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You are viewing titles for UNIVERSITY OF CONNECTICUT in the Statistics available through the UMI Dissertations & Thesis Gradwoorks site
 
Modelling genetic data using Bayesian hierarchical models
 A factor and vector-AR model on analyzing high dimension volatility for high-frequency financial data
 
Mining tools for high-dimensional time series data using spectral methods
 Hidden Markov models for anomaly detection and fault diagnosis
 
Bayesian methods for high-throughput gene expression data in bioinformatics
 Generalized linear models and beyond: An innovative approach from Bayesian perspective
 
Maximum likelihood estimation and multiple imputation: A Monte Carlo comparison of modern missing data techniques for multilevel data
 Asymptotic properties of generalized kernel density estimators
 
Bayesian phylogenetic model selection and applications
 Contributions to microarray data analysis
 
General classes of skewed link functions for categorical response data
 Semiparametric functional estimation and extreme value modeling using mixture distributions and limited quantile information
 
Volatility estimation and option pricing
 A multivariate spatial point process model: Theory, simulation, and application
 
A new class of Bayesian survival models and beyond
 Link Specification and Spatial Dependence for Generalized Linear Mixed Models
 
Diagnostic Accuracy of a Binary Test in the Presence of Two Types of Missing Values
 Statistical Inference for a Normal Distribution with Variance as a Multiple of Its Mean
 
A comparison of statistical models for multiple treatment groups meta-analysis
 Bayesian Inference of survival data with gamma process priors
 
Statistical Inferences for Interval Censored Data
 Performance of U-Statistics Having Kernels of Degree Higher Than Two in Inference Problems with Applications
 
Bayesian methodologies for time-course gene expression data and clinical trial data
 Asymptotics of Clustering for Smooth Distributions