Letter to the Editor

The paper by Alfons, Croux and Gelper (2013), Sparse least trimmed squares regression for analyzing high-dimensional large data sets, considered a combination of least trimmed squares (LTS) and lasso penalty for robust and sparse high-dimensional regression. In a recent paper [She and Owen (2011)], a method for outlier detection based on a sparsity penalty on the mean shift parameter was proposed (designated by "SO" in the following). This work is mentioned in Alfons et al. as being an "entirely different approach." Certainly the problem studied by Alfons et al. is novel and interesting.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS640 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Purchasing Motivations Toward Counterfeit Luxury Goods on E-marketplaces

This research is designed to study consumers’ purchasing attitudes to counterfeit luxury goods on electronic marketplaces (e-marketplaces). And two research hypotheses are proposed in this research. Based on data analysis of 243 samples, this study explores the dimensions of consumer attitudes (morality and law, accessibility, burden-bearing, function effectiveness, economical efficiency) and motivations (conspicuous psychology, rebel psychology, social identity, self-enjoying and cost performance) to luxury counterfeit goods on e-marketplaces. It is found that the major reasons for consumers to choose e-business channels to buy luxury counterfeits are convenience, information acquisition, product and service. In particular, the findings indicate that online consumers’ attitudes toward luxury counterfeit products significantly impact purchasing motivation; online consumers’ attitudes and motivations positively impact purchasing intention

A novel multi-party semiquantum private comparison protocol of size relationship with d-dimensional single-particle states

By using d-level single-particle states, the first multi-party semiquantum private comparison (MSQPC) protocol which can judge the size relationship of private inputs from more than two classical users within one execution of protocol is put forward. This protocol requires the help of one quantum third party (TP) and one classical TP, both of whom are allowed to misbehave on their own but cannot conspire with anyone else. Neither quantum entanglement swapping nor unitary operations are necessary for implementing this protocol. TPs are only required to perform d-dimensional single-particle measurements. The correctness analysis validates the accuracy of the compared results. The security analysis verifies that both the outside attacks and the participant attacks can be resisted.Comment: 19 pages, 2 figures, 2 table