Results 91 to 100 of about 221,738 (314)
Evaluation of fall‐seeded cover crops for grassland nesting waterfowl in eastern South Dakota
Cover crops are experiencing a revival among Midwestern farmers, and we assessed their attractiveness and safety for nesting ducks in South Dakota. Nest success was markedly lower in cover crops than in perennial cover during both years of our study, including 2019 which was a best‐case scenario for cover crops, with extremely wet conditions delaying ...
Charles W. Gallman +3 more
wiley +1 more source
Hastings-Metropolis algorithm on Markov chains for small-probability estimation***
Shielding studies in neutron transport, with Monte Carlo codes, yield challenging problems of small-probability estimation. The particularity of these studies is that the small probability to estimate is formulated in terms of the ...
Bachoc Francois +2 more
doaj +1 more source
Particle Gibbs with Ancestor Sampling
Particle Markov chain Monte Carlo (PMCMC) is a systematic way of combining the two main tools used for Monte Carlo statistical inference: sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC).
Jordan, Michael I. +2 more
core
Markov chain Monte Carlo estimation of quantiles [PDF]
Charles R. Doss +3 more
openalex +1 more source
ABSTRACT Background Lebrikizumab is approved to treat patients with moderate‐to‐severe atopic dermatitis (AD). Objectives This study evaluated the 16‐week efficacy outcomes of lebrikizumab in adults and adolescents with severe AD in ADvocate trials who would be eligible for treatment based on South Korean reimbursement‐like criteria. Methods This was a
Chong Hyun Won +11 more
wiley +1 more source
This study investigates the estimation of the stress-strength reliability measure, $\varsigma = P(X \lt Y)$ , assuming that both stress ( $X$ ) and strength ( $Y$ ) follow the new X-Lindley distribution.
Fatma Ciftci +4 more
doaj +1 more source
Discrete-Time Stochastic Volatility Models and MCMC-Based Statistical Inference [PDF]
In this paper, we review the most common specifications of discrete-time stochas- tic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference.
Nikolaus Hautsch, Yangguoyi Ou
core
On the convergence time of some non-reversible Markov chain Monte Carlo\n methods [PDF]
Marie Vialaret, Florian Maire
openalex +1 more source
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

