Estimation of parameters in heavy-tailed distribution when its second order tail parameter is known

Estimating parameters in heavy-tailed distribution plays a central role in extreme value theory. It is well known that classical estimators based on the first order asymptotics such as the Hill, rank-based and QQ estimators are seriously biased under finer second order regular variation framework. To reduce the bias, many authors proposed the so-called second order reduced bias estimators for both first and second order tail parameters. In this work, estimation of parameters in heavy-tailed distributions are studied under the second order regular variation framework when the second order parameter in the distribution tail is known. This is motivated in large part by a recent work by the authors showing that the second order tail parameter is known for a large class of popular random difference equations (for example, ARCH models). The focus is on least squares estimators that generalize rank-based and QQ estimators. Though other possible estimators are also briefly discussed, the least squares estimators are most simple to use and perform best for finite samples in Monte Carlo simulations.     

Beauty is in the in-group of the beholded: Intergroup differences in the perceived attractiveness of leaders

Physical attractiveness is most commonly presumed to be an exogenous characteristic that influences people's feelings, perceptions, and behavior across myriad types of relationships. We investigate the opposite prediction in which feelings toward other people influence the perceptions of others' attractiveness. Focusing specifically on subordinates' perceptions of leaders of in-groups and out-groups, we examine whether group membership moderates familiarity in relation to ratings of physical attractiveness. Studies 1 and 2 show that subordinates rate the leaders of their in-groups as significantly more physically attractive than comparably familiar out-group leaders. Our findings have relevance for understanding the interactive roles of physical attractiveness within contemporary organizational environments and help to account for variance in interpersonal perceptions on the basis of group membership. In contrast with research traditions that treat physical attractiveness as a static trait, our findings highlight the importance of group membership as a lens for perceiving familiar leaders' physical attractiveness.     

Long-range dependence analysis of Internet traffic

Long-range-dependent time series are endemic in the statistical analysis of Internet traffic. The Hurst parameter provides a good summary of important self-similar scaling properties. We compare a number of different Hurst parameter estimation methods and some important variations. This is done in the context of a wide range of simulated, laboratory-generated, and real data sets. Important differences between the methods are highlighted. Deep insights are revealed on how well the laboratory data mimic the real data. Non-stationarities, which are local in time, are seen to be central issues and lead to both conceptual and practical recommendations.     

Transformative Events and Generational Memory: A Case Study Over Time in Lithuania

Research on the distribution of collective memories in national populations has often been conducted in relatively stable societies, where most individuals have experienced a limited range of event types. We examine collective memories in Lithuania, a society that has seen substantial change, using three surveys conducted during the two decades since Lithuanian protests against Soviet rule began in the late 1980s. We identify two types of events that individuals may recall, drawing on Sewell's ( 2005 ) distinction between structure‐transforming events and other events that are significant but less momentous, and we find that the two types of events exhibit different patterns of change over time: in particular, transformative events may absorb other events through assimiliation and are likely to be the focus of commemoration. Recall of transformative events also shows a distinctive relation to birth cohort. Our results support the need to take into account the nature of events in order to understand which events are remembered as important and by whom.