Analysis of an European union election using principal component analysis

While studying the results from one European Parliament election, the question of principal component analysis (PCA) suitability for this kind of data was raised. Since multiparty data should be seen as compositional data (CD), the application of PCA is inadvisable and may conduct to ineligible results. This work points out the limitations of PCA to CD and presents a practical application to the results from the European Parliament election in 2004. We present a comparative study between the results of PCA, Crude PCA and Logcontrast PCA (Aitchison in: Biometrika 70:57–61, 1983; Kucera, Malmgren in: Marine Micropaleontology 34:117–120, 1998). As a conclusion of this study, and concerning the mentioned data set, the approach which produced clearer results was the Logcontrast PCA. Moreover, Crude PCA conducted to misleading results since nonlinear relations were presented between variables and the linear PCA proved, once again, to be inappropriate to analyse data which can be seen as CD.     

The exponential COM-Poisson distribution

The Conway-Maxwell Poisson (COMP) distribution as an extension of the Poisson distribution is a popular model for analyzing counting data. For the first time, we introduce a new three parameter distribution, so-called the exponential-Conway-Maxwell Poisson (ECOMP) distribution, that contains as sub-models the exponential-geometric and exponential-Poisson distributions proposed by Adamidis and Loukas (Stat Probab Lett 39:35?C42, 1998) and Ku? (Comput Stat Data Anal 51:4497?C4509, 2007), respectively. The new density function can be expressed as a mixture of exponential density functions. Expansions for moments, moment generating function and some statistical measures are provided. The density function of the order statistics can also be expressed as a mixture of exponential densities. We derive two formulae for the moments of order statistics. The elements of the observed information matrix are provided. Two applications illustrate the usefulness of the new distribution to analyze positive data.     

Weibull and generalised exponential overdispersion models with an application to ozone air pollution

We consider the problem of estimating the mean and variance of the time between occurrences of an event of interest (inter-occurrences times) where some forms of dependence between two consecutive time intervals are allowed. Two basic density functions are taken into account. They are the Weibull and the generalised exponential density functions. In order to capture the dependence between two consecutive inter-occurrences times, we assume that either the shape and/or the scale parameters of the two density functions are given by auto-regressive models. The expressions for the mean and variance of the inter-occurrences times are presented. The models are applied to the ozone data from two regions of Mexico City. The estimation of the parameters is performed using a Bayesian point of view via Markov chain Monte Carlo (MCMC) methods.     

Double-sampling control charts for attributes

In this article, we propose a double-sampling (DS) np control chart. We assume that the time interval between samples is fixed. The choice of the design parameters of the proposed chart and also comparisons between charts are based on statistical properties, such as the average number of samples until a signal. The optimal design parameters of the proposed control chart are obtained. During the optimization procedure, constraints are imposed on the in-control average sample size and on the in-control average run length. In this way, required statistical properties can be assured. Varying some input parameters, the proposed DS np chart is compared with the single-sampling np chart, variable sample size np chart, CUSUM np and EWMA np charts. The comparisons are carried out considering the optimal design for each chart. For the ranges of parameters considered, the DS scheme is the fastest one for the detection of increases of 100% or more in the fraction non-conforming and, moreover, the DS np chart is easy to operate.     

A Pilot Study to Explore the Influence of the ‘Safety First Assessment Intervention’ on the Family Environment

The family environment is considered an important influence on a young person's well‐being. The ‘Safety First Assessment Intervention’ is a model of care that considers and incorporates the importance of family environment when assessing and managing distressed young people. This pilot study explores the influence of the ‘Safety First Assessment Intervention’ on the family environment of young people referred to Child and Adolescent Mental Health Services. A pre‐ and post‐design was used, with families completing the Family Survey before and after their assessment/intervention. The Family Survey was correlated with a validated measure of family function, the APGAR, and pre‐intervention. Significant changes in multiple dimensions of family environment, including reduced level of distress for the adult, increased level of distress for the young person, improved sense of how the family felt the adult was managing currently, and improved confidence in family communication were found. There was no significant change in how the adult understood their role in helping the young person manage their distress. A thematic analysis showed trends in the current concerns for young people and adults as well as the difficulty young people in distress have in identifying their strengths. This pilot study demonstrates that the ‘Safety First Assessment Intervention’ can influence the family environment in a positive way and highlights the importance of using a family‐based approach for distressed young people.     

COVID Health Structure Index: The Vulnerability of Brazilian Microregions

Social Indicators Research - Many developing countries have highly unequal health systems across their regions. The pandemic of COVID-19 brought an additional challenge, as hospital structures...     

Reduced-Bias Tail Index Estimators Under a Third-Order Framework

In this article, we are interested in the comparison, under a third-order framework, of classes of second-order, reduced-bias tail index estimators, giving particular emphasis to minimum-variance reduced-bias estimators of the tail index γ. The full asymptotic distributional properties of the proposed classes are derived under a third-order framework and the estimators are compared with other alternatives, not only asymptotically, but also for finite samples through Monte Carlo techniques. An application to the log-exchange rates of the Euro against the USA Dollar is also provided.     

A note on testing for nonstationarity in autoregressive processes with level dependent conditional heteroskedasticity

In this paper, we investigate the empirical distribution and the statistical properties of maximum likelihood (ML) unit-root t-statistics computed from data sampled from a first-order autoregressive (AR) process with level-dependent conditional heteroskedasticity (LDCH). This issue is of particular importance for applications on interest rate time-series. Unfortunately, the extent of the technical complexity related associated to LDCH patterns does not offer a feasible theoretical analysis, and there is no formal knowledge about the finite-sample size and power behaviour or the ML test for this context. Our analysis provides valuable guidelines for applied work and directions for future work.     

Ownership concentration,contestability, family firms,and capital structure

This study analyses the distribution of power among the several blockholders of a firm and the identity of those blockholders as a determinant of firm leverage. Using a sample of 694 firms from 12 Western European countries, our results support a negative relationship between ownership concentration in the hands of the main blockholder and firm leverage. Moreover, we detect that the presence of a second and third large shareholder (beyond the first blockholder) has a significant positive effect on the leverage ratio. In addition, the results show that contestability in family firms plays a more relevant role. Finally, we show that family firms do have significant impact on firm leverage level, and this impact varies depending on the legal framework and institutional environment. In our main sample the results show family firms negatively affect market leverage, supporting the theory that family firms are more averse to an increase in the debt level due to the risk of bankruptcy and financial distress as a result of having an under-diversified portfolio. In contrast, the opposite effect is found in the sample that excludes the United Kingdom. This last result cannot be explained by agency theory, given that family businesses are those that suffer less from Type I agency problems. This result suggests either some difficulty in financing their investments by issuing new equity or the need to use debt as a signal of the quality of its investments. Our results prove to be stable against a battery of robustness tests.