Results 31 to 40 of about 167,396 (260)
Spbsampling: An R Package for Spatially Balanced Sampling
Journal of Statistical Software, 2022 The basic idea underpinning the theory of spatially balanced sampling is that units closer to each other provide less information about a target of inference than units farther apart.
Francesco Pantalone +2 more
doaj +1 more source
MCMC-ODPR : primer design optimization using Markov Chain Monte Carlo sampling [PDF]
, 2012 Background Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly.
Allaby, Robin G. +3 more
core +3 more sources
pexm: A JAGS Module for Applications Involving the Piecewise Exponential Distribution
Journal of Statistical Software, 2021 In this study, we present a new module built for users interested in a programming language similar to BUGS to fit a Bayesian model based on the piecewise exponential (PE) distribution.
Vinícius D. Mayrink +2 more
doaj +1 more source
MCMC and GLMs for estimating regression parameters: Evidence from non-life Egyptian insurance sector [PDF]
Journal of Humanities and Applied Social Sciences, 2019 Purpose – The purpose of this study is to estimate the linear regression parameters using two alternative techniques. First technique is to apply the generalized linear model (GLM) and the second technique is the Markov Chain Monte Carlo (MCMC) method ...
Mahmoud ELsayed, Amr Soliman
doaj +1 more source
Preconditioning Markov Chain Monte Carlo Simulations Using Coarse-Scale Models [PDF]
, 2006 We study the preconditioning of Markov chain Monte Carlo (MCMC) methods using coarse-scale models with applications to subsurface characterization. The purpose of preconditioning is to reduce the fine-scale computational cost and increase the acceptance ...
Efendiev, Y., Hou, T., Luo, W.
core +3 more sources
TI-Stan: Adaptively Annealed Thermodynamic Integration with HMC †
Proceedings, 2019 We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimating ...
R. Wesley Henderson, Paul M. Goggans
doaj +1 more source
An Investigation into Exoplanet Transits and Uncertainties [PDF]
, 2017 A simple transit model is described along with tests of this model against published results for 4 exoplanet systems (Kepler-1, 2, 8, and 77). Data from the Kepler mission are used.
Banks, Timothy +3 more
core +2 more sources
Open Physics, 2017 The coefficient of variation [CV] has several applications in applied statistics. So in this paper, we adopt Bayesian and non-Bayesian approaches for the estimation of CV under type-II censored data from extension exponential distribution [EED].
Bakoban Rana A.
doaj +1 more source
Quantum Speedups for Multiproposal MCMC. [PDF]
Bayesian AnalMultiproposal Markov chain Monte Carlo (MCMC) algorithms choose from multiple proposals to generate their next chain step in order to sample from challenging target distributions more efficiently. However, on classical machines, these algorithms require $\mathcal{O}(P)$ target evaluations for each Markov chain step when choosing from $P$ proposals ...
Lin CY +5 more
europepmc +5 more sources
, 2020 Markov Chain Monte Carlo (MCMC) algorithms ubiquitously employ complex deterministic transformations to generate proposal points that are then filtered by the Metropolis-Hastings-Green (MHG) test. However, the condition of the target measure invariance puts restrictions on the design of these transformations.
Neklyudov, Kirill, Welling, Max
openaire +2 more sources