Results 11 to 20 of about 125,648 (258)
Bayesian Estimation of Turbulent Motion [PDF]
Based on physical laws describing the multiscale structure of turbulent flows, this paper proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales.
Patrick Héas +4 more
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Generalized power Akshaya distribution is a brand-new two-parameter distribution that builds on the Akshaya distribution first introduced by \cite{Ramadan}. The lifetime data is intended to be modelled by this distribution.
Ahlam Hamdy, Ehab M. Almetwally
doaj +1 more source
Bayesian Estimation With Distance Bounds [PDF]
We consider the problem of estimating a random state vector when there is information about the maximum distances between its subvectors. The estimation problem is posed in a Bayesian framework in which the minimum mean square error (MMSE) estimate of the state is given by the conditional mean.
Dave Zachariah +3 more
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Studies on the going-on COVID-19 pandemic face small sample issues. In this context, Bayesian estimation is considered a viable alternative to frequentist estimation.
Nguyen Ngoc Thach
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Accelerated Life Test Method for the Doubly Truncated Burr Type XII Distribution
The Burr type XII (BurrXII) distribution is very flexible for modeling and has earned much attention in the past few decades. In this study, the maximum likelihood estimation method and two Bayesian estimation procedures are investigated based on ...
Hua Xin +3 more
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The most recent consensus guidelines for dosing and monitoring vancomycin recommended the use of area‐under‐the‐curve with Bayesian estimation for therapeutic monitoring.
Ashley Chen +3 more
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Iterative Bayesian Estimation of Travel Times on Urban Arterials: Fusing Loop Detector and Probe Vehicle Data. [PDF]
On urban arterials, travel time estimation is challenging especially from various data sources. Typically, fusing loop detector data and probe vehicle data to estimate travel time is a troublesome issue while considering the data issue of uncertain ...
Kai Liu +3 more
doaj +1 more source
Bayesian nonparametric subspace estimation [PDF]
Principal component analysis is a widely used technique to perform dimension reduction. However, selecting a finite number of significant components is essential and remains a crucial issue. Only few attempts have proposed a probabilistic approach to adaptively select this number. This paper introduces a Bayesian nonparametric model to jointly estimate
Elvira, Clément +2 more
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Enhanced off-grid DOA estimation by corrected power Bayesian inference using difference coarray
Sparse Bayesian inference for on-grid direction-of-arrival (DOA) estimation using difference coarray was investigated in the authors’ previous work to estimate more signal sources than the number of physical antenna elements. Sparse Bayesian inference is
Yanan Ma, Xianbin Cao, Xiangrong Wang
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This paper investigates the estimation of an unknown shape parameter of the generalized Rayleigh distribution using Bayesian and expected Bayesian estimation techniques based on type-II censoring data.
E. M. Eldemery +3 more
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