brady Jacob Rocks, Jeff Gill, N. Mohan Kumar, Peter 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)

- Ruth E. Patterson, Graham A. Colditz, +42 authors Mark D. Thornquist
- Cancer Causes & Control
- 2013

Recognition of the complex, multidimensional relationship between excess adiposity and cancer control outcomes has motivated the scientific community to seek new research models and paradigms. The National Cancer Institute developed an innovative concept to establish a center grant mechanism in nutrition, energetics, and physical activity, referred to as… (More)