misspecified. The most commonly used robust confidence interval, the generalized Wald interval, is known to be liberal in small … performance: the generalized score interval; the robust profile likelihood interval; a new, modified generalized score interval …

constrained nonparametric maximum likelihood estimator (C-NPMLE) of the survivor functions in one- and two-sample settings …

for the ratio and odds ratio of two survival functions through both parametric and nonparametric approaches.We first … construct empirical likelihood confidence interval and simultaneous confidence bands for the odds ratio of two survival … functions to address small sample efficacy and sufficiency. The empirical log-likelihood ratio is developed, and the …

of Finance 56, 815849] argue that fluctuations from the equilibrium ratio of consumption to wealth (cy) reflect changing …

on the latent variables cannot be verified directly using observed data. Even though semiparametric and nonparametric … inference is robust under certain latent-model assumptions. We refer to such robustness as latent-model robustness.We start with …

. Unfortunately, as I show here, all existing null model tests are biased or non-robust. Although both qualities are problematic, the …. To fix the problem, I derive robust tests. Letting i and j denote the ith and jth colonists to arrive at a site …

squares methods. We use Huber's loss function in developing robust methods for time-course multivariate responses. We use … parts. The first part develops a robust score test for linear models by a modification of the well-known Rao's score test … dissertation, we propose a robust clustering method based on the EM algorithm applied to a modified multivariate normal density …