Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 86 for “"Maximum likelihood estimator"”.
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Finite sample properties of the maximum likelihood estimator in continuous time models
… three papers on finite sample properties of the maximum likelihood (ML) estimator of parameters in continuous time dynamic models. In the first chapter, we obtain analytical expressions to approximate the bias and variance of the ML estimator in a univariate model with a known mean. We analyze …
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First order bias and second order variance of the Maximum Likelihood Estimator with application to multivariate Gaussian data and time delay and Doppler shift estimation
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 2000.
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Estimation in Truncated Exponential Family of Distributions
… statistical inference. The non-existence of the maximum likelihood estimator (m.l.e.) with positive probability in certain truncated distributions is not well known. To mention a few results in the literature:</p> <p>(i) Deemer and Votaw 1955 show that the maximum likelihood estimator does not …
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Concentration Inequalities for Dependent Random Variables on Bayesian Networks
… we illustrate about the concentration of the maximum likelihood estimator of some learning models. We also show the optimality of certain results and the comparison to the results in other relevant literature.
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Topics on the estimation of small probabilities
In Part I the Maximum Likelihood/Entropy (ML/E) method of estimation of the cell probabilities for multinomial and contingency table problems is derived and discussed. This method is a generalization of the Maximum Likelihood estimator to situations when small probabilities are to be estimated and …
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A multivariate GARCH model for the non-normal behaviour of financial assets
… Kozubowsky and Podgorski (2003). We prove that maximum likelihood estimator provides optimal estimates of the relevant parameters estimated. We show the applicability of our approach in a comprehensive set of risk management implementations where we compute Value-at-Risk and Expected-Shorfall …
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Identification of linear sampled data systems.
A least squares estimator is derived for the state transition matrix phi of a linear, stationary sampled data system operating in a stochastic environment. The estimator is shown to be unbiased and minimum variance under the condition of full observability of the state vector of the system. The …
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Estimation in random field models for noisy spatial data
… random field. Large sample properties of the Maximum Likelihood Estimator (MLE) of an Onrstein-Uhlenbeck process model with measurement error are studied. The effect caused by adding measurement error, or ""nugget,"" is revealed by the fixed region asymptotics of the MLE. The kriging predictor …
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Mark-Recapture Creel Survey and Survival Models
… follows a binomial distribution. We obtain the maximum likelihood estimator and the moment estimator of the exploitation rate. We also compare the performance of these two estimators. In Chapter 3, the model based approach of Chapter 2 is extended to the case where the space-time units of the …
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Investigation of bootstrap estimates of the parameters, their standard errors, and associated confidence intervals of structural equation models with ordered categorical variables
… simulation, and it is also compared with the Maximum Likelihood estimator applied on both polychoric correlation matrices and Pearson's product moment correlation matrices. The bootstrap samples are generated randomly and transformed, so that they preserve the covariance structure of the …
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From Homogeneous To Heterogeneous: Statistical 3-D Signal Reconstruction Of Macromolecular Complexes
… thesis focuses on developing statistical models, estimators for the parameters in the models, algorithms for determining the estimates, and computational implementations using high performance computing of the algorithms and demonstrates these results on biological problems where the complex is a …
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Modelling long-term security returns
… and evaluate returns on common stocks using the Maximum Likelihood Estimator (MLE), assuming that daily log returns follow a normal distribution. Additionally, the Merton Jump Diffusion (MJD) model is considered to account for jumps in stock trajectories with an independent Poisson process term …
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Theory and Algorithms for Penalization, Graphical Models, and Surrogate Marker Evaluation
… we introduce a general slow rate bound for maximum regularized likelihood estimators in Kullback-Leibler divergence. The result applies to a wide variety of models and estimators where the densities have a convex parametrization, and the regularization is definite and positively homogenous. …
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Per-flow cardinality estimation based on virtual LogLog sketching
… Firstly, we propose and investigate a family of estimators that generalizes the original vHLL estimator and evaluate the performance of the vHLL estimator compared to other estimators in this family. Secondly, we propose an alternative solution to the estimation problem by deriving a …
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Analysis of a high resolution deep ocean acoustic navigation system
… regression techniques are employed to develop a maximum likelihood estimator for net element positions based on these phase and travel time measurements. An approximate error covariance matrix is generated and an optimum choice of survey points is indicated., The combined system, using these …
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Methods and Theory for Joint Estimation of Incidental and Structural Parameters in Latent Class Models
Marginal maximum likelihood estimation has become the standard for parameter estimation in latent variable models. However, there are instances when alternative estimators that jointly estimate incidental parameters and structural parameters might be easier to implement. A drawback to joint …
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Empirical Bayes methods in time series analysis
… the Empirical Bayes method often leads to estimators which have smaller mean squared errors than the classical estimators. Suppose there is an unobservable random variable θ, where θ ~ G(θ), usually called a prior distribution. The Bayes estimator of θ cannot be obtained in general unless …
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Data-driven Techniques For Estimation And Stochastic Reduction Of Multiscale Systems
… high dimensional Lorenz-96 model. First estimator considered for the reduced model is approximate Maximum Likelihood estimator which is highly dependent on the subsampling time-step of the given data. There is no feasible solution to compute optimal subsampling time-step for consistent …
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Properties of two modified moment estimators for parameters of the negative binomial distribution
… deals with the properties of two modified moment estimators for parameters of the negative binomial distribution (NBD). Several parametric forms have been suggested for the NBD. The estimation problems vary according to the form which is used. In particular, the form proposed by Anscombe …
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