Results 11 to 20 of about 83,569 (221)

Forecasting Spatio-Temporal Dynamics on the Land Surface Using Earth Observation Data—A Review

Remote Sensing, 2020
Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods.
Jonas Koehler, Claudia Kuenzer
doaj   +1 more source

On the use of whole-genome sequence data for across-breed genomic prediction and fine-scale mapping of QTL

Genetics Selection Evolution, 2021
Background Whole-genome sequence (WGS) data are increasingly available on large numbers of individuals in animal and plant breeding and in human genetics through second-generation resequencing technologies, 1000 genomes projects, and large-scale genotype
Theo Meuwissen, Irene van den Berg, Mike Goddard   +2 more
doaj   +1 more source

Efficient computation of passage time densities and distributions in Markov chains using Laguerre method

Electronics Letters, 2008
The Laguerre method for the numerical inversion of Laplace transforms is a well known approach to the approximation of probability density functions (PDFs) and cumulative distribution functions (CDFs) of first passage times in Markov chains. Results are presented that relate the Laguerre generating functions and Laguerre coefficients of a PDF with ...
H. Kulatunga, W.J. Knottenbelt
openaire   +1 more source

Parallel Metropolis chains with cooperative adaptation [PDF]

, 2015
Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) algorithms, have become very popular in signal processing over the last years. In this work, we introduce a novel MCMC scheme where parallel MCMC chains interact, adapting cooperatively the ...
Elvira, V., Louzada, F., Luengo, D., Martino, L.   +3 more
core   +2 more sources

XRate: a fast prototyping, training and annotation tool for phylo-grammars

BMC Bioinformatics, 2006
Background Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars.
Kosiol Carolin, Chao Sharon, Bradley Robert K, Bendaña Yuri R, Uzilov Andrew V, Klosterman Peter S, Goldman Nick, Holmes Ian   +7 more
doaj   +1 more source

Diffusion approximation-based simulation of stochastic ion channels: which method to use?

Frontiers in Computational Neuroscience, 2014
To study the effects of stochastic ion channel fluctuations on neural dynamics, several numerical implementation methods have been proposed. Gillespie’s method for Markov Chains (MC) simulation is highly accurate, yet it becomes computationally intensive
Danilo ePezo, Daniel eSoudry, Patricio eOrio, Patricio eOrio   +3 more
doaj   +1 more source

Inference of Markovian Properties of Molecular Sequences from NGS Data and Applications to Comparative Genomics [PDF]

, 2015
Next Generation Sequencing (NGS) technologies generate large amounts of short read data for many different organisms. The fact that NGS reads are generally short makes it challenging to assemble the reads and reconstruct the original genome sequence. For
Cannon, Charles H., Deng, Minghua, Reinert, Gesine, Ren, Jie, Song, Kai, Sun, Fengzhu   +5 more
core   +1 more source

Comparison of Analysis Methods for the Joint Connection-Level and Packet-Level Performance Evaluation of VoIP Traffic Networks

IEEE Access
In this paper, the performance of different mathematical models for the joint connection-level and packet-level numerical evaluation of systems with Voice over Internet Protocol (VoIP) traffic are studied and compared.
Mario A. Ramirez-Reyna, Felipe A. Cruz-Perez, Sandra Lirio Castellanos-Lopez, Genaro Hernandez-Valdez   +3 more
doaj   +1 more source

A remarkably simple and accurate method for computing the Bayes Factor from a Markov chain Monte Carlo Simulation of the Posterior Distribution in high dimension

, 2013
Weinberg (2012) described a constructive algorithm for computing the marginal likelihood, Z, from a Markov chain simulation of the posterior distribution. Its key point is: the choice of an integration subdomain that eliminates subvolumes with poor sampling owing to low tail-values of posterior probability.
Weinberg, Martin D., Yoon, Ilsang, Katz, Neal S.   +2 more
openaire   +2 more sources

An introduction to computational complexity in Markov Chain Monte Carlo methods

, 2020
The aim of this work, is to give an introduction to the theoretical background and computational complexity of Markov chain Monte Carlo methods. Most of the mathematical results related to the convergence are not found in most of the statistical references, and computational complexity is still open question for most of the MCMC methods.
openaire   +2 more sources