Properties of maximum likelihood estimators
The Relative Performance of Targeted Maximum Likelihood Estimators
... DR estimators is “boundedness,” in that for a finite sample, estimators of the mean response fall in the parameter space with probability ...1. Estimators that impose such a restriction can introduce ...
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Consistent Pseudo Maximum Likelihood Estimators and Groups of Transformations
... If A is the group of triangular matrices with positive diagonal elements, then A ∗ 0 is unique up to homothetic transformations of the columns. Indeed, the permutations of the columns are no longer possible. It is ...
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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- ...coverage properties of such intervals are determined and it is shown that symmetric ...
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Moderate deviations of maximum likelihood estimators under alternatives
... Basic properties as the asymptotic null distribution and consistency for data driven smooth tests for composite goodness of fit hypotheses have been proved in Inglot et ...
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Asymptotic Efficiency of Maximum Likelihood Estimators Under Misspecified Models
... 1.Introduction Maximum likelihood based procedures are quite predominant in classical statistical ...these properties may not hold if the model is ...
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Modified maximum likelihood estimators using ranked set sampling
... MML estimators and compare them with competitors based on ...efficiency properties of these estimators are ...new estimators for the population mean and variance using two modified ranked set ...
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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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Performance of the maximum likelihood estimators for the parameters of multivariate generalized Gaussian distributions
... these estimators has not been inves- tigated, which is the main objective of this ...the maximum likelihood estimator (MLE) of the MGGD scatter matrix exists and is unique up to a scalar ...derives ...
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Maximum likelihood estimators in linear regression models with Ornstein Uhlenbeck process
... 11. Wu, WB: M-Estimation of linear models with dependent errors. Ann. Stat. 35(2), 495-521 (2007) 12. Fox, R, Taqqu, MS: Large sample properties of parameter estimates for strongly dependent stationary Gaussian ...
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Maximum likelihood estimators of a long memory process from discrete observations
... The maximum likelihood technique is chosen in this paper because of two reasons: one is that this technique has been applied efficiently in a large set; the other is that it has well-documented favorable ...
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Detecting rare and faint signals via thresholding maximum likelihood estimators
... For testing rare and faint signals in means, Donoho and Jin (2004) showed that the Higher Criticism (HC) test can attain the optimal detection boundary [Ingster (1997)] for uncorrelated Gaussian random vectors; see ...
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Maximum Likelihood Estimators for Markov Switching Autoregressive Processes with ARCH Component
... 1 Introduction 1 Introduction Autoregressive (AR) processes and autoregressive conditionally heteroscedastic (ARCH) processes are well established and very popular models. While AR processes can be used for forecasting, ...
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Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes
... To the best of our knowledge, our results (Theorems 3, 4, 5, 6 and 7) provide the first increasing-domain asymptotic analysis of Gaussian maximum likelihood and cross validation for non-Gaussian random ...
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Multiple Choice Tests: Inferences Based on Estimators of Maximum Likelihood
... unconditioned estimators by means of the maximum likelihood ...some properties arising from the unconditional inference, some additional issues regarding this model are also going to be ...
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CiteSeerX — The alter egos of the regularized maximum likelihood density estimators: deregularized maximum-entropy,
... important properties: (i) L1 = (1/n)1 n , where 1 n is the vector of ones with length n; (ii) Lv = x, where x is the vector consisting of the sample points x i ...
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Higher order properties of GMM and generalised empirical likelihood estimators
... empirical likelihood (EL), continuous updating, and exponential tilt- ing ...these estimators share a common structure, being members of a class of generalized empirical likelihood (GEL) ...of ...
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Modified Moment, Maximum Likelihood and Percentile Estimators for the Parameters of the Power Function Distribution
... The Power function distribution is a flexible life time distribution model that may offer a good fit to some sets of failure data. Theoretically Power function distribution is the inverse of Pareto distribution. An ...
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Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators
... di¤erentiability properties of the mapping 7! ~ p k(n) ( ), which we were unable to ...di¤erentiability properties via the implicit function theorem is not feasible here since ~ p k(n)( ) falls on the ...
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Fixed-domain asymptotic properties of composite likelihood estimators for Gaussian processes
... The maximum likelihood method is generally considered as the best option for estimating the covariance parameters of a Gaussian process (at least in the framework of the present paper, where the true ...
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Properties of Maximum Likelihood Male Fertility Estimation in Plant Populations
... log of the likelihood with equal fertilities, and is symbolized mance of the estimators compared with standard param- as D log L. For each statistical test, 500 data sets were simulated eter values ...
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