Surveying migrant households: a comparison of census-based, snowball and intercept point surveys

Summary.  Few representative surveys of households of migrants exist, limiting our ability to study the effects of international migration on sending families. We report the results of an experiment that was designed to compare the performance of three alternative survey methods in collecting data from Japanese–Brazilian families, many of whom send migrants to Japan. The three surveys that were conducted were households selected randomly from a door-to-door listing using the Brazilian census to select census blocks, a snowball survey using Nikkei community groups to select the seeds and an intercept point survey that was collected at Nikkei community gatherings, ethnic grocery stores, sports clubs and other locations where family members of migrants are likely to congregate. We analyse how closely well-designed snowball and intercept point surveys can approach the much more expensive census-based method in terms of giving information on the characteristics of migrants, the level of remittances received and the incidence and determinants of return migration.     

Order test for high-dimensional two-sample means

We propose a new method to test the order between two high-dimensional mean curves. The new statistic extends the approach of Follmann (1996) to high-dimensional data by adapting the strategy of Bai and Saranadasa (1996). The proposed procedure is an alternative to the non-negative basis matrix factorization (NBMF) based test of Lee et al. (2008) for the same hypothesis, but it is much easier to implement. We derive the asymptotic mean and variance of the proposed test statistic under the null hypothesis of equal mean curves. Based on theoretical results, we put forward a permutation procedure to approximate the null distribution of the new test statistic. We compare the power of the proposed test with that of the NBMF-based test via simulations. We illustrate the approach by an application to tidal volume traces.     

A note on the representation of {E\left({\textit{\textbf {x}}}\otimes {\textit{\textbf {xx}}}^{\prime}\right) } and {E\left({\textit{\textbf {xx}}}^{\prime }\otimes {\textit{\textbf {xx}}}^{\prime }\right)} for the random vector x

In this paper we consider ${E(x\otimes xx^{\prime})}$ and ${E(xx^{\prime }\otimes xx^{\prime})}$ for a random vector x where x _i has existing moments up to the fourth order and where the higher moments may depend on i. This extends previous results which assumed a common higher moment and E(xx??)?=?I.     

Funny bikes: a symmetrical study of urban space,vehicular units and mobility through the voyeuristic spokesperson of a video lens

This paper presents methodological considerations from a comparative, symmetrical video analysis of cyclist practices in Gothenburg and Toulouse. Video recording pays as much attention to the properties of bicycles as to the characteristics of people; it takes into account the pragmatic and situated dimension and, thus, allows a generalised symmetry. From there, visual methods enable us to submit the collected material to a double treatment of a quantitative analysis of observed bicycles and a qualitative ethnomethodological analysis of bike rental sequences. To better understand the logic and challenges of our method, we present it alongside an analogy with a famous film equivalent – the strategy used by the film-maker Michael Haneke in his heuristic film(s), Funny Games. Despite objectives and content that are obviously completely at odds to one another, the Funny Games film(s) and our own videos share at least five interesting features: twin films, static shots, photomontage, silent films, and rewinding.     

Analysing exponential random graph (p-star) models with missing data using Bayesian data augmentation

Missing data are often problematic in social network analysis since what is missing may potentially alter the conclusions about what we have observed as tie-variables need to be interpreted in relation to their local neighbourhood and the global structure. Some ad hoc methods for dealing with missing data in social networks have been proposed but here we consider a model-based approach. We discuss various aspects of fitting exponential family random graph (or p-star) models (ERGMs) to networks with missing data and present a Bayesian data augmentation algorithm for the purpose of estimation. This involves drawing from the full conditional posterior distribution of the parameters, something which is made possible by recently developed algorithms. With ERGMs already having complicated interdependencies, it is particularly important to provide inference that adequately describes the uncertainty, something that the Bayesian approach provides. To the extent that we wish to explore the missing parts of the network, the posterior predictive distributions, immediately available at the termination of the algorithm, are at our disposal, which allows us to explore the distribution of what is missing unconditionally on any particular parameter values. Some important features of treating missing data and of the implementation of the algorithm are illustrated using a well-known collaboration network and a variety of missing data scenarios.     

