Results 261 to 270 of about 605,028 (307)

Minimum Variance Approximate Formulas

SIAM Journal on Numerical Analysis, 1976
We discuss the construction of minimum variance approximate formulas for a given linear functional. We first describe an elementary method for obtaining the minimum variance weights; for the purpose, we set up two systems having the advantage that the order of the matrix to be inverted will not exceed half the number of abscissas in the formula.
Chawla, M. M., Ramakrishnan, T. R.
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Minimum Variance Portfolio Composition

SSRN Electronic Journal, 2010
Empirical studies document that equity portfolios constructed to have the lowest possible risk have surprisingly high average returns. Clarke, de Silva, andThorley derive an analytic solution for the long-only minimum-variance portfolio under the assumption of a single-factor covariance matrix. The equation for optimal security weights has a simple and
Roger Clarke, Harindra de Silva, Steven Thorley   +2 more
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Minimum Variance Huffman Codes

SIAM Journal on Computing, 1982
Huffman’s well-known coding method constructs a minimum redundancy code which minimizes the expected value of the word length. In this paper, we characterize the minimum redundancy code with the minimum variance of the word length. An algorithm is given to construct such a code. It is shown that the code is in a certain sense unique.
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Fast minimum variance deconvolution

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
We propose a statistical estimation approach to the deconvolution problem which is optimal in the minimum variance sense when the a priori knowledge on the signal to be restored is strictly limited to its first two moments. By viewing the estimation problem as a degenerate case of a Kalman filter applied to a static system with time-varying ...
Guy Demoment, Roger Reynaud
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Minimum variance centroid thresholding

Optics Letters, 2002
Image-processing thresholding algorithms are extended segmentation tools that are suitable for tracking applications. The centroid of the tracked image distribution is a good point of reference for the location of the image. We describe a new thresholding technique that is based on the estimation of the optimum threshold for achieving minimal variance ...
J, Arines, J, Ares
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Minimum variance stratification

Communications in Statistics - Simulation and Computation, 1995
The equations for the solution of minimum variance stratification under Neyman allocation are not easily tractable and hence approximate solutions have been suggested by various workers. These approximate solutions are in general not satisfactory as they do not achieve global minimum variance.
V.K.G. Unnithan, N. Unnikrishnan Nair
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Minimum Variance Immunization

SSRN Electronic Journal, 2020
This paper analyzes immunization strategies in the mean-variance framework. We characterize the efficient portfolio allocations and identify the minimum variance immunization strategy. We show that the efficient allocations can be superior or inferior to the minimum variance allocation as time passes.
Pascal Francois, Franck Moraux
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Minimum variance capacity identification

European Journal of Operational Research, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Minimum Variance Stratification

Journal of the American Statistical Association, 1959
Abstract When estimating the mean value of a quantity x, in a population to be divided into L strata according to the value of a quantity closely correlated with x, it is necessary to choose the L — 1 points of stratification. Nearly optimum points are obtained if they are chosen to equalize the integrals over the various strata of the square root of ...
Tore Dalenius, Joseph L. Hodges
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Intersample variances in discrete minimum variance control

IEEE Transactions on Automatic Control, 1984
Summary: This note investigates the continuous-time response resulting from digital control of stochastic systems. A method is presented for computing the time-varying covariance between sampling instants. The results are used to examine the performance of the well-known minimum variance control strategy.
de Souza, Carlos E., Goodwin, Graham
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