This paper proposes a flexible modeling approach for so-called comet assay data regularly encountered in preclinical research. While such data consist of non-Gaussian outcomes in a multilevel hierarchical structure, traditional analyses typically completely or partly ignore this hierarchical nature by summarizing measurements within a cluster. Non-Gaussian outcomes are often modeled using expon...

This paper presents a new method to estimate systematic errors in the maximum-likelihood regression of count data. The is applicable particular X-ray spectra situations where Poisson log-likelihood, or Cash goodness-of-fit statistic, indicate poor fit that attributable overdispersion Overdispersion data treated as an intrinsic model variance can be estimated from best-fit model, using Cmin stat...

The significance of single-cell transcription resides not only in the cumulative expression strength of the cell population but also in its heterogeneity. We propose a new model that improves the detection of changes in the transcriptional heterogeneity pattern of RNA-Seq data using two heterogeneity parameters: ‘burst proportion’ and ‘burst magnitude’, whose changes are validated using RNA-FIS...

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 ...

During the past decade, mutations affecting liability to human disease have been discovered at a phenomenal rate, and that rate is increasing. For the most part, however, those diseases have a relatively simple genetic basis. For diseases with a complex genetic and environmental basis, new approaches are needed to pave the way for more rapid discovery of genes affecting liability. One such appr...

In actuarial hteramre, researchers suggested various statistical procedures to estimate the parameters in claim count or frequency model. In particular, the Poisson regression model, which is also known as the Generahzed Linear Model (GLM) with Poisson error structure, has been x~adely used in the recent years. However, it is also recognized that the count or frequency data m insurance practice...