Global ETD Search
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Showing 1 to 6 of 6 for “"Pseudolikelihood"”.
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Statistical models for social support networks: Application of exponential models to undirected graphs with dyadic dependencies
… to this problem that has been proposed uses pseudolikelihood estimation procedures to fit exponential models under assumptions of certain types of dependencies among the network ties. The pseudolikelihood estimates, although not identical to the maximum likelihood estimates, are often quite …
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A Theoretical Development and Simulation-Based Comparison of Four Parameter Estimation Methods for the Spatio-Temporal Autologistic Model with Emphasis on Maximum Generalized and Block Generalized Pseudolikelihood
… for the autologistic model are maximum pseudolikelihood (PL) and Markov Chain Monte Carlo Maximum Likelihood (MCMCML). Two newer and less understood approaches are maximum generalized pseudolikelihood (GPL) and maximum block generalized pseudolikelihood (BGPL). Both of these newer …
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A Theoretical Development and Simulation-Based Comparison of Four Parameter Estimation Methods for the Spatio-Temporal Autologistic Model with Emphasis on Maximum Generalized and Block Generalized Pseudolikelihood
… for the autologistic model are maximum pseudolikelihood (PL) and Markov Chain Monte Carlo Maximum Likelihood (MCMCML). Two newer and less understood approaches are maximum generalized pseudolikelihood (GPL) and maximum block generalized pseudolikelihood (BGPL). Both of these newer …
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Loglinear Models as Item Response Models
… effectiveness of the developed models and the pseudolikelihood estimation method, I will present results of a series of simulation studies. To demonstrate the practical advantages of the methods, I will give a detailed description of an application to a real data set from a study on verbally …
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Optimization Methods for Machine Learning under Structural Constraints
… We propose a novel estimator via ℓ₀ℓ₂-penalized pseudolikelihood. We then design a specialized nonlinear Branch-and-Bound (BnB) framework that solves a mixed integer programming (MIP) formulation of the proposed estimator. Our estimator is computationally scalable to p~10,000, and provides faster …
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Multivariate Analysis of Dietary Data in the Presence of Excess Zeros and Measurement Error
… occasionally-consumed food intakes utilising a pseudolikelihood approach and parametric bootstrap for parameter estimation. The approach is illustrated by modelling the intake of alcohol, jointly with the intake of other foods, and the resulting analysis is compared with that based on the …