Maximum Likelihood Estimation
Maximum likelihood estimation of a stochastic frontier model with residual covariance
... In theoretical literature on productivity, the disturbance terms of the stochastic frontier model are assumed to be independent random variables. In this paper, we consider a stochastic production frontier model with ...
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Targeted maximum likelihood estimation for a binary treatment: A tutorial.
... Targeted maximum likelihood estimation respects the limits of the possible range of the targeted parameter, reduces bias through the use of ensemble and machine ‐ learning algorithms, and, finally, ...
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Maximum-Likelihood Estimation of Coalescence Times in Genealogical Trees
... Our method has the advantage of the optimal as- ymptotic properties (as the sequence length increases) of maximum-likelihood estimation and in simulation stud- ies was shown to give slight ...
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On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... forward likelihood expressions (Prakasa Rao, 1999) available for continuously observed diffusion ...efficient maximum likelihood estimation (MLE) can not be readily implemented for most of ...
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Readings in Targeted Maximum Likelihood Estimation
... mum likelihood estimation can be applied, or closely related M-estimate ...conditions. Maximum likelihood estimation in semiparametric models has been an extensive research area of ...
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Maximum likelihood estimation for stochastic Lotka–Volterra model with jumps
... the maximum likelihood estimation for the drift coefficients based on continuous time ...The likelihood function and explicit estimator are derived by using semimartingale ...
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Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation
... for maximum likelihood estimation, and a proposal based on alternate optimization is made to alleviate this ...of maximum likelihood estimators in small samples, and real data is ...
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Cluster Analysis of Temporal Data using Maximum Likelihood Estimation
... Due to rapid growth of technologies, a large amount of data gets generated. The need arises to handle this data for retrieving and analyzing useful information. Clustering of temporal data has been explored using ...
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Maximum Likelihood Estimation of Linkage Disequilibrium in Half-Sib Families
... A half-sib family consisting of 36 calves from commercial beef cattle at the Gund Ranch in Nevada was used to illustrate and to compare alternative methods for estimation of linkage disequilibrium. The first step ...
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Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard
... Suppose the optimal k-means solution is realized by centers µ ∗ = (µ ∗ 1 , . . . , µ ∗ k ). Let π 1 ∗ = · · · = π k ∗ = 1/k and σ ∗2 = Φ(µ ∗ )/nd. To bound the log-likelihood of the mixture model (π ∗ , µ ∗ , σ ∗ ...
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Maximum likelihood estimation of the parameters of a system of simultaneous regression equations
... Because the coefficients of the under-identified equations cannot be esti- mated, and since the coefficients of the just-identified equations are easily recoverable from the red[r] ...
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Maximum-Likelihood Estimation of Admixture Proportions From Genetic Data
... the estimation could be influenced potentially by several come the barrier of isolation and come into contact ...First, estimation errors can come from sampling, due to various causes, such as range ...
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Maximum-Likelihood Estimation of Relatedness
... traditional maximum-likelihood estimator in relation to the ...traditional maximum-likelihood estimator exhibits a lower standard error under essentially all ...the likelihood ...
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Maximum Likelihood Estimation of the Multivariate Normal Mixture Model
... the likelihood may be unbounded in which case the maximum likelihood (ML) estimator does not ...the likelihood equation that is consistent and asymptotically efficient; see McLachlan and ...
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Approximate maximum likelihood estimation for population genetic inference
... approximate maximum likelihood methods have been proposed that estimate the likelihood surface in an ABC like fashion (Creel and Kristensen, 2013; Rubio and Johansen, 2013) or using MCMC (de Valpine, ...
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Computational approaches for maximum likelihood estimation for nonlinearmixed models.
... tion 5 factorial experiment. (Resolution 5 requires that all main eects and rst order interactions to not be aliased with any other main eect or rst order interaction.) An appropriate choice would be to set the options ...
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Maximum Likelihood Estimation of Recombination Rates From Population Data
... We analyzed the three population data sets separately and together; results are shown in Table 2, with esti- Table 1. For all of the values of ⌰ examined, estimation mates of ⌰ using the method of Watterson (1975) ...
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Maximum Likelihood Estimation of Factored Regular Deterministic Stochastic Languages
... the Maximum Likelihood Estimate of D with respect to C can be found efficiently by locally optimizing the parame- ter ...the likelihood function de- composes in a natural ...log likelihood ...
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MAXIMUM LIKELIHOOD ESTIMATION OF LINKAGE AND INTERFERENCE FROM TETRAD DATA
... As in the case of two-point crosses with an estimate of interference, the values of x obtained from the equations for ranked data with interference are equal to - (1/2)ln p ( 0 [r] ...
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Particle methods for maximum likelihood estimation in latent variable models
... for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo ...of maximum likeli- hood ...
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