Classical and robust orthogonal regression between parts of compositional data

The different parts (variables) of a compositional data set cannot be considered independent from each other, since only the ratios between the parts constitute the relevant information to be analysed. Practically, this information can be included in a system of orthonormal coordinates. For the task of regression of one part on other parts, a specific choice of orthonormal coordinates is proposed which allows for an interpretation of the regression parameters in terms of the original parts. In this context, orthogonal regression is appropriate since all compositional parts – also the explanatory variables – are measured with errors. Besides classical (least-squares based) parameter estimation, also robust estimation based on robust principal component analysis is employed. Statistical inference for the regression parameters is obtained by bootstrap; in the robust version the fast and robust bootstrap procedure is used. The methodology is illustrated with a data set from macroeconomics.     

Club forms of activities and creation of educational environment promoting the development of social work students

ABSTRACT

The article presents research on extracurricular forms of club activity as one of the important components of educational activity of social work students at University of Ruse, Bulgaria. The purpose of the research is to identify the impact of this type of extracurricular activity on the formation of positive attitudes towards people of different ethnic background and towards persons with disabilities, stimulating their cognitive, professional and social development. A sample has been formed and research tools have been used that is consistent to the purpose and specificity of the research. The results of the statistical processing of empirical data and their analysis confirm the accepted purpose. They reveal the role and importance of extracurricular forms of club activity to create an interactive learning environment and conditions that form positive attitudes towards the target groups and stimulate students: integrate acquired values, knowledge, skills into curriculum activities with practical experience and detailed information about outside groups; consciously and motivated to includes in equal, tolerant and non-discriminatory interactions in different interpersonal systems; to enhance their cultural competence; to appreciate diversity in the community and society. In synthesis, the presented aspects contribute to the cognitive, professional and social development of social work students.     

Application of additive manufacturing for mass customisation: understanding the interaction of critical barriers

Additive Manufacturing (AM) technology presents a very optimistic case for its application for mass customisation. Even though theoretically suitable, practically several critical barriers inhibit its implementation. Thus, this paper attempts to identify those barriers and also understand the dynamic interaction among them. The barriers were identified by a detailed literature review and validated by expert opinions. Interpretative Structural Modelling (ISM) was applied to determine the mutual influences among the barriers. It was also able to ascertain the level of the barriers and categorise them based on their driving power and dependence. The results are highly useful for industry practitioners to determine the interventions required to overcome the most dominant barriers.     

The contemporary situation and future possibilities for foster care in Bulgaria

This article explores some of the problems connected with building a system of foster care and family placement in Bulgaria. Based on an analysis of the situation of children at risk, especially that of institutionalized children, some directions are presented here, which could help and support the transition to a system of foster care. The short Bulgarian experience in this sphere, which took place first in the early 1940s, and subsequently after the democratic reforms in 1989, has been the starting point of this analysis, and is proof of the responsibility Bulgaria has taken for establishing a sound working system for children's protection.     

Parametric Inference and Dynamic State Recovery From Option Panels

We develop a new parametric estimation procedure for option panels observed with error. We exploit asymptotic approximations assuming an ever increasing set of option prices in the moneyness (cross‐sectional) dimension, but with a fixed time span. We develop consistent estimators for the parameters and the dynamic realization of the state vector governing the option price dynamics. The estimators converge stably to a mixed‐Gaussian law and we develop feasible estimators for the limiting variance. We also provide semiparametric tests for the option price dynamics based on the distance between the spot volatility extracted from the options and one constructed nonparametrically from high‐frequency data on the underlying asset. Furthermore, we develop new tests for the day‐by‐day model fit over specific regions of the volatility surface and for the stability of the risk‐neutral dynamics over time. A comprehensive Monte Carlo study indicates that the inference procedures work well in empirically realistic settings. In an empirical application to S&P 500 index options, guided by the new diagnostic tests, we extend existing asset pricing models by allowing for a flexible dynamic relation between volatility and priced jump tail risk. Importantly, we document that the priced jump tail risk typically responds in a more pronounced and persistent manner than volatility to large negative market shocks.     

