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On the uniqueness of the maximum likelihood estimator
Economics Letters, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Orme, Chris D., Ruud, Paul A.
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Linear maximum likelihood estimator
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, 1991A 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, 1984AbstractMaximum‐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. +1 more
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Maximum Likelihood Estimators on Manifolds
2017Maximum likelihood estimator (MLE) is a well known estimator in statistics. The popularity of this estimator stems from its asymptotic and universal properties. While asymptotic properties of MLEs on Euclidean spaces attracted a lot of interest, their studies on manifolds are still insufficient.
Hatem Hajri +2 more
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Moment Estimators and Maximum Likelihood
Biometrika, 1958where 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, 1997Summary: 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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Maximum-likelihood estimation of the entropy of an attractor
Physical Review E, 1994In this paper, a maximum-likelihood estimate of the (Kolmogorov) entropy of an attractor is proposed that can be obtained directly from a time series. Also, the relative standard deviation of the entropy estimate is derived; it is dependent on the entropy and on the number of samples used in the estimation.
Schouten, J.C. (author) +2 more
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A Note on a Maximum-Likelihood Estimate
Econometrica, 1947An 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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Maximum Likelihood Estimation and Mathematica
Applied Statistics, 1995Data and outline Mathematica code are given for several examples of maximum likelihood estimation. A common approach is taken to both elementary complete data problems and more computationally demanding incomplete data problems. In teaching, this common approach brings many conceptually simple but computationally heavy problems within reach of the ...
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On maximum likelihood estimation of a Pareto mixture
Computational Statistics, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bee, Marco +2 more
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