Aim This study focuses on the influence of methodological choices on the predictive performance of macroecological models (MEMs), i.e. statistical models designed to predict patterns of biodiversity using environmental predictors. We emphasize the influence of three methodological choices: (1) the choice of the currency in which the abundance of each species is measured, i.e. numbers of individ...

The purpose of this paper is to draw attention to the widespread occurrence of quotient spaces in statistical work. Quotient spaces are intrinsic to probability distributions, residuals and interaction in linear models, covariance functions and variograms of stochastic processes, etc. The theme is that explicit recognition of the quotient space can offer surprising conceptual simplification. Th...

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. ...

In this paper, we use a novel duration model to study joint retirement in married couples using the Health and Retirement Study. Whereas conventionally used models cannot account for joint retirement, our model admits joint retirement with positive probability and nests the traditional proportional hazards model. In contrast to other statistical models for simultaneous durations, it is based on...

In recent years, the class of generalized linear models has gained popularity as a statistical modeling tool. This popularity is due in part to the flexibility of generalized linear models in addressing a variety of statistical problems and to the availability of software to fit the models. The SAS system provides two new tools that fit generalized linear models. The GENMOD procedure in SAS/ST...