Intelligent transportation systems (ITS) are becoming more and more effective, benefiting
from big data. Despite this, missing data is a problem that prevents many prediction …

Quantile estimation has attracted significant research interest in recent years. However,
there has been only a limited literature on quantile estimation in the presence of incomplete …

Abstract Development of imputation procedures appropriate for data with extreme values or
nonlinear relationships to covariates is a significant challenge in large scale surveys. We …

Crop yields and harvest prices are often considered to be negatively correlated, thus acting
as a natural risk management hedge through stabilizing revenues. Storage theory gives …

We address the problem of imputation when a response or covariate may be subject to a
nonignorable (or, equivalently, missing not at random) nonresponse, meaning the response …

Within this dissertation are three statistical applications to problems in actuarial science. We
expand upon the previously established stochastic volatility with discontinuous jumps for …

Quantile treatment effects can be important causal estimands in the evaluation of biomedical
treatments or interventions for health outcomes such as birthweight and medical cost …

Intelligent transportation systems (ITSs) are becoming more and more effective. Robust and
accurate short-term traffic prediction plays a key role in modern ITS and demands …