Results 251 to 260 of about 6,177,620 (296)
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On the asymptotic relative efficiency of distributed detection schemes
Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 1995The asymptotic relative efficiency (ARE) of two centralized detection schemes has proved useful in large-sample-size and weak-signal performance analysis. In the paper, ARE is applied to some distributed detection cases which use counting (k out of N) fusion rules.
Rick S. Blum, Saleem A. Kassam
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Relative efficiency with equivalence classes of asymptotic covariances
Journal of Econometrics, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David M. Mandy, Carlos Martins-Filho
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Analysis of the asymptotic relative efficiency of the MUSIC algorithm
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988An analytical performance evaluation of the errors of the direction-of-arrival estimates obtained by the MUSIC algorithm for uncorrelated sources is provided. Explicit asymptotic formulas are derived for the means and the covariance of the estimates. The covariances are then compared to the Cramer-Rao lower bound.
Boaz Porat, Benjamin Friedlander
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Distance measures and asymptotic relative efficiency
IEEE Transactions on Information Theory, 1970Summary: The relationship between distance measures and asymptotic relative efficiency is discussed. It is shown that the ratio of the Bhattacharyya distance or J divergences of two test statistics is equivalent to asymptotic relative efficiency. Two input systems are discussed as examples, and the performances of the polarity coincidence correlator ...
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On the Asymptotic Relative Efficiency of the Mantel‐Haenszel Test
Biometrical Journal, 1987AbstractThe Mantel‐Haenszel test is optimal when the odds ratio is constant. This paper investigates the effects of departures from the assumption of a constant odds ratio on the behavior of the Mantel‐Haenzel test. A simple approximation is proposed for the non‐null distribution of the test statistic.
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Asymptotic relative efficiency of survival tests with covariates
Biometrika, 1981SUMMARY Comparison of survival for two groups of patients when adjusting for covariates is a standard problem in clinical trials. In this paper the general life table models developed by Cox (1972) and the stratified log rank test (Mantel & Haenszel, 1959; Peto & Peto, 1972) are compared.
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Asymptotic relative efficiencies of multistage tests (Corresp.)
IEEE Transactions on Information Theory, 1985Asymptotic relative efficiencies of two-stage and multistage tests of a simple null hypothesis Versus a simple location alternative are considered. Observations are taken in groups, not necessarily of the same size, and a test statistic is computed for comparison with thresholds.
S. Tantaratana, H. Poor
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Estimating the asymptotic relative efficiency of weighted rankings
Communications in Statistics - Simulation and Computation, 1983Five tests for the hypothesis of no treatment effects in complete blocks designs are compared with respect to asymptotic relative efficiency: the ordinary two-way analysis of variance, the analysis of variance of ranks (Friedman, 1937), the method of ranking after alignment (Hodges and Lehmann, 1962), and a method of weighted rankings proposed by Quade
Claudio Silva, Dana Quade
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Asymptotic relative efficiencies of r-estimators of location
Communications in Statistics - Theory and Methods, 1983A table of asymptotic relative efficiencies of a large variety of R-estimators is given and some of its uses discussed.The family of distributions used includes both those common in the robustness literature and those that correspondent to various rank tests for location.
David L. Hall, Brian L. Joiner
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Adaptive composite quantile regressions and their asymptotic relative efficiency
Journal of Statistical Computation and Simulation, 2017The composite quantile regression (CQR for short) provides an efficient and robust estimation for regression coefficients. In this paper we introduce two adaptive CQR methods.
Ke Yang, Liping Zhu, Wangli Xu
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