Robust selection of variables in linear discriminant analysis

A commonly used procedure for reduction of the number of variables in linear discriminant analysis is the stepwise method for variable selection. Although often criticized, when used carefully, this method can be a useful prelude to a further analysis. The contribution of a variable to the discriminatory power of the model is usually measured by the maximum likelihood ratio criterion, referred to as Wilks’ lambda. It is well known that the Wilks’ lambda statistic is extremely sensitive to the influence of outliers. In this work a robust version of the Wilks’ lambda statistic will be constructed based on the Minimum Covariance Discriminant (MCD) estimator and its reweighed version which has a higher efficiency. Taking advantage of the availability of a fast algorithm for computing the MCD a simulation study will be done to evaluate the performance of this statistic. The presentation of material in this article does not imply the expression of any opinion whatsoever on the part of Austro Control GmbH and is the sole responsibility of the authors.     

Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli,Marco Riani,Anthony C. Atkinson and Aldo Corbellini

This paper discusses the contribution of Cerioli et al. (Stat Methods Appl, 2018), where robust monitoring based on high breakdown point estimators is proposed for multivariate data. The results follow years of development in robust diagnostic techniques. We discuss the issues of extending data monitoring to other models with complex structure, e.g. factor analysis, mixed linear models for which S and MM-estimators exist or deviating data cells. We emphasise the importance of robust testing that is often overlooked despite robust tests being readily available once S and MM-estimators have been defined. We mention open questions like out-of-sample inference or big data issues that would benefit from monitoring.     

Elected in 100 milliseconds: Appearance-Based Trait Inferences and Voting

Recent research has shown that rapid judgments about the personality traits of political candidates, based solely on their appearance, can predict their electoral success. This suggests that voters rely heavily on appearances when choosing which candidate to elect. Here we review this literature and examine the determinants of the relationship between appearance-based trait inferences and voting. We also reanalyze previous data to show that facial competence is a highly robust and specific predictor of political preferences. Finally, we introduce a computer model of face-based competence judgments, which we use to derive some of the facial features associated with these judgments.     

Compositional Tables Analysis in Coordinates

Compositional tables – a continuous counterpart to the contingency tables – carry relative information about relationships between row and column factors; thus, for their analysis, only ratios between cells of a table are informative. Consequently, the standard Euclidean geometry should be replaced by the Aitchison geometry on the simplex that enables decomposition of the table into its independent and interactive parts. The aim of the paper is to find interpretable coordinate representation for independent and interaction tables (in sense of balances and odds ratios of cells, respectively), where further statistical processing of compositional tables can be performed. Theoretical results are applied to real‐world problems from a health survey and in macroeconomics.     

Public Opinion on Foreign Policy: The Multilateral Public that Perceives Itself as Unilateral

Americans have a strong preference for multilateral foreignpolicies over unilateral foreign policies. But do Americansknow their own preferences? Data from a national survey showwide misperceptions of public opinion on foreign policy. WhileAmericans strongly prefer multilateral policies, they overestimatepublic support for unilateral policies. For example, while only23 percent of respondents agreed that the more important lessonof September 11 is that the United States should work aloneto fight terrorism rather than work with other countries, respondentsestimated that almost 50 percent of Americans endorsed thisview. Moreover, misperceptions of public opinion were relatedto subsequent judgments of specific policies. For example, respondentswho incorrectly perceived the unilateral view as the majorityview were 1.84 times more likely to support a presidential decisionto invade Iraq without the approval of the United Nations (UN)Security Council than respondents who correctly perceived theunilateral view as the minority view. Misperceptions of publicopinion were also associated with the belief that the currentforeign policy reflects the opinions of the American people.This belief in the legitimacy of the foreign policy was as stronga predictor of support for specific unilateral policies as respondents’attitudes.