ProQuest Subject Index - Statistics at DUKE UNIVERSITY

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You are viewing titles for DUKE UNIVERSITY in the Statistics available through the UMI Dissertations & Thesis Gradwoorks site

The comparison of information functions in sensor planning	Clustering Multiple Related Datasets with a Hierarchical Dirichlet Process

Bayesian Models for Relating Gene Expression and Morphological Shape Variation in Sea Urchin Larvae	Bayesian functional data analysis for computer model validation

Conditions for rapid and torpid mixing of parallel and simulated tempering on multimodal distributions	Model selection and multivariate inference using data multiply imputed for disclosure limitation and nonresponse

Bayesian analysis in cancer pathway studies and probabilistic pathway annotation	Conserving moving species under changing landscapes and climates

Some advances in Bayesian nonparametric modeling	Bayesian function estimation using overcomplete dictionaries with application in genomics

Multi-task learning for sequential data via the infinite hidden Markov model and the nested Dirichlet process	Theory and practice in replica-exchange molecular dynamics simulation

Using data augmentation and stochastic differential equations in spatio temporal modeling	Extreme value modeling for space-time data with meteorological applications

Nitric oxide synthase genes, environmental factors, and complex interactions in families with Parkinson's disease	Statistical computation for model space exploration in high-dimensional problems

Bayesian analysis and computational methods for dynamic modeling	Automated microscopy and high throughput image analysis in Arabidopsis and Drosophila

Bayesian adjustment for multiplicity	Levy random measures: Posterior consistency and applications

Statistical methods for dynamic network data	Bayesian additive regression kernels

Bayesian methods to characterize uncertainty in predictive modeling of the effect of urbanization on aquatic ecosystems	Bayesian multi- and matrix-variate modelling: Graphical models and time series

Bayesian model uncertainty and prior choice with applications to genetic association studies	Machine learning with Dirichlet and beta process priors: Theory and applications

Bayesian mixture modeling approaches for intermediate variables and causal inference	Modeling point patterns, measurement error and abundance for exploring species distributions

Bayesian spatial quantile regression	Separating features from noise with persistence and statistics

Modeling multi-factor binding of the genome	Nonparametric Bayes models for high-dimensional and sparse data

Probability Models for Targeted Borrowing of Information	Kernel Averaged Predictors for Space and Space-Time Processes

Factor Models to Describe Linear and Non-linear Structure in High Dimensional Gene Expression Data.	Bayesian Sparse Learning for High Dimensional Data

Development and Implementation of Bayesian Computer Model Emulators	Bayesian Modelling and Computation in Dynamic and Spatial Systems

Computational Methods for Investigating Dendritic Cell Biology	Structural Estimation Using Sequential Monte Carlo Methods

Nonparametric Bayesian context learning for buried threat detection	Transparent and Efficient I/O for Statistical Computing

Bayesian Nonparametric Modeling and Theory for Complex Data	Bayesian Semi-parametric Factor Models

Dependent Hierarchical Bayesian Models for Joint Analysis of Social Networks and Associated Text	Bayesian and Information-Theoretic Learning of High Dimensional Data

Bayesian Modeling Using Latent Structures	Autonomous Modeling, Statistical Complexity and Semi-annealed Treatment of Boolean Networks

Mixture Modeling, Sparse Covariance Estimation and Parallel Computing in Bayesian Analysis	Bayesian Analysis of Latent Threshold Models

Approximate Bayesian computation for complex dynamic systems