Results 271 to 280 of about 524,430 (317)
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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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The Estimation of Many Parameters
Journal of the Royal Statistical Society, 1942Not ...
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UTRAN traffic parameters estimation
2003 International Symposium on VLSI Technology, Systems and Applications. Proceedings of Technical Papers. (IEEE Cat. No.03TH8672), 2004The paper characterizes the statistical distribution of the interarrival packet time of UTRAN traffic at the SAP level of the MAC layer. We analyze a simulated traffic trace of UMTS networks to characterize the nature of the aggregated flows. We chose MMPP-2 (Markov modulated Poisson process) to model the packet interarrival time.
Aouad, H., Ibrahim, A., Tohmé, Samir
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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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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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2006
Abstract Parameter estimation is a common data analysis problem. Like Laplace, for example, we may be interested in knowing the mass of Saturn; or, like Millikan, the charge of the electron. In the simplest case, we are only concerned with the value of a single parameter; such elementary examples are the focus of this chapter. They serve
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Abstract Parameter estimation is a common data analysis problem. Like Laplace, for example, we may be interested in knowing the mass of Saturn; or, like Millikan, the charge of the electron. In the simplest case, we are only concerned with the value of a single parameter; such elementary examples are the focus of this chapter. They serve
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Estimating the Loss of Estimators of a Binomial Parameter
Biometrika, 1988A loss function is introduced, which combines the estimation error of a statistical procedure with a measure of its accuracy. The properties of this loss function are illustrated by the estimator of a binomial parameter. The choice of a conjugate prior distribution is discussed from this point of view.
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Estimation of HIV/AIDS parameters
Automatica, 2002The author proposes an estimation procedure for parameters of the simplest three-dimensional model of HIV/AIDS dynamics. The model takes into account the dynamics of uninfected and infected CD4+T cells and the evolution of the concentration of free virions.
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XV.—On the Estimation of Statistical Parameters
Proceedings of the Royal Society of Edinburgh. Section A. Mathematical and Physical Sciences, 1942SummaryIn the problem of estimating from sample the value of a parameter in a probability function new postulates are suggested of unbiased linear estimate and minimum sampling variance. A comparison is made, with illustrative examples, between this method and the principle of maximum likelihood, and ground common to the two is traversed.
Aitken, A. C., Silverstone, H.
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