Results 111 to 120 of about 409,081 (168)
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2013 European Control Conference (ECC), 2013
The paper proposes a sampled data based estimation methodology to reconstruct local incident parameter of the macroscopic Incident Traffic Flow (ITF) models. The key idea in ITF models is to dynamically relax the traffic mean speed to the traffic equilibrium one based of an time and space varying incident term. First, the analysis of incident corrupted
Azita Dabiri, Balázs Kulcsár
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The paper proposes a sampled data based estimation methodology to reconstruct local incident parameter of the macroscopic Incident Traffic Flow (ITF) models. The key idea in ITF models is to dynamically relax the traffic mean speed to the traffic equilibrium one based of an time and space varying incident term. First, the analysis of incident corrupted
Azita Dabiri, Balázs Kulcsár
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Robustness in parameter estimation
IEEE Transactions on Information Theory, 1977A constructive approach to robust parameter estimation that carries over naturally to the nonparametric estimation is presented. Vagueness in previous notions of "robustness" has prevented such a connection from being made. To eliminate vagueness, robustness is defined in a precise mathematical way that leads to isolation of constructive analytical ...
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Identifiability and Parameter Estimation
Journal of Parenteral and Enteral Nutrition, 1991In experiments on biological systems one often cannot measure all state variables (compartments). Given a particular experiment of that type, a basic kinetic parameter may have no effect on the observations; such a parameter is an insensible parameter for that experiment. A parameter may influence the observations and not be uniquely determinable; such
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On the estimation of the general parameter
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Matthew Stearns, Sarjinder Singh
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The Estimation of Many Parameters
Journal of the Royal Statistical Society, 1942Not ...
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Parameter estimation: local identifiability of parameters
American Journal of Physiology-Endocrinology and Metabolism, 1990For biological systems one often cannot set up experiments to measure all of the state variables. If only a subset of the state variables can be measured, it is possible that some of the system parameters cannot influence the measured state variables or that they do so in combinations that do not define the parameters' effects separately.
J A, Jacquez, T, Perry
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1995
The Introduction of this chapter sketches the problem of the estimation of item parameters and the notation in the ease of incomplete data. Then the joint, conditional, and marginal maximum likelihood methods are discussed. A final section briefly mentions a few other methods not based on likelihoods.
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The Introduction of this chapter sketches the problem of the estimation of item parameters and the notation in the ease of incomplete data. Then the joint, conditional, and marginal maximum likelihood methods are discussed. A final section briefly mentions a few other methods not based on likelihoods.
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A minimum discrepancy estimator in parameter estimation
IEEE Transactions on Information Theory, 1998Summary: In statistical estimation theory, a satisfactory estimator should be able to embody a large portion of the available information, which may be known a priori or provided by the data. Hence, the loss of information is minimum when this estimator is employed.
Shyang Chang +2 more
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Covariance Matrices for Parameter Estimates of Constrained Parameter Estimation Problems
SIAM Journal on Matrix Analysis and Applications, 2007In this paper we show how, based on the conjugate gradient method, to compute the covariance matrix of parameter estimates and confidence intervals for constrained parameter estimation problems as well as their derivatives.
Hans Georg Bock +2 more
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Geophysical Parameter Estimation
The Journal of the Acoustical Society of America, 2008Seismic exploration for oil and gas is a parameter estimation problem. Geological properties and fluid content of subsurface reservoirs are sensed from the earth's surface. Seismic data are acquired by generating elastic waves at the surface and recording the reflections off subsurface targets using large receiver arrays.
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