Inference for low- and high-dimensional inhomogeneous Gibbs point processes

Gibbs point processes (GPPs) constitute a large and flexible class of spatial point processes with explicit dependence between the points. They can model attractive as well as repulsive point patterns. Feature selection procedures are an important topic in high-dimensional statistical modeling. In this paper, a composite likelihood (in particular pseudo-likelihood) approach regularized with convex and nonconvex penalty functions is proposed to handle statistical inference for possibly high-dimensional inhomogeneous GPPs. We particularly investigate the setting where the number of covariates diverges as the domain of observation increases. Under some conditions provided on the spatial GPP and on penalty functions, we show that the oracle property, consistency and asymptotic normality hold. Our results also cover the low-dimensional case which fills a large gap in the literature. Through simulation experiments, we validate our theoretical results and finally, an application to a tropical forestry dataset illustrates the use of the proposed approach.     

Role of land-cover and WUI types on spatio-temporal dynamics of fires in the French Mediterranean area

This work aims at assessing, in the French Mediterranean area, the spatio-temporal trends of fires, including their causes, at fine scale (communities), comparing different periods between 1993 and 2017. These trends were compared to those of land-cover and wildland-urban interface (WUI) which were coupled with a spatial analysis of the ignitions in order to highlight the main drivers and preferential areas. Fire density was highly variable among communities, hotspots being located mostly close to big cities but spatially varying in time in contrast to fire occurrence and burned area. A decrease in the unknown cause proportion and a variation of the cause frequency were highlighted among periods, criminal fires being the most frequent and deleterious, especially before 2009, as well as those due to negligence during private activities, mostly after 2009. Land cover classes significantly varied among periods, artificialized and natural areas presenting a reversed trend compared with agricultural areas. Natural areas were the most affected by ignitions (60%), regardless of the period; this trend is slowly decreasing. WUI represented ∼30% of the study area, the different types varying spatially (denser clustered types mostly located in the South-East) and showed an increase over time, especially for both clustered types but with high variability among communities. Half of the ignitions occurred in WUI, with “very dense clustered” and “scattered” types being the most affected, especially in 2009. Better understanding the spatio-temporal evolution of fires and of their causes should allow refining the fire policies in terms of awareness raising, firefighting means, and land management.     

A standardized distance-based index to assess the quality of space-filling designs

One of the most used criterion for evaluating space-filling design in computer experiments is the minimal distance between pairs of points. The focus of this paper is to propose a normalized quality index that is based on the distribution of the minimal distance when points are drawn independently from the uniform distribution over the unit hypercube. Expressions of this index are explicitly given in terms of polynomials under any \(L_p\) distance. When the size of the design or the dimension of the space is large, approximations relying on extreme value theory are derived. Some illustrations of our index are presented on simulated data and on a real problem.     

Unbiased and almost unbiased ratio estimators of the population mean in ranked set sampling

In this paper we study the problem of reducing the bias of the ratio estimator of the population mean in a ranked set sampling (RSS) design. We first propose a jackknifed RSS-ratio estimator and then introduce a class of almost unbiased RSS-ratio estimators of the population mean. We also present an unbiased RSS-ratio estimator of the mean using the idea of Hartley and Ross (Nature 174:270?C271, 1954) which performs better than its counterpart with simple random sample data. We show that under certain conditions the proposed unbiased and almost unbiased RSS-ratio estimators perform better than the commonly used (biased) RSS-ratio estimator in estimating the population mean in terms of the mean square error. The theoretical results are augmented by a simulation study using a wheat yield data set from the Iranian Ministry of Agriculture to demonstrate the practical benefits of our proposed ratio-type estimators relative to the RSS-ratio estimator in reducing the bias in estimating the average wheat production.     

Organizational Stages and Cultural Phases: A Critical Review and a Consolidative Model of Corporate Social Responsibility Development

Based on a stakeholder-oriented conceptualization of corporate social responsibility (CSR), this paper offers a multi-dimensional, dynamic perspective which integrates moral, cultural and strategic aspects of the CSR development process, together with its organizational implications. Therefore, the authors link existing stage models of CSR development with stakeholder culture and social responsiveness continuums and provide a consolidative model which highlights a seven-stage development process towards CSR, articulated around three cultural phases (i.e. CSR reluctance, CSR grasp and CSR embedment). In a context in which literature on CSR development and implementation tends to be overly segmented, this consolidative model integrates organizational values and culture together with management processes and operations. In its emphasis on the importance of the organizational context and characteristics in analyses of organizations' CSR development, the proposed consolidative model offers novel research perspectives and highlights the relevance of adopting a phase-dependent approach.     

Modeling initiation into drug injection among street youth

This study aimed at examining the predictors of initiation into drug injection among street youth using social cognitive theory framework. A prospective cohort study based on semi-annual interviews was carried out. Psychosocial determinants referred to avoidance of initiation. Other potential predictors were: sociodemographic characteristics, relationships with injectors, parent's substance misuse, drug use patterns, homelessness, survival sex, sexual abuse. Independent predictors were identified using Cox proportional hazards regression models. Among the 352 participants, high control beliefs about avoidance of initiation was protective while younger age, daily alcohol consumption, heroin use, cocaine use, and survival sex all increased risk of initiation. Preventive strategies targeting street youth should both enhance youth's control beliefs and actual control over their substance use and improve their life conditions.     

Linguistic human rights as a source of policy guidelines: A critical assessment

The 'linguistic human rights'(LHR) perspective, though relevant to the protection and promotion of minority languages (or, more generally, of linguistic diversity), displays one major weakness, namely, its almost exclusive reliance on moral considerations. Although LHR advocates often back up their claims with other (including economic) arguments, the latter often fail to pass 'hard' validation tests. Hence, the actual import of LHR arguments is constrained by the extent to which the underpinning moral considerations are shared by public opinion and politicians. Even if there is broad consensus around values, arguments in favour of minority language rights can be defeated by three types of objections that have to do with feasibility, costs, and burden sharing. In order to overcome these objections, it is necessary to draw on the tools of policy evaluation, which provides strong arguments in favour of linguistic diversity.