Toward Comprehensive Refugee Legislation in Hong Kong? Reflections on Reform of the 'Torture Screening' Procedures

Commentpublished_or_final_versio

Bayesian hierarchical linear mixed models for additive smoothing splines

Generalized linear mixed models, Gibbs sampling, Linear mixed models, Markov chain Monte Carlo, Multivariate normal, Variance components,

Convergence rates for trigonometric and polynomial-trigonometric regression estimators

Upper bounds are derived for the rates of convergence for trigonometric series regression estimators of an unknown, smooth regression function. The resulting rates depend on the regression function satisfying certain periodic boundary conditions that may not hold in practice. To overcome such difficulties alternative estimators are proposed which are obtained by regression on trigonometric functions and low-order polynomials. These estimators are shown to always be capable of obtaining the optimal rates of convergence over a particular smoothness class of functions, irregardless of whether or not the regression function is periodic.Guaranteed rates mean squared error nonparametric regression orthogonal series

Error Analysis and Ultrasonic Scattering Amplitude Estimation Using the Wiener Filter with Limited Prior Information

In ultrasonic nondestructive evaluation (NDE), flaw characterization is inhibited by the effects of the measurement system and by acoustic noise due to non-flaw related scattering of the sound. The Wiener filter can be formulated to optimally remove the effects of the measurement system and suppress the noise; however, prior information must be available about the noise and flaw distributions, respectively. The objective of this research is to develop an approach for the optimal implementation of the Wiener filter given prior noise information but no prior flaw information.</p