Bayesian inference about small areas is of considerable current interest, and simultaneous intervals for the parameters for the areas are needed because these parameters are correlated. This is not usually pursued because with many areas the problem becomes difficult. We describe a method for finding simultaneous credible intervals for a relatively large number of parameters, each corresponding...

A recipe is provided for producing, from a sequence of procedures in the Gaus-sian regression model, an asymptotically equivalent sequence in the density estimation model with i. i. d. observations. The recipe is, to put it roughly, to calculate normalised frequencies over certain intervals, add a small random distortion, calculate square roots, and pretend these to be observations from a Gauss...

BACKGROUND The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some ...

Statistical methodology is presented for the statistical analysis of nonlinear measurement error models. Our approach is to provide adjustments for the usual maximum likelihood es-timators, their standard errors and associated signiicance tests in order to account for the presence of measurement error in some of the covariates. We illustrate the technique with a mixed eeects Poisson regression ...

Multiple response categorical variables (MRCVs), also known as “pick any” or “choose all that apply” variables, summarize survey questions for which respondents are allowed to select more than one category response option. Traditional methods for analyzing the association between categorical variables are not appropriate with MRCVs due to the within-subject dependence among responses. We have d...

We generalize to the arithmetic Walsh transform (AWT) some results which were previously known for the Walsh Hadamard transform of Boolean functions. We first generalize the classical Poisson summation formula to the AWT. We then define a generalized notion of resilience with respect to an arbitrary statistical measure of Boolean functions. We apply the Poisson summation formula to obtain a con...

We present a method to discover robust and interpretable sociolinguistic associations from raw geotagged text data. Using aggregate demographic statistics about the authors’ geographic communities, we solve a multi-output regression problem between demographics and lexical frequencies. By imposing a composite `1,∞ regularizer, we obtain structured sparsity, driving entire rows of coefficients t...

Over the last 20 to 30 years, there has been a significant amount of tools and statistical methods that have been proposed for analyzing crash data. Yet, the Poisson-gamma (PG) is still the most commonly used and widely acceptable model. This paper documents the application of the Poisson-Weibull (PW) generalized linear model (GLM) for modeling motor vehicle crashes. The objectives of this stud...

Extreme droughts and high temperatures have becomemore frequent in the last two decades, increasing fire risk in the Amazon. The overarching goal of this study is to shed light on the influence of temperature and rainfall on fire occurrence for the 1998–2013 period. We use a Poisson regression to model satellite-based monthly fire counts across the Brazilian Amazon as a function of observed rai...

A multivariate expectile regression model is proposed to analyze the tail events of large cross-sectional and spatial data, when the tail events are linked by a latent factor structure. The computational advantage of the method is demonstrated, and the estimation risk is analyzed for every fixed number of iteration and fixed sample size, when the latent factors are either exactly or approximate...