A voluminous literature on right-censored failure time data has been developed in the past 30 years. Due to advances in biomedical research, interval censoring has become increasingly common in medical follow-up studies. ...

The first part studies the problem of estimating the covariance matrix in a star-shaped model with missing data. By introducing a class of priors based on a type of Cholesky decomposition of the precision matrix, we then ...

Interval-censored failure time data commonly arise in clinical trials and medical studies. In such studies, the failure time of interest is often not exactly observed, but known to fall within some interval. For multivariate ...

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Longitudinal studies are conducted widely in fields such as agriculture and life sciences, business and industry, demography and other social sciences, ...

We consider a multivariate regression model with time varying volatilities in the error term. The time varying volatility for each component of the error is of unknown nature, may be deterministic or stochastic. We propose ...

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Three distinct but related topics contribute my work in objective Bayesian methodology and spatio-temporal models. This dissertation starts with the ...

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The smoothing splines and penalized regression splines (P-splines) are popular nonparametric regression methods for curve fitting problems, and the ...

The processes governing environmental systems are often complex, involving different interacting scales of variability in space and time. The complexities and often high dimensionality of such spatio-temporal processes can ...

As a branch of statistics, survival analysis, which is often referred to as "reliability theory" in engineering, has a long history. While in practical problems, some information might be missing. This dissertation discusses ...