Results 91 to 100 of about 168,901 (276)
Pooling information across sites and years to estimate bat fatalities at wind farms
We compared complete pooling (CP), no pooling (NP), and partial pooling (PP) approaches for estimating detection probabilities and hence bat fatalities at wind farms. Partial pooling integrates information across sites and years, improving precision with sparse data while preserving site‐level variation.
Natalia Berberian, Philip M. Dixon
wiley +1 more source
Spatial and temporal variation in survival of female wild turkeys
We monitored 370 female wild turkeys across North Carolina's 3 ecoregions from 2020‐2022 to understand factors influencing their survival. Female survival varied by ecoregion and behavior state, with the incubation period having the lowest survival rates. None of the land cover variables affected survival.
David J. Moscicki +5 more
wiley +1 more source
Phenotypic Subtypes of Obstructive Eustachian Tube Dysfunction as Defined by Cluster Analysis
Obstructive ETD encompasses five clinically distinct phenotypes, ranging from mild, post‐upper respiratory infection presentations to chronic, bilateral disease driven by sinusitis and reflux. These were identified through hierarchical cluster analysis of 490 patients using seven key clinical variables.
Jenilkumar H. Patel +4 more
wiley +1 more source
We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Delayed-acceptance Markov chain Monte Carlo (DA-MCMC) samples from a probability distribution via a two-stages version of the Metropolis-Hastings algorithm, by combining the target distribution with a "surrogate" (i.e.
Boomsma, Wouter +4 more
core
Markov chain Monte Carlo (MCMC) is a sampling-based method for estimating features of probability distributions. MCMC methods produce a serially correlated, yet representative, sample from the desired distribution. As such it can be difficult to know when the MCMC method is producing reliable results.
Vats, Dootika +3 more
openaire +2 more sources
The Irano‐Turanian Floristic Region harbors a rich flora, but our understanding of the development of this diversity is limited by a lack of data on phylogenetic relationships and biogeographic patterns of endemic and more widespread plants. Hypotheses of in situ diversification versus allopatric diversification were tested using Iris subgen. Scorpiris,
Mona Salimbahrami +4 more
wiley +1 more source
Amanita theophili sp. nov. (Amanitaceae) from central Mexico
Amanita theophili sp. nov., a member of Amanita sect. Amidella (Amanitaceae), is described from temperate pine‐oak forests in Morelos, central Mexico. Morphological features and phylogenetic analyses based on ITS and 28S rDNA sequences confirm its distinct taxonomic status. The new species is morphologically similar to A. peckiana and A.
Evangelina Pérez‐Silva +1 more
wiley +1 more source
Environmental influence on intraspecific trait variation in the tropical seagrass Halodule uninervis
Intraspecific trait variation (ITV) enhances the precision of applying functional trait approaches in plant ecology. Despite its benefits, ITV is rarely considered in functional trait‐based seagrass research. The goal of our research is to measure ITV in the tropical seagrass species Halodule uninervis and assess the environmental factors associated ...
Chieh Lin +5 more
wiley +1 more source
Markov Chain Monte Carlo (MCMC) algorithms are a workhorse of probabilistic modeling and inference, but are difficult to debug, and are prone to silent failure if implemented naively. We outline several strategies for testing the correctness of MCMC algorithms.
Grosse, Roger B., Duvenaud, David K.
openaire +2 more sources

