Results 261 to 270 of about 376,196 (334)

Modified maximum likelihood estimator

2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016
In this paper, we present a modified maximum likelihood estimation method, which is suitable to be used with φ-families rather than exponential families. An indicative result of the efficacy of this method is established. We perform numerical experiments to illustrate the accuracy of this method for estimating the dispersion parameter σ in φ-Gaussians.
David C. de Souza, Charles Casimiro Cavalcante, Rui Facundo Vigelis   +2 more
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On the uniqueness of the maximum likelihood estimator

Economics Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Orme, Chris D., Ruud, Paul A.
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Maximum Likelihood Estimation

Handbook of Regional Science, 2004
This chapter recalls the basics of the estimation method consisting in maximizing the likelihood associated to the observations. The resulting estimators enjoy convenient theoretical properties, being optimal in a wide variety of situations.
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Linear maximum likelihood estimator

[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991
A general linear and quasi-efficient estimator is presented which is an optimal (for a given criterion) approximation of the maximum likelihood estimator (MLE with nonlinear measurement equation) when the measurements are corrupted by a Gaussian noise. This approach consists of choosing a particular state vector which characterizes the signal.
Christian J. Musso, Claude Jauffret
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The interpretation of maximum‐likelihood estimation

Canadian Journal of Statistics, 1984
AbstractMaximum‐likelihood estimation is interpreted as a procedure for generating approximate pivotal quantities, that is, functions u(X;θ) of the data X and parameter θ that have distributions not involving θ. Further, these pivotals should be efficient in the sense of reproducing approximately the likelihood function of θ based on X, and they should
Sprott, David A., Viveros-Aguilera, Román   +1 more
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Small-Sample Properties of Nonlinear Least Squares and Maximum Likelihood Estimators in the Context of Autocorrelated Errors

Journal of the American Statistical Association, 1979
J. Spitzer
exaly   +4 more sources

Asymptotic Properties of Maximum Likelihood Estimators Based on Conditional Specification

Annals of Statistics, 1979
P. Sen
exaly   +2 more sources

Moment Estimators and Maximum Likelihood

Biometrika, 1958
where J'q2(x) P(x; 0) dx = Or, J'q(x) qq(x) P(x; 0) dx = 0 (r+ s). (2) To avoid undue complication at this stage we assume P(x; 0) is continuous throughout its range. We reconsider the restrictions on P in a subsequent section.
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A Semiparametric Maximum Likelihood Estimator

Econometrica, 1997
Summary: This paper presents a procedure for analyzing a model in which the parameter vector has two parts: a finite-dimensional component \(\theta\) and a nonparametric component \(\lambda\). The procedure does not require parametric modeling of \(\lambda\) but assumes that the true density of the data satisfies an index restriction.
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A Note on a Maximum-Likelihood Estimate

Econometrica, 1947
An estimate of y obtained by applying the method of maximum likelihood under the assumption that ut is normally distributed is consistent and asymptotically normally distributed. The asymptotic standard deviation is given in this note. Although Kendall considers many estimates of the period in his publication, he does not use the maximum-likelihood ...
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