UNCONDITIONAL MAXIMUM LIKELIHOOD ESTIMATORS FOR THE
An unconditional maximum likelihood test for a unit rood
... Such tests are often called unit root tests (unit roots being the null hypothesis) but could arguably also.. be called tests for stationarity when that is taken as the alternative.[r] ...
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Distributions of Maximum Likelihood Estimators and Model Comparisons
... 6 Conclusion Analysts should consider using exact densities for maxi- mum likelihood estimates whenever it is practical to do so. The densities are particularly appropriate where al- ternative models are to be ...
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Obtaining Expected Maximum Log Likelihood Estimators
... equating the derivative of the sample likelihood to zero and solving for 0 is a plausible way of estimating 00.. Of course, it also maximises the sample.[r] ...
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The Relative Performance of Targeted Maximum Likelihood Estimators
... many estimators rely in one way or another on the inverse probability of censoring weights ...Such estimators can be biased and highly variable under practical or theoretical violations of the positivity ...
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Unconditional maximum likelihood estimation of dynamic models for spatial panels
... the unconditional likelihood function of the model formulated in ...obtain unconditional results by taking into account the density function of the first observation of each time-series of ...exact ...
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Consistent Pseudo Maximum Likelihood Estimators and Groups of Transformations
... pseudo-maximum likelihood (PML) method, that is, by using a misspecified distribution of the errors, but the PML estimator of β is in general not ...PML estimators of appropriate functions of ...
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Maximum Likelihood Estimators for a Supercritical Branching Diffusion Process
... In Section 2, we establish the model and the main notations. Also, we give certain sufficient conditions in order to have the existence of diffusion model and the nonexplosion on finite time of the branching part. These ...
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Confidence sets based on penalized maximum likelihood estimators
... penalized maximum likelihood estima- tors such as the LASSO, adaptive LASSO, and hard-thresholding are an- ...the maximum likelihood ...penalized estimators are tuned to possess the ...
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Moderate deviations of maximum likelihood estimators under alternatives
... of estimators of these nuisance parameters not only under the null hypothesis, but also under ...in estimators of the nuisance parameters in tests which are devel- oped assuming that the nuisance parameters ...
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Asymptotic Efficiency of Maximum Likelihood Estimators Under Misspecified Models
... University of Florida Abstract We illustrate with examples when and how maximum likelihood estimators continue to be asymptotically efficient even under misspecified models. Also, we provide a ...
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Modified maximum likelihood estimators using ranked set sampling
... closed-form maximum likelihood estimators (MLEs) of population mean and variance under ranked set sampling (RSS) do not exist since the likelihood equations involve nonlinear functions and ...
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On the distribution of penalized maximum likelihood estimators: The LASSO, SCAD, and thresholding.
... the Estimators We start with the orthogonal linear regression model Y = Xβ + u where X 0 X is diagonal and the vector u is multivariate normal with mean zero and variance covariance matrix σ 2 ...least-squares ...
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On the distribution of penalized maximum likelihood estimators: The LASSO, SCAD, and thresholding
... thresholding estimators, in finite samples and in the large-sample ...the estimators are tuned to perform consistent model selection and for the case where the es- timators are tuned to perform conservative ...
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Maximum Likelihood Estimators for Multivariate Hidden Markov Mixture Models
... In this paper we consider a multivariate switching model, with constant states means and covariances. In this model, the switching mechanism between the basic states of the observed time series is controlled by a hidden ...
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Multiple Choice Tests: Inferences Based on Estimators of Maximum Likelihood
... unconditioned estimators by means of the maximum likelihood ...the unconditional inference, some additional issues regarding this model are also going to be addressed, ...
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Expansions for Approximate Maximum Likelihood Estimators of the Fractional Difference Parameter
... Whittle likelihood as a summand of two terms, with dependence on d only through the second term in the summand, which is a scaled quadratic form in Gaussian long memory ...
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On the distribution of penalized maximum likelihood estimators: The LASSO, SCAD, and thresholding.
... Bridge estimators studied by Frank and Friedman (1993), least an- gle regression (LARS) of Efron, Hastie, Johnston, Tibshirani (2004), or the smoothly clipped absolute deviation (SCAD) estimator of Fan and Li ...
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CiteSeerX — The alter egos of the regularized maximum likelihood density estimators: deregularized maximum-entropy,
... of maximum entropy principle with that of min- imum Kullback-Leibler divergence, in our discretized version deregularized to min- imize, over the very same sieve, the discrepancy of the estimated density to the ...
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Performance of the maximum likelihood estimators for the parameters of multivariate generalized Gaussian distributions
... To cite this version: Lionel Bombrun, Fr´ ed´ eric Pascal, Jean-Yves Tourneret, Yannick Berthoumieu. Performance of the maximum likelihood estimators for the parameters of multivariate generalized ...
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Maximum likelihood estimators in linear regression models with Ornstein Uhlenbeck process
... some estimators of β , θ and σ are given by the quasi-maximum likelihood ...quasi-maximum likelihood estimators as well as asymptotic normality are investigated in Section ...
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