Results 31 to 40 of about 2,034,768 (362)
On maximum-likelihood decoding with circuit-level errors [PDF]
Quantum, 2020 Error probability distribution associated with a given Clifford measurement circuit is described exactly in terms of the circuit error-equivalence group, or the circuit subsystem code previously introduced by Bacon, Flammia, Harrow, and Shi. This gives a
Leonid P. Pryadko
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New maximum likelihood estimators for eukaryotic intron evolution. [PDF]
PLoS Computational Biology, 2005 The evolution of spliceosomal introns remains poorly understood. Although many approaches have been used to infer intron evolution from the patterns of intron position conservation, the results to date have been contradictory.
Hung D Nguyen +2 more
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The maximum likelihood threshold of a graph [PDF]
Bernoulli, 2018 Added Section 6 and Section ...
Gross, Elizabeth, Sullivant, Seth
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On the inefficiency of the restricted maximum likelihood [PDF]
Statistica Neerlandica, 2015 The restricted maximum likelihood is preferred by many to the full maximum likelihood for estimation with variance component and other random coefficient models, because the variance estimator is unbiased. It is shown that this unbiasedness is accompanied in some balanced designs by an inflation of the mean squared error.
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Maximum likelihood of phylogenetic networks [PDF]
Bioinformatics, 2006 Abstract Motivation: Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for ...
Luay Nakhleh +3 more
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Maximum likelihood localization: When does it fail?
ICT Express, 2016 Maximum likelihood is a criterion often used to derive localization algorithms. In particular, in this paper we focus on a distance-based algorithm for the localization of nodes in static wireless networks. Assuming that Ultra Wide Band (UWB) signals are
Stefania Monica, Gianluigi Ferrari
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Dynamic Indoor Localization Using Maximum Likelihood Particle Filtering
Sensors, 2021 A popular approach for solving the indoor dynamic localization problem based on WiFi measurements consists of using particle filtering. However, a drawback of this approach is that a very large number of particles are needed to achieve accurate results ...
Wenxu Wang, Damián Marelli, Minyue Fu
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Maximum likelihood estimation of the Weibull distribution with reduced bias [PDF]
arXiv, 2022 In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The proposed estimate of the shape parameter is significantly less biased and more efficient than the corresponding maximum likelihood estimate, while being simple to compute ...
arxiv
Distributed Maximum Likelihood Sensor Network Localization [PDF]
, 2013 We propose a class of convex relaxations to solve the sensor network localization problem, based on a maximum likelihood (ML) formulation. This class, as well as the tightness of the relaxations, depends on the noise probability density function (PDF) of
Leus, Geert, Simonetto, Andrea
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The Dual of the Maximum Likelihood Method [PDF]
SSRN Electronic Journal, 2012 The Maximum Likelihood method estimates the parameter values of a statistical model that maximize the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires the formulation of a Lagrange problem.
Paris, Quirino, Paris, Quirino
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