Results 41 to 50 of about 54,345 (310)
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
MCMC genome rearrangement [PDF]
Bioinformatics, 2003 Abstract Motivation: As more and more genomes have been sequenced, genomic data is rapidly accumulating. Genome-wide mutations are believed more neutral than local mutations such as substitutions, insertions and deletions, therefore phylogenetic investigations based on inversions, transpositions and inverted transpositions are less ...
openaire +2 more sources
Augmentation schemes for particle MCMC [PDF]
Statistics and Computing, 2015 Particle MCMC involves using a particle filter within an MCMC algorithm. For inference of a model which involves an unobserved stochastic process, the standard implementation uses the particle filter to propose new values for the stochastic process, and MCMC moves to propose new values for the parameters.
Paul Fearnhead, Loukia Meligkotsidou
openaire +4 more sources
A Classical and Bayesian Approach for Parameter Estimation in Structural Equation Models
Journal of New Theory, 2020 Structural Equation Models (SEMs) with latent variables provide a general framework for modelling relationships in multivariate data. Although SEMs are most commonly used in studies involving intrinsically latent variables, such as happiness, quality of ...
Naci Murat, Mehmet Ali Cengiz
doaj
Nuevo Itinerario, 2021 The article that we present here is part of a research / extension process that lasted for more than two years in the Puna and Chaco of Salta, in northern Argentina, with significant interaction with the Kolla de Hurcuro and Wichí de El peoples.
Facundo Gonzalez
doaj +1 more source
Adaptive Metropolis-coupled MCMC for BEAST 2 [PDF]
PeerJ, 2020 With ever more complex models used to study evolutionary patterns, approaches that facilitate efficient inference under such models are needed. Metropolis-coupled Markov chain Monte Carlo (MCMC) has long been used to speed up phylogenetic analyses and to
Nicola F. Müller, Remco R. Bouckaert
doaj +2 more sources
CoRR, 2012 Filtering---estimating the state of a partially observable Markov process from a sequence of observations---is one of the most widely studied problems in control theory, AI, and computational statistics. Exact computation of the posterior distribution is generally intractable for large discrete systems and for nonlinear continuous systems, so a good ...
Bhaskara Marthi +3 more
openaire +3 more sources
Crop Breeding and Applied Biotechnology, 2021 The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation.
Leonardo Lopes Bhering +7 more
doaj
CoRR, 2017 Markov Chain Monte Carlo (MCMC) sampling methods are widely used but often encounter either slow convergence or biased sampling when applied to multimodal high dimensional distributions. In this paper, we present a general framework of improving classical MCMC samplers by employing a global optimization method.
Ricky Fok, Aijun An, Xiaogang Wang 0007
openaire +2 more sources
BarekengThis study compares the Log-linear Realized GARCH (LRG) and its extension with Continuous and Jump components (LRG-CJ) in modeling the volatility of financial assets, using daily data from the Tokyo Stock Price Index (TOPIX) over 2004–2011.
Didit Budi Nugroho +2 more
doaj +1 more source