Results 91 to 100 of about 44,986 (305)

Analysis of the effect of inputs uncertainty on riverine water temperature predictions with a Markov chain Monte Carlo (MCMC) algorithm

Environmental Monitoring and Assessment, 2020
Water temperature is a key characteristic defining chemical, physical, and biologic conditions in riverine systems. Models of riverine water quality require many inputs, which are commonly beset by uncertainty. This study presents an uncertainty analysis of inputs to the stream-temperature simulation model HFLUX.
Abdi, Babak, Bozorg-Haddad, Omid, Loáiciga, Hugo A   +2 more
openaire   +4 more sources

Both density‐ and frequency‐dependent effects determine plant growth in a dune heath ecosystem

Oikos, EarlyView.
We tested the hypothesis that both density‐ and frequency‐dependent interactions play important roles in determining plant growth in a dune heath ecosystem at several levels of available nitrogen. Plant growth was measured using the pin‐point method in a five‐block experiment with four nitrogen levels.
Christian Damgaard, Mathias Emil Kaae, Jacob Weiner, Jesper Leth Bak   +3 more
wiley   +1 more source

Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models [PDF]

Hamiltonian Monte Carlo (HMC) is a recent statistical procedure to sample from complex distributions. Distant proposal draws are taken in a equence of steps following the Hamiltonian dynamics of the underlying parameter space, often yielding superior ...
John Maheu, Martin Burda
core   +2 more sources

Parallel hierarchical sampling:a general-purpose class of multiple-chains MCMC algorithms [PDF]

This paper introduces the Parallel Hierarchical Sampler (PHS), a class of Markov chain Monte Carlo algorithms using several interacting chains having the same target distribution but different mixing properties.
Antonietta Mira, Fabio Rigat
core  

Waves of range dynamics and gene flow characterize the biogeographic history of Litsea elongata, a dominant tree in East Asian evergreen broadleaved forests

PLANTS, PEOPLE, PLANET, EarlyView.
Evergreen broadleaved forests (EBLFs) represent an iconic vegetation type in subtropical montane East Asia, but they are experiencing intensifying anthropogenic pressure and increasing habitat fragmentation. Here, using a dominant and widespread tree species characteristic of East Asian EBLFs, we examine its phylogeographic history and evaluate what it
Sheng‐Yuan Qin, Richard H. Ree, Zheng‐Yu Zuo, Chih‐Chieh Yu, Shuang‐Xiu Xu, Jun Rong, Peng‐Fei Ma, De‐Zhu Li   +7 more
wiley   +1 more source

Uso de WinBUGS en los métodos bayesianos. Una aplicación en auditoría

Rect@, 2001
Lo que se presenta es un breve recorrido por el programa WinBUGS, desarrollado para problemas de inferencia estadística bayesiana haciendo uso de métodos Markov Chain Monte Carlo, MCMC.
Vázquez Polo, Francisco José, Martel Escobar, María   +1 more
doaj  

Aerosol model selection and uncertainty modelling by adaptive MCMC technique [PDF]

Atmospheric Chemistry and Physics, 2008
We present a new technique for model selection problem in atmospheric remote sensing. The technique is based on Monte Carlo sampling and it allows model selection, calculation of model posterior probabilities and model averaging in Bayesian way.
M. Laine, J. Tamminen
doaj  

A Markov Chain Monte Carlo (MCMC) Multivariate Analysis of the Association of Vital Parameter Variation With the Lunar Cycle in Patients Hospitalized With COVID-19. [PDF]

Cureus, 2023
Koya S, Ponnam S, Salenius S, Pamidighantam S.   +3 more
europepmc   +1 more source

First genome sequence of a European Alternaria brassicae isolate and genes involved in early development of alternaria leaf spot on Brassica juncea

Pest Management Science, EarlyView.
This article reports the first genome sequence of a UK Alternaria brassicae isolate. Dual RNA‐sequencing profiling of A. brassicae‐infected Brassica juncea leaves identified differentially expressed genes involved in pathogenicity and host response pathways in moderately resistant Sej‐2 (2) and moderately susceptible Pusa Jaikisan cultivars.
Kevin M. King, Graham McLaughlin, Chinthani S. Karandeni Dewage, Zedi Gao, David J. Hughes, Jonathan S. West, Henrik U. Stotz   +6 more
wiley   +1 more source

Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC [PDF]

We provide Markov chain Monte Carlo (MCMC) algorithms for computing the bandwidth matrix for multivariate kernel density estimation. Our approach is based on treating the elements of the bandwidth matrix as parameters to be estimated, which we do by ...
Rob J. Hyndman, Maxwell L. King, Xibin Zhang   +2 more
core   +2 more sources