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.
Results
Showing 1 to 8 of 8 for “"estimation consistency"”.
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A penalized estimation procedure for varying coefficient models
… is a recurrent topic in nonparametric function estimation. A function has global sparsity if it is zero over the entire domain, and it indicates that the corresponding covariate is irrelevant to the response variable. A function has local sparsity if it is nonzero but remains zero for a set of …
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Scalable sparsity structure learning using Bayesian methods
… to learn sparsity structure in various models. Estimation consistency and selection consistency of our methods are established. First, a nonparametric Bayes estimator is proposed for the problem of estimating a sparse sequence based on Gaussian random variables. We adopt the popular two-group …
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A penalized linear mixed model with generalized method of moments estimators for complex phenotype prediction
… oracle properties, including variable selection consistency, estimation consistency, and asymptotic normality. We further develop a hybrid screening rule that constitutes of the sequential strong rule and the enhanced dual polytope projection rule to reduce data dimension and improve …
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Identifiability for latent class models
… parameters, and asymptotic analysis such as consistency study on the proposed estimation procedures for identifiable models. In the first part of the thesis, we consider Cognitive Diagnostic Models (CDMs). CDMs are latent variable models developed to infer latent skills, knowledge, or …
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Approximate likelihood for dependent networks and hyperlink predictions
… SBM, and the proposed algorithm has a lower estimation bias and accelerated convergence speed compared to the variational EM. Our simulation studies show that the proposed algorithm outperforms the existing variational EM algorithm assuming conditional independence among edges. We also …
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Heterogeneity modeling and longitudinal clustering
… property. In theory, we establish the consistency properties asymptotically. In addition, we show that our method outperforms the existing competitive approaches in our simulation studies and real data example. In the third part of the thesis, we are interested in marketing …
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Functional Linear Regression in High Dimensions
… apply existing methods for model selection and estimation. We propose a new class of partially functional linear models to characterize the regression between a scalar response and those covariates, including both functional and scalar types. The new approach provides a unified and flexible …
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Sparse spectrum fitting in array processing
… to the problem of Direction-Of-Arrival (DOA) estimation using sensor arrays. By developing the sparse representation models for the spatial covariance matrix of correlated or uncorrelated sources respectively, the DOA estimation problem is reformulated under the framework of Sparse Signal …