Results 281 to 290 of about 45,703 (314)

ASYMPTOTIC CONCENTRATION OF ESTIMATORS AND DISPERSIVITY

Statistics & Risk Modeling, 1986
Any regular estimator-sequence of the parameter of a univariate LAN family is asymptotically more dispersed that a certain normal distribution in the sense that any two quantiles of the estimator- sequence are asymptotically more widely separated than the corresponding quantiles of the normal distribution.
Droste, Wolfgang, Wefelmeyer, Wolfgang
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ASYMPTOTICS OF SPECTRAL DENSITY ESTIMATES

Econometric Theory, 2009
We consider nonparametric estimation of spectral densities of stationary processes, a fundamental problem in spectral analysis of time series. Under natural and easily verifiable conditions, we obtain consistency and asymptotic normality of spectral density estimates.
Liu, Weidong, Wu, Wei Biao
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Asymptotic estimates for the generalized Fourier coefficients

Journal of Computational and Applied Mathematics, 1984
Explicit forms for the orthonormal polynomials with respect to a given weight function on the interval [−1, 1] usually are difficult to construct. In this paper we give asymptotic estimates for the generalized Fourier coefficients of functions expanded ...
Chen, T.H.C.
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Asymptotic Normality of some Estimators

Calcutta Statistical Association Bulletin, 1981
This paper uses martingale central limit theorem and continuous mapping theorem to establish asymptotic normality of log-likelihood ratio process, maximum likelihood estimators and the posterior distributions. Illustrative examples are given.
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ASYMPTOTIC DEFICIENCY OF THE JACKKNIFE ESTIMATOR

Australian Journal of Statistics, 1983
SummaryIn this paper it is shown that the bias‐adjusted maximum likelihood estimator (MLE) is asymptotically equivalent to the jackknife estimator in the variance up to the order n‐1 and the asymptotic deficiency of the jackknife estimator relative to the bias‐adjusted MLE is equal to zero.
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Asymptotic Estimates of Fourier Coefficients

SIAM Journal on Mathematical Analysis, 1974
Complex variable techniques are used to estimate the Fourier coefficients of functions expanded in series of Jacobi, Laguerre and Hermite polynomials.
Elliott, David, Tuan, P. D.
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Asymptotic Efficiency of Inverse Estimators

Theory of Probability & Its Applications, 2000
Summary: Inverse estimation concerns the recovery of an unknown input signal from blurred observations on a known transformation of that signal. The estimators considered in this paper are based on a regularized inverse of the transformation involved, employing a Hilbert space set-up. We focus on properties related to weak convergence. It is shown that
van Rooij, A. C. M., Ruymgaart, F. H., van Zwet, W. R.   +2 more
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Asymptotics ofT-Estimators

Theory of Probability & Its Applications, 1993
See the review in Zbl 0774.62030.
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On the use of asymptotics in detection and estimation

IEEE Transactions on Signal Processing, 1996
We illustrate the importance of a finite dimensionality assumption when using functions of asymptotic statistics. We also note that asymptotic distributions need to converge uniformly to facilitate algebraic manipulations. Finally, we point to subtleties in using detection statistics stemming from the central limit theorem and Taylor series without ...
Lee M. Garth, Yoram Bresler
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On the asymptotic optimality of orthoregressional estimators

Journal of Applied and Industrial Mathematics, 2016
Summary: It is shown that the ortho-regressional (STLS) parameter estimators in linear algebraic systems (including autonomous difference equations with matrix coefficients) converge to the maximum likelihood estimators and thus become asymptotically best in the limit case of large variances of the random coordinates on the variety of solutions to the ...
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