Results 81 to 90 of about 44,758 (308)
GARPOS-MCMC: MCMC-based analysis tool for GNSS-Acoustic seafloor positioning
<p>"GARPOS-MCMC" (GNSS-Acoustic Ranging combined POsitioning Solver with Markov-Chain Monte Carlo) is an analysis tool for GNSS-Acoustic seafloor positioning based on MCMC method.</p> <p>Please see README file or visit <a href ...
Watanabe, Shun-ichi +3 more
core +1 more source
Markov-chain Monte Carlo method enhanced by a quantum alternating operator ansatz
Physical Review ResearchQuantum computation is expected to accelerate certain computational tasks over classical counterparts. Its most primitive advantage is its ability to sample from classically intractable probability distributions.
Yuichiro Nakano +3 more
doaj +1 more source
The Journal of Wildlife Management, EarlyView.We used 4 sampling methods to estimate or index the abundance and sex ratio of spotted salamanders (Ambystoma maculatum) over 14 years. The present study highlights the importance of considering individual heterogeneity in capture probability when estimating abundance of pond‐breeding amphibians from capture data with imperfect detection. Abstract Long‐
Patrick D. Moldowan +3 more
wiley +1 more source
Phenotypic Subtypes of Obstructive Eustachian Tube Dysfunction as Defined by Cluster Analysis
The Laryngoscope, EarlyView.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
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 +2 more
core
Estimation of Hyperbolic Diffusion Using MCMC Method
, 2002 In this paper we propose a Bayesian method for estimating hyperbolic diffusion models. The approach is based on the Markov Chain Monte Carlo (MCMC) method after discretization via the Milstein scheme.
Tse, Y.K. +4 more
core +1 more source
Correlation‐guided multi‐object tracking with correlation feature transfer
IET Computer Vision, 2019 Here, the authors propose a correlation‐guided Monte Carlo Markov chain (MCMC) solver to promote the efficiency for tracking multiple objects under recursive Bayesian filtering framework.
Jiatong Li, Yanjie Zhao, Zhiguo Jiang
doaj +1 more source
Movement Disorders, EarlyView.Abstract Background The identification of Parkinson's disease (PD) subtypes is crucial for predicting the disease course and designing personalized therapeutic strategies. Objectives The aim of the study was to characterize the heterogeneity of the spatiotemporal evolutionary patterns of striatal dopamine depletion and cerebral hypoperfusion in PD ...
Yeeun Sun +9 more
wiley +1 more source
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
Mathematical Methods in the Applied Sciences, EarlyView.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