Test of symmetry based on copula function

We introduce some new nonparametric statistical tests of symmetry. The limiting behaviors of the proposed statistics are established under the null hypothesis. Emphasis is placed on explanation of the strong approximation methodology. The asymptotic validity of a re-sampling method to compute p-values is also established. A simulation study for some considered statistics is performed.     

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.     

Protected Sites: Reconceptualising Secret Societies in Colonial and Postcolonial Singapore

Street gangs in Singapore are commonly known as secret societies. The irony behind this term is that these secret societies have not only been contributing to the making of modern Singapore for more than a century, they have often carried out their dealings in the public sphere. These overt operations of the underworld are possible, in part, due to the symbiotic relationship forged between the Chinese triads and the police which have continued till today. Through examining the notion of protected sites, this article explores how the postcolonial state has taken on a similar pragmatic approach as that practised by its colonial predecessor in the management of the criminal underworld.     

An efficient two-stage randomized response model under stratified random sampling

A two-stage randomized response model is extended to stratified random sampling in order to find out more efficient estimators of proportions built from sensitive questions, which respondents may not answer truthfully, in a population divided into homogeneous subgroups. In each subgroup, the respondents who have not answered the sensitive question in the first stage are requested in the second stage to either answer the sensitive question (second attempt then) or to draw a card indicating “yes” or “no”. In the latter case, they are required to report the outcome. Such extension provides a more efficient estimator of the proportion of the population having a given sensitive attribute than its counterpart in simple random sampling. The extended two-stage randomized response model is more efficient than the stratified randomized response model, where respondents must answer the sensitive question either in the first or in the second stage. Moreover, it increases the respondents’ cooperation. When strata weights are unknown, they are estimated by the double sampling method.     

Promoting Civil Society in Contemporary Poland: Gendered Results of Institutional Changes

This paper is a contribution to the ongoing discussion concerning factors determining the development of civil society in a post-state socialist context. It examines the financial mechanisms designed to promote civic engagement in Poland, including EU grants and the so-called ‘percentage law’ that allows citizens to support NGOs of their choice with 1 % of their taxes. A detailed analysis of these mechanisms demonstrates that they are advantageous for some types of non-governmental organizations and not for others. Instead of enhancing the situation of the whole sector, they tend to support NGOs that already have substantial resources and hold a strong position vis-à-vis the state. Moreover, organizations and groups fighting for issues considered to be controversial—such as women’s NGOs advocating for the right to abortion or criticizing authorities for their lack of concern when it comes to violence against women—have limited chances to gain financial support from both the state and those sources that are independent from the state. This shows how seemingly gender-neutral institutional arrangements may bring gendered results. The following analysis is based on available statistics (several reports provided by the Klon-Jawor Association, Social Diagnosis Reports from 2007 and 2011) and qualitative data (semi-structured interviews and discourse analysis of the Polish media).     

Tests for noncorrelation of two multivariate ARMA time series

In many situations, we want to verify the existence of a relationship between multivariate time series. In this paper, we generalize the procedure developed by Haugh (1976) for univariate time series in order to test the hypothesis of noncorrelation between two multivariate stationary ARMA series. The test statistics are based on residual cross-correlation matrices. Under the null hypothesis of noncorrelation, we show that an arbitrary vector of residual cross-correlations asymptotically follows the same distribution as the corresponding vector of cross-correlations between the two innovation series. From this result, it follows that the test statistics considered are asymptotically distributed as chi-square random variables. Two test procedures are described. The first one is based on the residual cross-correlation matrix at a particular lag, whilst the second one is based on a portmanteau type statistic that generalizes Haugh's statistic. We also discuss how the procedures for testing noncorrelation can be adapted to determine the directions of causality in the sense of Granger (1969) between the two series. An advantage of the proposed procedures is that their application does not require the estimation of a global model for the two series. The finite-sample properties of the statistics introduced were studied by simulation under the null hypothesis. It led to modified statistics whose upper quantiles are much better approximated by those of the corresponding chi-square distribution. Finally, the procedures developed are applied to two different sets of economic data.     

Diagonal latent block model for binary data

This paper addresses the problem of co-clustering binary data in the latent block model framework with diagonal constraints for resulting data partitions. We consider the Bernoulli generative mixture model and present three new methods differing in the assumptions made about the degree of homogeneity of diagonal blocks. The proposed models are parsimonious and allow to take into account the structure of a data matrix when reorganizing it into homogeneous diagonal blocks. We derive algorithms for each of the presented models based on the classification expectation-maximization algorithm which maximizes the complete data likelihood. We show that our contribution can outperform other state-of-the-art (co)-clustering methods on synthetic sparse and non-sparse data. We also prove the efficiency of our approach in the context of document clustering, by using real-world benchmark data sets.