Weibull tail-distributions revisited: A new look at some tail estimators

In this paper, we propose to include Weibull tail-distributions in a more general family of distributions. In particular, the considered model also encompasses the whole Fréchet maximum domain of attraction as well as log-Weibull tail-distributions. The asymptotic normality of some tail estimators based on the log-spacings between the largest order statistics is established in a unified way within the considered family. This result permits to understand the similarity between most estimators of the Weibull tail-coefficient and the Hill estimator. Some different asymptotic properties, in terms of bias, rate of convergence, are also highlighted.     

Khmer Potent Places: Pāramī and the Localisation of Buddhism and Monarchy in Cambodia

Cambodia is strewn with places of national, local or, most frequently, village importance, considered as potent places, that is to say, places that are said to have agency and a positive or negative power of interaction with human beings. This paper emphasises the constituent principles of potency using case studies based on ethnographic research conducted between 2007 and 2015 in Pursat province, western Cambodia. Beginning with the analysis of the sanctuary of a powerful land guardian spirit called Khleang Muang, the author progressively guides the reader to all the potent places that form a network which spatially tells the legend of the sixteenth-century Khmer King Ang Chan who passed by Pursat, coming from Angkor and settled in Lovek (south of Tonle Sap Lake). Violent death and sacrifices, rituals, spiritual energy called paramī, old buildings, monasteries, precious tableware kept in the soil, trees, stones, termite mounds?…?all those constituents of the potency of the places are analysed. The author’s discussion of the core of potency (pāramī and paramī) enables her to show how Buddhism and land guardian spirit cults are entangled in a single still hierarchical religious system. Finally, the author analyses how potent places in Cambodia embody a process of localisation of the nation-level institution of monarchy.     

Smooth Conditional Distribution Function and Quantiles under Random Censorship

We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional -quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).     

Nonparametric regression estimation of conditional tails: the random covariate case

We present families of nonparametric estimators for the conditional tail index of a Pareto-type distribution in the presence of random covariates. These families are constructed from locally weighted sums of power transformations of excesses over a high threshold. The asymptotic properties of the proposed estimators are derived under some assumptions on the conditional response distribution, the weight function and the density function of the covariates. We also introduce bias-corrected versions of the estimators for the conditional tail index, and propose in this context a consistent estimator for the second-order tail parameter. The finite sample performance of some specific examples from our classes of estimators is illustrated with a small simulation experiment.     

Estimating the conditional tail index by integrating a kernel conditional quantile estimator

This paper deals with the estimation of the tail index of a heavy-tailed distribution in the presence of covariates. A class of estimators is proposed in this context and its asymptotic normality established under mild regularity conditions. These estimators are functions of a kernel conditional quantile estimator depending on some tuning parameters. The finite sample properties of our estimators are illustrated on a small simulation study.     

Estimation of extreme quantiles from heavy and light tailed distributions

In Gardes et al. (2011), a new family of distributions is introduced, depending on two parameters τ$\tau$ and θ$\theta$, which encompasses Pareto-type distributions as well as Weibull tail-distributions. Estimators for θ$\theta$ and extreme quantiles are also proposed, but they both depend on the unknown parameter τ$\tau$, making them useless in practical situations. In this paper, we propose an estimator of τ$\tau$ which is independent of θ$\theta$. Plugging our estimator of τ$\tau$ in the two previous ones allows us to estimate extreme quantiles from Pareto-type and Weibull tail-distributions in an unified way. The asymptotic distributions of our three new estimators are established and their efficiency is illustrated on a small simulation study and on a real data set.     

Coordination meetings as a means of fostering collective learning among jury members involved in the validation of prior learning (VPL)

Jury members involved in the validation of prior learning (VPL) are supposed to draw parallels between the skills the candidate has acquired and the criteria established in relation to the frame of reference. The recalibration of criteria is a form of collective work. During meetings, jury members face common obstacles together. They try to sidestep the prescribed work and then collectively take ownership of it. Collective meetings allow responsibilities to be shared. This contrast between the imposition of extremely narrow prescribed work and the possibility of modifying prescribed work during collective meetings, sets a dialogic process in motion. Such a process gives jury members the opportunity to evolve in their practices. This ensures that jury members are always in a position to reflect on their own methods of action.