Results 1 to 10 of about 13,575 (293)

On the Asymptotic Relative Efficiency of Planned Missingness Designs

Psychometrika, 2016
In planned missingness (PM) designs, certain data are set a priori to be missing. PM designs can increase validity and reduce cost; however, little is known about the loss of efficiency that accompanies these designs. The present paper compares PM designs to reduced sample (RN) designs that have the same total number of data points concentrated in ...
Rhemtulla, M., Savalei, V., Little, T.D.
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Asymptotic Relative Efficiency

, 1981
In any given inference situation, many statistical procedures may be available, both parametric and nonparametric. Some measure of their relative merits is needed, especially as regards their performance or operating characteristics. For instance, a comparison of the power functions of various tests of the same (or essentially the same) hypotheses ...
John W. Pratt, Jean D. Gibbons
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Asymptotic relative efficiency of multivariate m-estimators

Communications in Statistics - Simulation and Computation, 1985
Asymptotic Relative Efficiencies (ARE) of the robust coordinatewise M-estimators with respect to the robust Maronna-type M-estimators proposed by Singer and Sen (1985) are computed under different elliptically symmetric error distributions. ARE of robust coordinatewise M-estimators with respect to Normal Maximum Likelihood (NML) estimators are also ...
Julio M. Singer, Pranab K. Sen
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On the asymptotic relative efficiency of the MUSIC algorithm

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003
The authors provide an analytic performance evaluation of the errors of the direction-of-arrival estimates obtained by the MUSIC algorithm for uncorrelated sources. Explicit asymptotic formulas are given for the covariances of the estimates. The covariances are then compared to the Cramer-Rao lower bound.
Boaz Porat, Benjamin Friedlander
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On the asymptotic relative efficiency of distributed detection schemes

Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, 1995
The 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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Distance measures and asymptotic relative efficiency

IEEE Transactions on Information Theory, 1970
Summary: 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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Relative efficiency with equivalence classes of asymptotic covariances

Journal of Econometrics, 1999
zbMATH 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, 1988
An 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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On the Asymptotic Relative Efficiency of the Mantel‐Haenszel Test

Biometrical Journal, 1987
AbstractThe 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, 1981
SUMMARY 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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