Results 41 to 50 of about 4,806,885 (346)
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 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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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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Likelihood ratio tests for fixed model terms using residual maximum likelihood [PDF]
, 1997 Likelihood ratio tests for fixed model terms are proposed for the analysis of linear mixed models when using residual maximum likelihood estimation. Bartlett-type adjustments, using an approximate decomposition of the data, are developed for the test ...
Welham, S. J., Thompson, R.
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The Density of the Maximum Likelihood Estimator
Econometrica, 1999 In this paper we derive an expression for the exact density of the maximum likelihood estimator (MLE) in the case where the MLE is uniquely defined at each point in the sample space by the vanishing of the score vector.
Hillier, G, Armstrong, M
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A new maximum-likelihood method for template fits
European Physical Journal C: Particles and Fields, 2022 A common statistical problem in particle physics is to extract the number of samples which originate from a statistical process in an ensemble containing a mix of several contributing processes. The probability density function of each process is usually
Hans Dembinski, Ahmed Abdelmotteleb
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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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Privacy-preserving Maximum Likelihood Estimation for Distributed Data
The Journal of Privacy and Confidentiality, 2010 Recent technological advances enable the collection of huge amounts of data. Commonly, these data are generated, stored, and owned by multiple entities that are unwilling to cede control of their data. This distributed environment requires statistical
Xiaodong Lin, Alan F. Karr
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Maximum Likelihood and the Single Receptor [PDF]
Physical Review Letters, 2009 Biological cells are able to accurately sense chemicals with receptors at their surfaces, allowing cells to move towards sources of attractant and away from sources of repellent. The accuracy of sensing chemical concentration is ultimately limited by the random arrival of particles at the receptors by diffusion.
Endres, RG, Wingreen, NS
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Parameter uncertainties in weighted unbinned maximum likelihood fits
European Physical Journal C: Particles and Fields, 2022 Parameter estimation via unbinned maximum likelihood fits is central for many analyses performed in high energy physics. Unbinned maximum likelihood fits using event weights, for example to statistically subtract background contributions via the sPlot ...
Christoph Langenbruch
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