Conditional quantile estimation with auxiliary information for left-truncated and dependent data

In this paper, the empirical likelihood method is used to define a new estimator of conditional quantile in the presence of auxiliary information for the left-truncation model. The asymptotic normality of the estimator is established when the data exhibit some kind of dependence. It is assumed that the lifetime observations with multivariate covariates form a stationary α‐mixing sequence. The result shows that the asymptotic variance of the proposed estimator is not larger than that of standard kernel estimator. Finite sample behavior of the estimator is investigated via simulations too.     

Stochastic Templates for Aquaculture Images and a Parallel Pattern Detector

A general statistical approach is presented for the identification of objects in digital images, motivated by an application in aquaculture involving underwater images of fish. Using Procrustes analysis, a point distribution model is fitted on a set of training images and used as a prior distribution for the shape of a deformable template. The likelihood of a proposed template is calculated in terms of the response from a feature detector along the boundary of the template. The posterior distribution of template variables is examined by using Markov chain Monte Carlo analysis. A key challenge in the aquaculture application is the variable nature of edges arising from the surface curvature of fish and the low contrast between the foreground and background. Conventional gradient-based edge detection proves inadequate, but a parallel pattern detector copes much better. Results are presented for a fully automated analysis of the database. The strengths and weaknesses of this approach are discussed and future developments are outlined.     

On an extension of the von Mises distribution due to Batschelet

This paper considers the three-parameter family of symmetric unimodal circular distributions proposed by Batschelet in [1 Batschelet, E. 1981. Circular Statistics in Biology, London: Academic Press.  [Google Scholar]], an extension of the von Mises distribution containing distributional forms ranging from the highly leptokurtic to the very platykurtic. The family's fundamental properties are given, and likelihood-based techniques described which can be used to perform estimation and hypothesis testing. Analyses are presented of two data sets which illustrate how the family and three of its most direct competitors can be applied in the search for parsimonious models for circular data.     

Comparison of normal probability plots and dot plots in judging the significance of effects in two level factorial designs

In this article, we present a study carried out to compare the effectiveness of the normal probability plot (NPP) and a simple dot plot in assessing the significance of the effects in experimental designs with factors at two levels (2 ^k?p designs). Several groups of students who had just completed a course that covered factorial designs were asked to identify the significant effects in a total of 32 situations, 16 of which were represented using NPPs and the other 16 using dot plots. Although the 32 scenarios were said to be different, there were really only 16 different situations, each of which was represented using the two methods to be compared. A simple graphical analysis shows no evidence that there is a difference between the two procedures. However, in designs with 16 runs there are some cases where NPP seems to give slightly better results.     

Nonparametric location-scale models for censored successive survival times

Let (T₁,T₂) be gap times corresponding to two consecutive events, which are observed subject to (univariate) random right-censoring. The censoring variable corresponding to the second gap time T₂ will in general depend on this gap time. Suppose the vector (T₁,T₂) satisfies the nonparametric location-scale regression model T₂=m(T₁)+σ(T₁)?, where the functions m and σ are ‘smooth’, and ? is independent of T₁. The aim of this paper is twofold. First, we propose a nonparametric estimator of the distribution of the error variable under this model. This problem differs from others considered in the recent related literature in that the censoring acts not only on the response but also on the covariate, having no obvious solution. On the basis of the idea of transfer of tail information (Van Keilegom and Akritas, 1999), we then use the proposed estimator of the error distribution to introduce nonparametric estimators for important targets such as: (a) the conditional distribution of T₂ given T₁; (b) the bivariate distribution of the gap times; and (c) the so-called transition probabilities. The asymptotic properties of these estimators are obtained. We also illustrate through simulations, that the new estimators based on the location-scale model may behave much better than existing ones.     

Climate Mobility and Development Cooperation

Population and Environment - Development cooperation actors have been addressing climate change as a cross-cutting issue and investing in climate adaptation projects since the early 2000s. More...     

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.     

Similarity in friendship networks: Selection or influence? The effect of constraining contexts and non-visible individual attributes

Most research on similarity in friendship networks focuses on clearly visible individual attributes (i.e. attitudes and behaviors) in contexts where choices whom to befriend are relatively unconstrained. These studies often reveal that social selection rather than social influence is the dominant cause of similarity among friends. We argue that in a setting where social collaboration is crucial and friendship choices are more constrained, influence might be the main reason for similarity found among friends. In addition, we examined whether social categorization and peer control amplifies the social influence process among friends. Using a stochastic actor-based model for network dynamics, we analyzed a three-wave dataset of first year Royal Netherlands Naval College officer students on friendship formation and military discipline. The data supports our first hypothesis that students adjust their own military discipline to that of their friends. Contrary to our expectations, we did not find support for the idea that individuals adjust their discipline more to friends who are of the same military specialty, and neither more to friends who exert peer control. We elaborate on these findings in the discussion.     

Biodiversity of the urban homegardens of São Luís city,Northeastern Brazil

There is a widely held notion that the increasing trend of urbanization accelerates loss of biodiversity and displaces native species. This study assessed the validity of this notion in the city of São Luís the capital of the state of Maranhão in the northeastern Brazil. The specific objectives of the study were to (1) assess plant and animal diversity of urban homegardens, (2) compare the diversity of homegardens in terms of origin of these species (exotic or indigenous to Brazil). We conducted a biodiversity survey in 40 randomly selected ‘quintais’ (hereafter called homegardens) from ten locations in the city of São Luis. We evaluated the species richness and diversity of various use categories of plant and animal species indigenous to Brazil as well as exotic species. A total of 186 species of plants in 68 families were recorded in the sampled homegradens. A total of 63 fruit tree species representing 34% of all tree species were found. Of these species, those indigenous to Brazil accounted for 58% of the cases, and this was significantly higher than the exotic species. Most of the species (60%) were indigenous to Brazil (wild and semi-wild domesticates), while the rest (40%) were exotic. A total of 42 species of vertebrates (mainly reptiles, birds and mammals) were also found in the homegardens, of which 47% were indigenous to Brazil. Some of the plant and animal species found in the homegardens are endangered species in their native habitats, suggesting that homegardens could provide a unique opportunity for their conservation and sustainable use. These species continue to play a vital role in the socioeconomic and ecological landscape of the city.