Chaudhuri, Doksum and Samarov (1997) have recently stressed the usefulness of the quantile regression formulation for survival analysis and for transformation models, more generally. In this paper, we explore the use of quantile regression in survival analysis by reanalysing a large experimental...

Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and...

Single index linear models for binary response with random coefficients have been extensively employed in many econometric settings under various parametric specifications of the distribution of the random coefficients. Nonparametric maximum likelihood estimation (NPMLE) as proposed by Cosslett...

Efron's elegant approach to g-modeling for empirical Bayes problems is contrasted with an implementation of the Kiefer-Wolfowitz nonparametric maximum likelihood estimator for mixture models for several examples. The latter approach has the advantage that it is free of tuning parameters and...

Shape constraints play an increasingly prominent role in nonparametric function estimation. While considerable recent attention has been focused on log concavity as a regularizing device in nonparametric density estimation, weaker forms of concavity constraints encompassing larger classes of...