Projection estimators of Pickands dependence functions

The authors consider the construction of intrinsic estimators for the Pickands dependence function of an extreme‐value copula. They show how an arbitrary initial estimator can be modified to satisfy the required shape constraints. Their solution consists in projecting this estimator in the space of Pickands functions, which forms a closed and convex subset of a Hilbert space. As the solution is not explicit, they replace this functional parameter space by a sieve of finite‐dimensional subsets. They establish the asymptotic distribution of the projection estimator and its finite‐dimensional approximations, from which they conclude that the projected estimator is at least as efficient as the initial one.     

The matrix affects carabid beetle assemblages in linear urban ruderal habitats

Matrix contrasts affect communities in patchy landscapes by influencing resources, abiotic conditions and spill-over effects. However, current knowledge is significantly biased towards forest and rural communities. We examined the effects of three different matrix types, i.e., low, intermediate and high contrasts, on carabid beetle assemblages at urban railway verges in two climatic regions. Study sites were located in Finland and in Slovenia. Using pitfall trapping, non-metric multidimensional scaling and generalised linear mixed models, we investigated carabid assemblages at railway verges and in differently contrasting adjacent matrices, i.e. built-up, grassland and forest. The matrix influenced carabid assemblages at railway verges. Assemblages grouped with adjacent matrix types, although some Finnish railway assemblages included a characteristic set of open dry habitat species. Abundances of generalist species at railway verges were higher when next to grassland or forest than urban matrices. Habitat specialists responded negatively to high contrast matrices, resulting in lower abundances of open habitat specialists in railway verges when next to forests and nearly no spill-over of forest specialists into railway verges. These patterns were consistent in both countries, i.e. irrespective of climatic region. Our study emphasises effects of the adjacent matrix and matrix contrasts on communities in linear open habitat patches in cities. Knowledge on matrix effects in patchy landscapes, such as urban environments, is essential in understanding the distribution and composition of communities in discrete patches. This knowledge can be used in conservation planning. If habitat specialists are negatively affected by high matrix contrasts, high contrasts should be avoided.     

Stratified Gaussian graphical models

Gaussian graphical models represent the backbone of the statistical toolbox for analyzing continuous multivariate systems. However, due to the intrinsic properties of the multivariate normal distribution, use of this model family may hide certain forms of context-specific independence that are natural to consider from an applied perspective. Such independencies have been earlier introduced to generalize discrete graphical models and Bayesian networks into more flexible model families. Here, we adapt the idea of context-specific independence to Gaussian graphical models by introducing a stratification of the Euclidean space such that a conditional independence may hold in certain segments but be absent elsewhere. It is shown that the stratified models define a curved exponential family, which retains considerable tractability for parameter estimation and model selection.     

How many people participated in candlelight protests? Counting the size of a dynamic crowd

The recent controversy about the size of crowds at candlelight protests in Korea raises an interesting question regarding the methods used to estimate crowd size. Protest organizers tend to count all participants in the event from its start to finish, while the police usually report the crowd size at its peak. While several counting methods are available to estimate the size of a crowd at a given time, counting the total number of the participants at a protest is not straightforward. In this paper, we propose a new estimator to count the total number of participants that we call the size of a dynamic crowd. We assume that the arrival and departure times of the crowd are randomly observed and that the number of the attendees in the crowd at a specific time is estimable. We estimate the number of total attendees during the entire gathering based on the capture-recapture model. We also propose a bootstrap procedure to construct a confidence interval for the crowd size. We demonstrate the performance of the proposed method with simulation studies and the data from Korea''s March for Science, a global event across the world on Earth Day, April 22, 2017.     

Vegetation changes at sub-xeric urban forest edges in Finland – the effects of edge aspect and trampling

The relative strengths of the effects of forest edges and recreational use on understorey vegetation were studied at sub-xeric boreal urban forest edges in the greater Helsinki region, Finland. The study was performed at northern, eastern, southern and western edges, and vegetation sample plots were placed on, next to and away from paths with different trampling intensities 0–107 m from the forest edges. We found that human trampling altered vegetation more than the effects of forest edges. Vegetation changed dramatically on paths and the effects of path edges were seen in seemingly untrampled vegetation at least up to 4 m from the path edge. However, our results suggested that the effect of the edge may penetrate up to 50 m into forest interiors. Changes in vegetation composition indicated that the effects of the edge were stronger at eastern, southern and western than at northern edges.