Distance sampling is a technique for estimating the abundance of animals or other objects in a region, allowing for imperfect detection. This paper evaluates the statistical efficiency of the method when its assumptions are met, both theoretically and by simulation. The theoretical component of the paper is a derivation of the asymptotic variance penalty for the distance sampling estimator aris...

Numerous efforts have been devoted to investigating crash occurrence as related to roadway design features, environmental factors and traffic conditions. However, most of the research has relied on univariate count models; that is, traffic crash counts at different levels of severity are estimated separately, which may neglect shared information in unobserved error terms, reduce efficiency in p...

Simple models of molecular evolution assume that sequences evolve by a Poisson process in which nucleotide or amino acid substitutions occur as rare independent events. In these models, the expected ratio of the variance to the mean of substitution counts equals 1, and substitution processes with a ratio greater than 1 are called overdispersed. Comparing the genomes of 10 closely related specie...

Generalized linear models (GLM's) have been routinely used in statistical data analysis. The evolution of these models as well as details regarding model tting, model checking and inference is thoroughly documented in McCullagh and Nelder (1989). However, in many applications, heterogeneity in the observed samples is too large to be explained by the simple variance function which is implicit in...

Next-generation sequencing technologies now constitute a method of choice to measure gene expression. Data to analyze are read counts, commonly modeled using negative binomial distributions. A relevant issue associated with this probabilistic framework is the reliable estimation of the overdispersion parameter, reinforced by the limited number of replicates generally observable for each gene. M...

Within the family of zero-inflated Poisson distributions, the data has Poisson distribution if any only if the mean equals the variance. In this paper we compare two closely related test statistics constructed based on this idea. Our results show that although these two tests are asymptotically equivalent under the null hypothesis and are equally efficient, one test is always more efficient tha...

The neutrality theory predicts that the rate of neutral molecular evolution is constant over time, and thus that there is a molecular clock for timing evolutionary events. It has been observed that the variance of the rate of evolution is generally larger than expected according to the neutrality theory, which has raised the question of how reliable the molecular clock is or, indeed, whether th...

In analyzing complicated data, we are often unwilling or not confident to impose a parametric model for the data-generating structure. One important example is data analysis for proportional or count data with overdispersion. The obvious advantage of assuming full parametric models is that one can resort to likelihood analyses, for instance, to use AIC or BIC to choose the most appropriate regr...

Significance Evidence indicates that superspreading plays a dominant role in COVID-19 transmission, so small fraction of infected people causes large proportion new cases. We developed an agent-based model simulates disease moving through society with networks both repeated contacts and nonrepeated, random contacts. The results indicate is the virus’ Achilles’ heel: Reducing contacts—such as th...

Avocado (Persea americana) farming in East Africa has expanded since recent, contributing significantly toward economic growth and livelihood for small-scale farmers. However, insects attacking avocado fruits reduce fruit quality size, causing massive losses. Previous studies have identified key insect pests, their temporal population patterns how landscape vegetation productivity influe...