Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

Despite the increasing popularity of Bayesian inference in empirical research, few practical
guidelines provide detailed recommendations for how to apply Bayesian procedures and …

Species distribution modeling (SDM) is widely used in ecology and conservation. Currently,
the most available data for SDM are species presence‐only records (available through …

Vorasidenib and ivosidenib inhibit mutant forms of isocitrate dehydrogenase (mIDH) and
have shown preliminary clinical activity against m IDH glioma. We evaluated both agents in …

We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA
concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan …

Background There is growing evidence of vaccine delays or refusals due to a lack of trust in
the importance, safety, or effectiveness of vaccines, alongside persisting access issues …

Abstract Markov chain Monte Carlo is a key computational tool in Bayesian statistics, but it
can be challenging to monitor the convergence of an iterative stochastic algorithm. In this …

The acute decline in global biodiversity includes not only the loss of rare species, but also
the rapid collapse of common species across many different taxa. The loss of pollinating …

Background Global child mortality reduced substantially during the Millennium Development
Goal period (2000–15). We aimed to estimate morbidity, mortality, and prevalence of risk …

Human activity and related land use change are the primary cause of accelerated soil
erosion, which has substantial implications for nutrient and carbon cycling, land productivity …