Many longitudinal studies involve relating an outcome process to a set of possibly time-varying covariates, giving rise to the usual regression models for longitudinal data. When the purpose of the study is to investigate the covariate effects when experimental environment undergoes abrupt...

In this paper, we argue that economists can learn a great deal from the design principles implemented in medical research. We develop a theoretical model to show the logic of adaptive sequential experiment design in the presence of uncertainty over negative effects and discuss how to choose...

In many credit risk and pricing applications, credit transition matrix is modeled by a constant transition probability or generator matrix for Markov processes. Based on empirical evidence, we model rating transition processes as piecewise homogeneous Markov chains with unobserved structural...

A class of generalized linear rank statistics is introduced for regression analysis in the presence of truncation or censoring on the response variable. Applications of these statistics to hypothesis testing and estimation are discussed. Martingale theory and stochastic integrals of...

Motivated by the analysis of linear rank estimators and the Buckley-James nonparametric EM estimator in censored regression models, we study herein the asymptotic properties of stochastic integrals of certain two-parameter empirical processes. Applications of these results on empirical processes...